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Ambiente & Sociedade

versão On-line ISSN 1809-4422

Ambient. soc. vol.17 no.3 São Paulo jul./set. 2014

http://dx.doi.org/10.1590/S1414-753X2014000300010 

Influence of environmental factors on the distribution of families of aquatic insects in rivers in southern Brazil

 

 

Vanessa dos Anjos BaptistaI; Michelle Bicalho AntunesIII; Alcemar Rodrigues MartelloII; Nícolas de Souza Brandão FigueiredoIII; Aline Monique Blank AmaralIII; Elisangela SecrettiIII; Bruna BraunIII

IProfessor, Department of Biology, URI, Campus de Santiago, Av. Bonoto Batista Sobrinho, 733, 97700-000, Santiago, RS. vanessaipp@gmail.com
IIProfessor, Department of Biology, UNESPAR, Campus de União da Vitória, Praça Coronel Amazonas, s /n, 84600-000, União da Vitória, PR. armartello@hotmail.com
IIIPost-Graduation Program in Animal Biodiversity, Federal University of Santa Maria, Av. Roraima, 1000, Subdivision Camobi, 97105-900, Santa Maria, RS. michelleantunes@gmail.com; figueiredonsb@gmail.com; nineblank@hotmail.com; e-secretti@hotmail.com; brumbraun@gmail.com

 

 


ABSTRACT

Neotropical rivers suffer effects of human actions. Conservation measures are based on data from other regions because few studies in this region and limnology knowledge. But it's often inability to realize differences in the environmental variables answer at different scales about aquatic communities. This study aimed: to know aquatic insects richness in a neotropical microbasin to check the environmental variables influence on the distribution of aquatic insects families in four tributaries of this microbasin and to check the rate distribution pattern of aquatic insects families between different rivers orders and different microbasins, according to environmental and spatial variables influence. We found 9,135 individuals belonging to 26 macroinvertebrates families. The communities structure were differed between microbasins. The aquatic insects families were influenced by different spatial and environmental variables in each microbasin.

Keywords: Macroinvertebrates; Lotic; Spatial scale Watershed Distribution.


RESUMEN

Ríos neotropicales sufren los efectos de las acciones humanas. Las medidas de conservación debido a la falta de estudios en la región y de conocimiento límnico, se basan en datos de otras regiones, siendo muchas veces ineficaces por no permitir observar las diferencias en las respuestas de las comunidades acuáticas a las variables ambientales en escalas diferentes. Este estudio tuvo como objetivo: conocer la riqueza de insectos acuáticos en una cuenca neotropical, verificar la influencia de las variables ambientales en la distribución de las famílias de insectos acuáticos en cuatro afluentes de esta cuenca, y observar si el patrón de distribución de las famílias de insectos acuáticos varia entre las ordenes de los ríos y/o entre microcuencas, según la influencia de las variables ambientales y espaciales. Fueron encontrados un total de 9135 individuos distribuidos en 26 famílias de macroinvertebrados. La estructura de las comunidades fue diferente entre las microcuencas. Las famílias de insectos acuáticos fueron influenciadas por las variables ambientales y espaciales diferentes en cada microcuenca.

Palabras clave: Macroinvertebrados; Lótico Escala espacial; Microcuenca; Distribución.


 

 

Introduction

The focus of conservation science is changing from protecting individual species and protected areas isolated (POIANI et al., 2000) for preservation of whole communities within regions (CHANDY et al., 2006). For this, it is necessary to know the structure of communities and how they are influenced by abiotic factors at different scales (regional and local), both on a stretch of one river, as in microbasins, aim of understanding the dynamics of communities in basin as a whole.

Macroinvertebrate communities may be influenced by variables related to either the local spatial scale (eg substrate, water chemistry, habitat conditions) or regional (latitude, biome, continent) (VINSON & HAWKINS, 1996), as well as temporal scales (BROSSE et al., 2003), suffering interference of biotic and abiotic variables and their interactions, which determine the structure of the community that is established. A change in one of these factors can influence the composition and distribution of aquatic organisms (WEIGEL et al., 2003).

Studies conducted in different orders rivers show that both the composition and richness increase from the headwater to the mouth of a river, but also the width, depth, temperature and also the production/respiration, which directly influence the composition and distribution of macroinvertebrates (VANNOTE et al., 1980; JACOBSEN, 2004). However, Statzner & Higler (1986) and Statzner et al. (1988) support the idea that hydric stress associated with the geomorphology of the stream bed is the main factor structuring lotic communities, and that these factors do not always vary in a predictable way along, so that there is the possibility of finding a pattern in the distribution of macroinvertebrates from the headwater to the mouth. Cornell (1999) argues that processes regional (biogeographic) and historical (evolutionary) scales are probably more important than the interactions between species.

In a study in northern Ecuador, in four microbasins, it was found that when communities of aquatic insects are analyzed along a longitudinal gradient, based on altitudinal zones, the identification to the family level is satisfactory because the same family aquatic insects can occur in different regions, with different influences of abiotic factors. The same is not verified for species that have high turnover in wider ranges (JACOBSEN, 2004). The use of the family level for taxonomic identification can also reduce problems of identifying and subsampling, increasing the reliability and robustness of the patterns revealed in longitudinal and environmental independent gradients of regions (RAHBEK, 1995). Furthermore, in studies in France (BOURNAUD et al., 1996), Denmark (FRIBERG & JACOBSEN, 1997) and in Britain (WRIGHT et al., 1998) it was found that the richness of families of aquatic insects is highly correlated with species richness.

In Brazil, studies on the diversity of benthic macroinvertebrates communities in lotic environments have generally focused on composition and spatial distribution in local scale, i.e., covering a stretch of river or a unique microbasin (e.g. TAKEDA et al., 1991; BAPTISTA et al., 2001; KIKUCHI & UIEDA, 2005; AYRES-PEREZ et al., 2006; BALDAN, 2006; HEPP & SANTOS, 2008; NESSIMIAN et al., 2008; RIBEIRO et al., 2009).

In the state of Rio Grande do Sul, only four studies were conducted along a longitudinal gradient: (i) in the Sinos River basin, for the analysis of water quality through the biomonitoring of aquatic insect communities in three streams second order (BIEGER et al., 2010.); (ii) in sixteen streams without specific hydrologic order (STRIEDER et al., 2006.); (iii) in two microbasins Jacuí River and one in Ibicuí in sites from 1st to 4th orders (SALVARREY et al., 2014) and (iv) in the Ibicuí River basin in four microbasins in sites from 1st to 4th orders, to analyze the distribution of communities of mollusks (FREITAS et al., 2011).

In this context, the aim of this study is to provide information about the spatial composition and structure of aquatic insect community along a longitudinal gradient (from 1st to 4th orders) in four microbasins in southern Brazil.

 

Materials and Methods

The Ibicuí River basin is located in the Pampa biome, on the western border of the State of Rio Grande do Sul, with 36,397.69 km2 drainage area, the largest basin of the Uruguay River Basin (www.comiteibicui.com.br - accessed 07.04.2012). The study area covers two of the three morphological units in the Ibicuí River basin is inserted: Planalto da Serra Geral; Depressão Central and grasslands, which dominate this space with the exception of riparian forests along rivers (LETURCQ et al., 2012). In plain, is characterized by vegetation consisting of grasses, creeping plants, some trees and shrubs found near watercourses (MARCHIORI, 2002).

The climate in the region is subtemperado with distinct seasons and an annual mean temperature of 18.1 ºC to 22 ºC and 13 ºC the average temperature of the coldest month. Rainfall is well distributed and reaches higher annual values to 1400 mm (MALUF, 2000). Considering this hydric balance, the region is included between sub-humid and humid climate classes (MALUF, 2000).

The economic basis of the region is agriculture, especially the cultivation of rice, which is the main water use (90% of the use of surface water). Water quality is affected by the lack of treatment of domestic and industrial sewage with heavy discharge of organic matter. Addition to agriculture, there are livestock and extraction of sand (www.comiteibicui.com.br - accessed 07.04.2012).

 

Sampling sites

Sampling was conducted at eight sites in the four microbasins belonging to the Ibicuí River basin: Inhacundá-Caraí Passo (IC), Miracatu-Taquari (MT), Lajeado Grande (LG) and Sanga Santo Antônio (SA) (Figure 1). The MT and IC microbasins are located north of the main channel, with the highest altitudes reaching 285 m to 358 m and the lower altitudes, 145 m to 77 m, respectively. The microbasins LG and SA are located south of the Ibicuí River, with altitudes ranging 48 to 161 and 36 m to 98 m, respectively (Table 1). The longest linear distance is 81 km between the SA1 and MT1 points, and the closest features 7 km between the MT1 and IC1 points.

In each microbasin, sites of orders 1st, 2nd, 3rd and 4th were sampled, with two replications were pooled in a single sample, due to the low N of aquatic insects in each replicate, with four sampling sites per microbasin, totaling 16 sites sampling.

For each site, we measured environmental factors, such as geographic coordinates (UTM) and altitude (m), using GPS, shading, river width, presence of macrophytes and land use, with the help of topographic maps (Table 1).

 

Sampling and identification

Samplings were conducted in April and May 2010. At each site, macroinvertebrates were collected with the help of a Surber sampler with an area of 30 cm x 30 cm. Individuals collected were preserved in 70% ethyl alcohol in plastic containers and taken to the laboratory for analysis. In the laboratory, individuals were counted and identified to taxonomic family level, with the help of specialized literature (MERRIT & CUMMINS, 1996; BORROR & DELONG, 2005; DOMÍNGUES & FERNÁNDEZ, 2009; MARIANO & FROEHLICH, 2010).

Abiotic factors were also measured, such as: air temperature (ºC) water temperature (ºC), dissolved oxygen (mg/L), water velocity (m/s), pH, electric conductivity (µS) with the help of thermometer, oximeter, peagameter and conductivity, in situ. In addition to these variables, also the concentration of Ca and Fe (mg/L), biochemical oxygen demand (mg/L), chemical oxygen demand (mg/L) were analyzed. Analyses of dissolved solids and chemical oxygen demands and biochemistry were performed at the Laboratory of Rural Water (LAR/UFSM). To analyze the granulometry of the sediments, we used the method of screening based on the Wentworth grain-size scale.

 

Statistical analysis

The variation between environmental factors (temperature of air and water, dissolved oxygen, calcium, iron, biochemical and chemical oxygen demand, altitude, water velocity, pH, electrical conductivity and grain size) between different orders of rivers and between different microbasins was verified through an analysis of variance (ANOVA).

To verify the existence of significant differences between the abundance of aquatic insects, among the different orders of the sampling sites and also for the richness an Analysis of Variance (ANOVA) was performed. The same was done to verify the existence of significant difference in abundance and richness in communities of aquatic insects between the microbasins.

To evaluate whether the communities that inhabit different orders are similar or if the similarity is greater among microbasins non-metric multidimensional scaling (NMDS) was performed. The Bray-Curtis dissimilarity was used (LEGENDRE & LEGENDRE, 1998).

Canonical Correspondence Analysis CCA was used to detect how much of the variability in taxonomic composition is explained by environmental variables (LEGENDRE & LEGENDRE, 1998). To transform the geographical coordinates in a matrix of Euclidean distance, was made a Principal Coordinate Analysis of Neighbor Matrices (PCNM) (BORCARD et al., 2002). The spatial covariate was used as a spatial matrix in CCA through the manual variable selection (forward stepwise) procedure, whereby only significant variables are added (p < 0.05 by Monte Carlo permutation test with 999 randomizations).

The biotic data were logarithmized [log10 (x +1)] and environmental variables (water temperature, dissolved oxygen, biochemical oxygen demand and chemical oxygen demand, altitude, water velocity, conductivity, river width and grain size) were transformed by square root and standardized by standard deviation. Data were logarithmized to stand homoscedastic (SOKAL & ROHLF, 1995). The standardization of environmental data was performed to homogenize the scale of different units of measure included in the environmental matrix (eg, µS for electrical conductivity and mg/L for dissolved oxygen) (CLARKE & GORLEY, 2006).

After the result of the CCA, the partition of variance was applied, with the aim of identify what percentage of variation of environmental, spatial factors and environmental factors and their influence on the structure of aquatic insect community (BORCARD et al., 2002).

 

Results

Among the environmental factors analyzed (Table 1), only four showed a significant variation between microbasins and a factor ranged between orders of the rivers. The air temperature ranged between MT and SA microbasin (ANOVA, F(3.12)= 3545, p=0.040). The water temperature ranged between LG and SA microbasins (ANOVA F(3.12) =5.884, p=0.019) and between MT and SA microbasins (ANOVA F(3,12)= 5.884, p=0.014). The quantity of Fe ranged between microbasins SA and IC, LG and MT (ANOVA F(3.12)= 24,658, p=0.001). The biochemical oxygen demand ranged between IC and LG (ANOVA F F(3.12)= 5.759, p=0.011). There was no significant difference between the analyzed factors and the orders of the rivers, except the very fine sand factor ranging between 4th order and other (ANOVA F(3.12)= 7.312, p= 0.011, 1st order; p= 0.040, 2nd order; p= 0.006, 3rd order).

In total 9,135 individuals were collected, distributed in 26 families of aquatic insects. The microbasin with the highest number of families was Inhacundá-Caraí Passo (IC), with 24 families of aquatic insects, followed by Miracatu-Taquari (MT), with 21 families, Lageado Grande (LG), with 15 families and Santo Antônio (SA) with ten families. There was no significant difference in species richness (Anova, F(3.12)= 2.805, p = 0.085) and abundance (Anova, F(3.12)= 1.095, p>0.05) between microbasins. When we analyzed the richness and abundance of aquatic insect communities between orders, no significant differences were found (ANOVA, F(3.12)= 2.244, p>0.05) and (ANOVA, F(3.12)=2.522, p>0.05), respectively. The only family of aquatic insect that occurred in all sampled sites was Chironomidae, followed by Baetidae, which not only occurred in one site. Other families of aquatic insects were also representative as Elmidae, which occurred in 11 of the 16 sites sampled, Calopterygidae and Hidropsychidae that occurred exactly in half of the sites sampled (Table 2).

Through the NMDS, we obtained a stress value equal to 0.08, representing proper adjustment (KRUSKAL & WISH, 1978), verifying a standard ordering between microbasins, especially in Inhacundá-Caraí Passo and Santo Antônio and between local orders 1st, 2nd and 3rd of microbasins Lageado Grande and Inhacundá-Caraí Passo. We can observe this same pattern between the first three orders of the microbasin Inhacundá-Caraí Passo and the 1st and 2nd orders of the microbasin Miracatu-Taquari. The sites 4th orders have a tendency to stay separate (Figure 2).

The canonical correspondence analysis (CCA) has revealed that families of aquatic insects are influenced by five environmental variables (Figure 3A): biochemical oxygen demand (BOD), chemical oxygen demand (COD), water velocity, cobble and silt (CCA, F=2.212, p=0.0010). Families are influenced by the BOD: Hydrophilidae, Hydroptilidae, Caenidae, Perlidae, Corydalidae, Helicopsychidae and Polycentropodidae. Cordullidae was influenced by COD, while Baetidae, Chironomidae and Empididae were by silt. The water velocity influenced families: Elmidae, Calopterygidae, Grypopterygidae, Libellulidae and Osotomidae. The pebble influenced families: Philopotamidae, Gomphidae, Ceratopogonidae, Leptophlebiidae and Hydroptilidae.

Similarity occurred in the distribution of the families of aquatic insects when the environmental variables were related to sampling sites through the CCA. These variables that significantly influence differ between microbasins and rivers in different orders. The first axis of the CCA showed positive correlation with silt and water velocity and negative with COD, BOD and pebble. The second axis was positively correlated with silt, COD and BOD and negative correlation with pebble and water velocity. In general, the axis 1 segregated sites of 1st and 3rd orders of the IC, LG and MT microbasins and in total microbasin SA. The axis 2 segregated sites 2nd and 4th orders of microbasins IC, LG and MT (Figure 3B).

Based on the analysis of partition, it is found that only 31% of the parameters that influence the distribution of aquatic insects were not included in this study, and that the distribution of families of aquatic insects in the Ibicuí River basin is strongly influenced by environmental variables (environment = 44%; spatial = 11%; environment + spatial = 14%).

 

Discussion

The significant results for the environmental variables between the microbasins studied demonstrate the need to understand that the rivers of the same basin suffer different influences, and evidence the need for analyzes in broader scales, such as microbasins and basins to infer the distribution of aquatic communities. This study demonstrates the need for individual assessments of anthropogenic effects in each microbasin demonstrating the fragility of decisions related to an aquatic system based on studies in different microbasins.

The families richness of aquatic insects found in this study is similar to that found in the Rio das Antas Basin and Gravataí River basin, totaling 25 families of aquatic insects (BUENO et al., 2003), and the Jacutinga River basin, with 27 families (HEPP & SANTOS, 2005). However, the richness found here is higher than that found in the Pelotas River basin and Taquari-Antas basin, with 18 families (BUCKUP et al., 2007), and lower than that found in the Tigre River basin and the Campo River basin, with 32 families (KÖNIG et al., 2008). Thus, the sampling carried out contemplates the results found in other studies, with satisfactory to the conclusions obtained.

The study area is inserted in an environmental matrix that is characterized by agriculture and livestock activities across its extension (Table 1). The land use is strongly related to patterns of large-scale (geographic), but patterns in the levels of land use influence water chemistry and subsequently biotic assemblages (eg communities of invertebrates and fish) (WILEY et al., 1990; ALLAN et al., 1997; TOWNSEND et al., 1997). The community structure can be more sensitive to disturbances of local land use than the ecosystem processes that incorporate both biotic and abiotic components in spatial scales broader (SPONSELLER et al., 2001).

The abundance of organisms collectors at all sampling sites, mainly Chironomidae, indicating an enrichment of organic matter in the sediment (DÉVAI, 1990). The entry of particulate organic matter depends of place characteristics and riparian vegetation, while the hydrological regime (which affects the distribution of sediment and channel conditions) is the result of regional climate and geology (ALLAN & JOHNSON, 1997). The Baetidae family is known for its ability to colonize and presents rapid growth (CALLISTO et al., 2001), which makes possible its presence in water bodies with different land uses.

The larvae and adults of Elmidae are common in regions of high water velocity and high oxygen content (BRIGHAM & WHITE, 1996), this aspect may explain its occurrence in the sampling sites. In this study, Elmidae was correlated with the water velocity and amount of pebble. Calopterygidae presented distribution in temperate and tropical environments and was present in 65% of sampling sites (CÓRDOBA-AGUILAR & CORDERO-RIVERA, 2005). Studies indicate that the adaptations of the larvae are related to biotic and abiotic factors (CORBET, 1999). Hydropsychidae can also be considered of high environmental tolerance (BUSS et al., 2002), and occurs in most studies with biomonitoring, such as Biasi et al. (2008) and Hepp & Santos (2009).

The microbasin Inhacundá-Caraí Passo was presented the highest richness. However there was no significant difference between the number of families present with other microbasins. In cluster analysis it is found that this microbasin is separated from the others, probably by higher levels of dissolved oxygen and water velocity. In addition to a neutral at all the sampling sites, and availability of refuge, with the presence of boulder and pebble. Greater abundance and richness found in areas with currents have already been widely discussed in the literature (ALLAN & CASTILLO, 1995; UIEDA & GAJARDO, 1996), for environments with rapid flow generally have more oxygen and food availability (MERRITT & CUMMINS, 1996).

There was a separation between microbasins and between sites from 1st to 3rd order with the 4th order based on NMDS. The components and processes that occur in a river can be seen as part of an interconnected system (VANNOTE et al., 1980; CORKUM, 1989). Most studies have assumed, at least implicitly, that local patterns are primarily determined by local processes (PALMER et al., 1996).

In the present study, local rivers of orders intermediate would provide the presence a greater abundance of organisms, mainly local first order. This pattern could be explained by the presence of macrophytes at all sites of first orders, and this vegetation hosts a community of insects varied and abundant due to support conditions that provide (ROSINE, 1955; GLOWACKA et al., 1976; MASTRANTUONO, 1986).

The segregation of the microbasins in this study also occurred in the Yakima River basin in the United States in 60 sites distributed in stretches from 1st to 6th order (CARTER et al., 1996). This distribution of species correlated with environmental variability and not the order of the rivers (CARTER et al., 1996). The same pattern was found for Boyero (2003), in two basins in central region of Spain, and Donald & Anderson (1977), in Canada, where the richness varied considerably among microbasins. The larger the scale of the study, the environment is more heterogeneous (FORMAM & GODRON, 1986), and spatial heterogeneity in rivers is complex and evident when examining multiple spatial scales (SCHLOSSER, 1991).

Among the environmental variables, pebbles and silt influenced the distribution of families of aquatic insects in the Ibicuí River basin. These variables were related to microbasins and not the orders of rivers. The texture, the degree of compaction, particle size and surface area of the sediment may influence the composition and abundance of species (NAKAMURA & KIKUCHI, 1996). Although the composition of the substrate is similar within each microbasin, it appears that the water velocity also varies and is determinant in the distribution of families. The velocity of the water exerts a direct physical force to organisms, but this variable also affects other factors within the river as substrate composition, distribution of nutrients and oxygen content (CORKUM, 1989; WIBERG-LARSEN et al., 2000). Some environmental variables such as nutrients, sediment and hydrology are more influenced by regional-scale features, while others are more controlled variables at the local scale (eg vegetation cover on a site) (ALLAN et al., 1997).

Addition to the importance of the substrate as habitat, as protected from currents and predators (ALLAN & CASTILLO, 1995), deposition of fine sediments, in the case of silt, often due to human activities, can have major consequences for aquatic organisms (LUEDTKE & BRUSVEN, 1976; NEWCOMBE & MACDONALD, 1991). In Trichoptera, Hydropsychidae mainly for family, fine sediment is deposited on the nets of captures produced by these individuals, causing damage and increasing energy expenditure for maintenance and reconstruction (STRAND & MERRIT, 1997).

Biochemical oxygen demand and chemical oxygen demand were decisive factors for the distribution of families of aquatic insects in the Ibicuí River basin. Larsen et al. (2009) found that BOD values are greater in pastures with lower richness of aquatic insects, and small variations in this parameter are sufficient to affect the community of these individuals (CLEWS & ORMEROD, 2008). In the present study, the BOD influenced the distribution of aquatic insects in the Inhacundá-Caraí Passo basin, in sites of 1st, 2nd and 3rd order, and the Miracatu-Taquari basin in site of 3rd order.

The chemical oxygen demand is negatively related to the distribution of aquatic insects in sites of 1st and 3rd order microbasin in the Lageado Grande and sites of 1st and 2nd order in microbasin Miracatu-Taquari. The COD is directly related to the presence of untreated effluents in water bodies (ALLAN & CASTILLO, 1995; PIEDRAS et al., 2006). In relation to eutrophication, some macroinvertebrates feature sensitivity (BACEY & SPURLCK, 2007) while others have a high tolerance, an increase of abundance in their communities as a response to organic enrichment caused by human activity (MARQUES et al., 1999; CALLISTO et al., 2005). In addition, the study conducted in microbasins with naturally acidic waters in New Zealand, was also not found correlation between the variables richness and pH (WINTERBOURN & COLLIER, 1987).

Through the partition observe the interaction of spatial and environmental factors explained only 14% of the distribution of families of aquatic insects, and spatial, only 11% and the environmental variables that most influence (44%) along the Ibicuí River basin. Although some studies have shown that landscape factors such as geology and surface area or geographic factors (latitude and distance of sampling sites in the river) are as important as the physical and chemical characteristics of the river (e.g. CORKUM, 1989; LAMMERT & ALLAN, 1999), the present study these variables were less explanatory.

Overall, the geographic distance also contributes to the increased diversity (MYKRÄ et al., 2007), such that, in the Ibicuí River basin, the greater the geographical distance between microbasins (e.g. SA and MT), the greater the possibility of increasing the occurrence of families of aquatic insects. The effect of geographic distance appears at small spatial scales (DIXO & VERDADE, 2006), as in Miracatu-Taquari and Inhacundá-Caraí Passo microbasins that even nearby showed some differentiation in the richness and occurrence of families of aquatic insects. Studies have shown that factors at large scales can excellent predictors of community structure (e.g. CORKUM, 1989; RICHARDS et al., 1996). However, little attention has been given to the relative influence of environmental variables measured at different spatial scales on local diversity of aquatic macroinvertebrates (VINSON & HAWKINS, 1998). Disregarding the spatial scale may arise ecological incorrect conclusions (WIENS et al., 1987; THOMAS & TAYLOR, 1990). The analysis in broader scales are a promising approach to discovery of patterns in the distribution families and aquatic insects which results at a local should not be extrapolated to others.

 

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Submitted on: 18/03/2013.
Accepted on: 19/09/2013.

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