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Ichthyofauna as bioindicator of environmental quality in an industrial district in the amazon estuary, Brazil/Ictiofauna com indicador biologico estuarino em um distrito industrial, estuario amazonico, Brasil.

1. Introduction

The Amazon estuary is the oceanic outlet of the World's largest hydrographic basin, with a total discharge equivalent to approximately one sixth of that of all the rivers in the World combined, containing one fifth of all the freshwater released into the planet's oceans (Martinelli et al., 1989). The dynamics of this estuary reflect the force of this discharge into the Atlantic Ocean, which is so strong that seawater rarely passes through the mouth of the river (Nittrouer et al., 1995). The composition of the region's ichthyofauna is influenced by seasonal fluctuations in salinity levels and the turbidity of the water, which is controlled by the estuarine plume (Barthem, 1985). Within the Amazon estuary, more precisely in the estuary of the Para River, an important industrial hub is located, where activities include the processing of kaolin, alumina and aluminum for export. These processes produce residues which may liberate substances with significant impacts on the quality of the water (Rubio and Tessele, 2002). The principal sources of risk include leaks from tanks and pipelines, accidental spills of toxic substances and the overflowing of residue sedimentation pools, all of which have been recorded in the study area since the establishment of the industrial installations (Lima et al., 2011).

A number of studies have shown that the degradation of aquatic ecosystems exposed to discharges of industrial waste may lead to a reduction in the abundance of commercially-important species, resulting in economic and social problems for local communities (Kennish, 1985; Blaber, 2000).

Estuarine environments, in particular that of the Amazon, which surrounds the cargo terminal, are characterised by high primary and secondary productivity and provide nurseries for numerous species of fish and other aquatic organisms, many of which are of commercial value. This study area is an estuarine environment with a considerable freshwater input, being classified as a tidal freshwater estuary according to the scheme of Elliott and McLusky (2002). Despite the intense industrial activity at the estuary of the Para River, the area is an important artisanal fishing ground and the local population is highly dependent on fishery resources (Paz et al., 2011). In addition to its socio-economic importance, the area plays an important ecological role in the reproduction, feeding and development of many fish species.

Biological monitoring is a method of assessing water quality through the responses of biological communities to changes in environmental conditions (Whitfield and Elliott, 2002; Goulart and Callisto, 2003). Fish can be effective bioindicators and have been used successfully for the assessment of the quality of many freshwater environments in the Amazon basin and estuarine environments, in the case Guajara Bay (Viana et al., 2010). In the present study, to diagnose the environmental quality in an industrial district in the Amazon estuary, the icthyofauna was used as bioindicator, through the use of different ecological descriptors.

2. Material and Methods

2.1 Study area and data collection

The study area is located on the right bank of the estuary Para River in the Brazilian state of Para, the Amazon estuary.

This work was designed to test the effects of the probable environmental contamination in the area adjacent to the industrial installations and cargo terminal in the estuary of the Para River. For this, the collection fish specimens were organised in three distinct Zones, representing different levels of impact: Zone 1, located in the vicinity of the cargo terminal and industrial district (Figure 1), where the risk of contamination was highest; Zone 2, adjacent to Capim Island (Figure 1), distant at 16.98 km of the cargo terminal and industrial district, classified as a median risk area due to its relative proximity to the Zone 1 and Zone 3, located in Oncas Island (Figure 1), at 38.42 km of the cargo terminal and industrial district, classified as minimum risk due to its distance from Zone 1.

Two different types of environment--the main river channel and tidal channel--were sampled in all three Zones. Samples were collected every three months, between 2009 (June and September) and 2010 (January and April), covering the region's principal climatic periods: rainy-dry transition (R-D), dry season, dry-rainy transition (D-R) and rainy season (R). All samples were collected during neap tides in all Zones for each climatic period.

Different sampling protocols were used in the main channel and tidal channel, due to their distinct dynamics. In the channel, monofilament gillnets with different stretched mesh sizes were used (25, 35 and 40 mm) and the total net was 133.2 m. The nets were allowed to drift for an average soak time of 1 h 30 min. In the tidal channel, a block net (25 mm mesh size) was set at the mouth of the tidal channel, closing it completely. Blocking was initiated at the end of the high tide and continued throughout the entire ebb tide cycle (c. 6 h). The fish were caught either by being gilled in the net (smaller specimens) or collected manually in the pools remaining near the net. All specimens were stored on ice and transported to the laboratory for processing. Samples were standardised for all study areas and environments.

2.2 Data analysis

The fish specimens were identified to the lowest possible taxonomic level, based on FAO (1992) and Keith et al. (2000).

For the evaluation of areas subject to different levels of contamination (Zones 1,2 and 3), the data were analysed in the context of environmental differences (main channel and tidal channel). The main channel and tidal channel habitats were analysed separately due to the ecological differences found between them and the consequent possibility of different responses to anthropogenic impacts (Viana et al., 2010). Seasonal variation was considered as replicates since no significant difference was reported between periods of the year for the biological analysis.

The individuals were classified by size, following Viana et al. (2010). Species captured with total length of less than 15 cm were classified as small, those between 15 cm and 30 cm in length as medium and fish over 30 cm in length as large. Variation in the body size of the different species among Zones was analyzed using the Kruskal-Wallis test.

The frequency of occurrence of the different fish species was evaluated based on the scheme proposed by Dajoz (1973). Species with a frequency of occurrence of [greater than or equal to] 50% were classified as constant, those with a frequency between 25 and 50% as accessory and those with a frequency of <25% as occasional.

Feeding functional groups, based on feeding preferences and strategies, were defined for each area. For this, species were allocated to feeding groups (based on Krumme et al., 2004 and Elliott et al., 2007): zooplanktivore (ZP); detritivore (DV); piscivore (PV); zoobenthivore (ZB); opportunist/ omnivore (OP). Two additional categories were included piscivore/zoobenthivore (PV/ZB). The trophic categories were identified by combining the regional information available on predominant diet (Krumme et al., 2004; Brenner and Krumme, 2007; Raiol, 2007, Almeida et al., 2010, Barbosa et al., 2012) and stomach examination of several species. Where little information was available, trophic preferences were inferred from data gathered by the Fishbase project (Froese and Pauly, 2007). The percentage contribution of each functional category to the total species richness and individual abundance was calculated for each area. The results were compared among groups in order to assess the prevailing feeding strategies adopted by fish community.

The Catch per Unit of Effort (CPUE) was used to assess the relative abundance of fish in the main channel, while density was used for the tidal channel. The CPUE values were based on the numerical abundance or density (number of individuals, n) and biomass (total weight, b). For the main channel, CPUE = 100n or b [([AT.sub.i]).sup.-1], where A is net length in metres, and [T.sub.i] is soak time in minutes. In the case of the tidal channel, the density index was obtained by n or b/Ai, where Ai is the flooded area, which was estimated for each tidal channel at the peak of the high tide during the neap tide.

Shannon's diversity index (H'), Pielou's evenness index (J), Simpson's index (l), total species present (S) and Margalef's index (D) were used to assess community structure.

The differences in the values of these indices among the different study Zones were evaluated using one-way ANOVA. When necessary, the data were log (x+1) transformed to make the normality and variance homogeneous. Tukey's test was used to determine the normality and Bartlett's test was used to determine the homogeneity of the variances. Differences were further explored with Tukey's post hoc test. For nonparametric data, the Kruskal-Wallis analysis of variance was used.

A multivariate multidimensional scaling (MDS) analysis was used to evaluate the effects of spatial (Zones) in species composition and to identify distinct groups. Groups were subsequently examined using the similarity percentages analysis (SIMPER). All groups were also tested using the analysis of similarities two-way nested ANOSIM (Clarke and Warwick, 1994). Catch per unit of effort (CPUE) was used as data entry for multivariate analyses.

3. Results

A total of 1.708 fish specimens belonging to 77 species, 27 families and 10 orders were captured. Considering both main channel and tidal channel, 23 species were captured in Zone 1, 49 in Zone 2, and 50 in Zone 3 (Table 1). The Plagioscion squamosissimus (Heckel, 1840) [22.1% of the total] and Lithodoras dorsalis (Valenciennes, 1840) [with 21.7% of the total] were the most abundant species.

Medium-sized fish predominated in all Zones, with an overall average 65.6%. Large fish were least common in Zone 1, whereas small fish were least common in Zone 3. The largest proportion of species classified as constant was recorded in Zone 1, in both main (33.3%) and tidal channels (44.4%). Accessory species predominated in Zone 3, in both main (44%) and tidal channel (62.7%), while occasional species were common in all Zones, principally the main channel (Table 1).

The CPUE values for both numerical abundance and biomass indicated a significantly higher abundance in Zone 1 for main channel (ANOVA, p < 0.05). For tidal channel, Zone 3 returned the highest density and biomass values, which were significantly different from those of the other Zones (Kruskal-Wallis,p < 0.05).

Considering the different feeding functional groups, there was a predominance of piscivore/zoobenthivore (PV/ ZB) and zoobenthivore (ZB) species in all areas, in terms of the percentage of species, except in Zone 1 in the main channel. The Zooplanktivorous (ZP) were also relatively important in Zone 1. The Piscivorous (PV) were not captured in the channel in any of the three Zones and the lowest diversity of feeding groups was recorded in Zone 1 (Figure 2a). Similar patterns are observed when individuals rather than species are considered, with a predominance of the PV/ZB and ZB categories, although opportunists/ omnivores were prominent in both the main channel and tidal channel of Zone 3 (Figure 2b).

Comparing the main channel of Zone 1 with those of the other Zones, all indices were significantly different (ANOVA, p < 0.05), except for evenness. The post test identified significantly lower values for species richness Shannon's and Margalef's index and higher values for abundance, dominance and Simpson's index (Figure 3). In the case of the tidal channel, significant differences were found only for species richness and evenness, with lower values being recorded for the latter parameter in Zone 3 (ANOVA, p < 0.05), but much higher species richness in comparison with Zone 1 (Figure 3).

The multivariate analysis identified distinct groups between three area in both main channel (ANOSIM, p < 0.05) and tidal channel (ANOSIM, p < 0.05) with significantly different habitats showed by ANOSIM test (Figure 4). The main species responsible for the discrimination of these groups was, in the main channel, Lithodoras dorsalis, Plagioscion squamosissimus andPellonaflavipinnis (zones 1x2 and 1x3) and, in the tidal channel, Hypophthalmus marginatus and Sternopygus macrurus (for zones 1x2) and L. dorsalis and P. squamosissimus (for zones 1x3).

4. Discussion

Human activities in estuarine environments tend to have negative effects on the local biota. Together with other waste, pollutants circulate extensively under the influence of the river discharge and tidal currents, often resulting in concentrations well above legally-defined limits (Whitfield and Elliott, 2002; Eddy, 2005), although in most cases, few data are available on the integrity of these environments.

In spite of the considerable impacts that have affected the study area since the construction of the local port by the Para Dock Company and the subsequent installation of mineral ore-processing industries, the ichthyofauna of the estuary of the Para River is characterized by a considerable diversity, with a total of 77 species being recorded within the study area. However, this diversity was much lower in the area closest to the port (Zone 1), where only 23 species were recorded, in comparison with the less impacted areas, which presented fauna typical of other tropical estuarine environments (Barthem, 1985; Krumme et al., 2004; Paiva et al., 2008; Viana et al., 2010).

In general, constant species were more numerous in the tidal channel than the main channel. These species spend their whole life cycle in these habitats, which are more favourable to their development, given the relative abundance of refuges and feeding resources (Ruffino, 2004; Viana et al., 2010). However, as observed in Guajara Bay, which is adjacent to the present study area, tidal channel are also more vulnerable to contamination, resulting in a faster response from the fish species, given that it takes longer to filter out contaminants in comparison with the open channels (Viana et al., 2010).

The analysis of diversity indices is one effective way to evaluate the health of an aquatic environment (Lopez-Rojas and Bonilla-Rivero, 2000; Whitfield and Elliott, 2002). Anthropogenic impacts are known to modify species composition through the elimination of the most sensitive taxa and the subsequent dominance of the more tolerant species (Attrill and Depledge, 1997). In our study, for both types of habitats, however, while species richness was lower in Zone 1, which is most vulnerable to industrial contamination, most species were constant, which appears to reflect their capacity to adapt to impacted environments. This does not necessarily mean that the area is healthy given the possibility of chronic processes, such as the accumulation of heavy metals in body tissue and histological alterations of vital organs, such as the liver, kidneys and gills (Triebskorn et al., 2008). In the same study area, Viana et al. (2012) observed that, for P. squamosissimus and L. dorsalis (main species), clear evidence of histological alterations in the specimens captured in the most impacted area (Zone 1) and severe and irreversible alterations of the liver have been registered for these species (Viana et al, 2012).

Medium-sized fish (TL = 15-30 cm) predominated in all three Zones, although larger fish were more common in the Zones further from the industrial area, presumably reflecting anthropogenic factors. The specie L. dorsalis, for example, presented smaller individuals in the zone 1 (TL = 17,43 [+ or -]4,4) in comparison with the zone 3 (TL = 30,36 [+ or -]10,9).

As in the present study, descriptive indicators for the structure of size classes have been used by a number of authors to evaluate seasonal and spatial variation in fish communities. In Senegal, for example, a decrease in the maximum length of fish was observed after 20 years of anthropogenic impact (Ecoutin et al., 2010). According to Yemane et al. (2008), the decline in both the mean maximum length and the number of fish species able to attain maximum length may be considered indicators of disturbances in the fish community, in this case, from overfishing. In the present study, the smaller proportion of larger-sized fish recorded in the impacted areas may reflect an ecological response to anthropogenic disturbance.

Also, in this study, the ecological indices indicated that the structure of the community closest to the industrial area and cargo terminal is the most impacted, based on the low values for species richness and the Shannon and Margalef indices and elevated dominance (Simpson). The most distant tidal channel (Zone 3) was relatively rich (Margalef index), but equitability was low, indicating a non-uniform distribution of species. The reduced equitability was probably influenced by the dominance of L. dorsalis and P. squamosissimus.

Species representative of all different feeding modes are expected in natural estuaries, as well as a predominance of bottom-feeders (Blaber, 2000; Chaves and Umbria, 2003; Paiva et al., 2008). This pattern was observed in all parts of the study area, in terms of both the number of species and individuals, given the predominance of zoobenthivores, piscivore-zoobenthivores, opportunist-omnivores and detritivores. A reduced number of trophic categories was recorded in the main channel of Zone 1. Environments that have suffered anthropogenic impacts tend to lose organisms at the top of the food chain (Browne and Lutz, 2010; Ecoutin et al., 2010), in this case, piscivores, as well as trophic specialists. According to Garrison and Link (2000), generalist predators find prey more easily than specialised ones (such as benthophagous species) and therefore are more able to survive major disturbances. Unfortunately, when no data are available on the trophic structure of the local communities prior to current impacts, more definitive conclusions on this point are weakened (Ecoutin et al., 2010).

Sets of indicators have been established by several authors for the monitoring of changes in the environmental quality of estuaries. However, variation in these indicators is difficult to interpret and may not fully account for the complexity of the ecosystem. In particular, some indicators are unable to identify short-term responses, demanding a much longer study period in order to demonstrate fluctuations effectively (Ecoutin et al., 2010). These variables include habitat use and the CPUE, which were evaluated in the present study.

In the case of relative abundance (CPUE), the highest values were recorded in the most impacted area. This may have been related to the relative abundance of P. squamosissimus and L. dorsalis, which are the dominant species in this area. Both species are relatively common in the Amazon basin and are considered to be relatively tolerant of contamination, given that studies in other parts of the estuary have found that their abundance is not affected by anthropogenic disturbances (Viana et al., 2010).

The adoption of exclusively physical-chemical criteria for the evaluation of water quality may not necessarily provide an accurate depiction of the conditions faced by local communities (Vieira and Shibatta, 2007). While these criteria may provide a reliable assessment of water quality per se, they may not necessarily offer an effective measure of the ecological integrity of the area (Goulart and Callisto, 2003), given that they merely provide a "snapshot" of environmental conditions at a given point in time. By contrast, biological indicators offer an integrated overview of the accumulated effects of pollution on the biota. In this study, ecological indicators, especially ecological descriptors, trophic categories and size, were especially effective for the demonstration of the critical alterations of the fish community of Zone 1, indicating that the biota is an integrating element that responds systematically to alterations in the environment, despite the restrictions about the use of analysis on the community structure in estuarine environments (Elliott and Quintino, 2007). These impacts were also evident when more sophisticated methods were applied as a selection of fish based multimetric indices of ecosystem integrity (Viana et al., 2012).The cargo terminal and industrial district are a case in point here and in addition to the intrinsic potential risks represented by its industries, a number of accidents have been reported since the installation of its ore-processing plants (Lima et al., 2011). Additionally, Berredo et al. (2001) showed evidence of contamination by heavy metals in the region.

It is clear that the presence of the cargo terminal and adjacent industries has an effect on the biological integrity of areas used by many local fish species for their reproduction and development. Many species visit the estuary of the Rio Para during the migrations inherent to their life cycle. The juveniles tend to prefer estuaries due to the existence of favourable conditions for feeding, growth and refuge, as well their connectivity with other habitats (Kennish, 1985; Blaber, 2000). Studies have shown that the inner portion of the Amazon estuary, including Marajo and Guajara bays and the Para estuary are used by ichthyofauna more for growth and development, rather than reproduction (Viana et al., 2010). In addition to the biological aspects of these phenomena, the local population is economically dependent on local fishery resources (Paz et al., 2011).

Considering the ecological and economic importance of the estuary of the Rio Para, the mitigation of the impacts caused by the local ore-processing installations and the cargo terminal and the systematic monitoring of the local aquatic environments should be given the highest priority. Such measures will be important to guarantee the productivity of these environments for future generations, given the importance of these resources as a source of income and subsistence for local populations. Additionally, despite the lack of historical data for the study area, the methodological procedures adopted in the present study were adequate for the detection of the alterations to the environment.

http://dx.doi.org/10.1590/1519-6984.16012

Received July 31, 2012--Accepted March 22, 2013--Distributed May 31, 2014 (With 4 figures)

Acknowledgements--The authors are grataeful to Dr. Thierry Fredou for comments on earlier drafts of the manuscript and Artur Miranda for helping with the map. This study was partially financed by CNPq through a student grant to the first author and through a research grant to the second author, and by the International Institute of Education of Brazil and Moore Foundation, with financial assistance during the project development.

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Viana, AP. * and Lucena Fredou, F.

Universidade Federal do Para--UFPA, Av. Bernado Sayao, 1, Guama, CEP 66075-110, Belem, PA, Brazil

* e-mail: vianaap@yahoo.com.br

Table 1. Species captured in the estuary of Para River (Amazon estuary).
Total length (TL) minimum and maximum; constancy of species (Cs):
C - Constant; A - accessory; O - occasional; Mc - Main channel;
Tc - Tidal Channel; 1 - Zone 1; 2 - Zone 2; 3 - Zone 3.

Family               Species

CHARACIFORMES

Anostomidae          Leporinus fasciatus (Bloch, 1794)

                     Leporinus friderici (Bloch, 1794)

Characidae           Astyanax fasciatus (Cuvier, 1819)

                     Species 1

                     Species 2

                     Pristobrycon calmoni (Steindachner, 1908)

                     Triportheus elongatus (Gunther, 1864)

Ctenoluciidae        Boulengerella cuvieri (Spix & Agassiz, 1829)

Curimatidae          Curimata inornata Vari, 1989

Cynodontidae         Raphiodon vulpinus Agassiz, 1829

Erythrinidae         Hoplias malabaricus (Bloch, 1794)

Hemiodontidae        Hemiodus unimaculatus (Bloch, 1794)

CLUPEIFORMES

Engraulididae        Anchoa spinifer (Valenciennes, 1848)

                     Anchovia surinamensis (Bleeker, 1865)

                     Lycengraulis batesii (Gunther, 1868)

                     Pterengraulis atherinoides (Linnaeus, 1766)

Pristigasteridae     Pellona castelnaeana Valenciennes, 1847

                     Pellonaflavipinnis (Valenciennes, 1837)

CYPRINODONTIFORMES

Anablepidae          Anableps anableps (Linnaeus, 1758)

GYMNOTIFORMES

Apteronotidae        Apteronotus albifrons (Linnaeus, 1766)

                     Sternarchella terminalis (Eigenmann & Allen, 1942)

                     Sternarchorhamphus muelleri (Steindachner, 1881)

Rhamphichthyidae     Rhamphichthys marmoratus Castelnau, 1855

                     Rhamphichthys rostratus (Linnaeus, 1766)

Sternopygidae        Rhabdolichops caviceps (Fernandez-Yepez, 1968)

                     Sternopygus macrurus (Bloch & Schneider, 1801)

MUGILIFORMES

Mugilidae            Mugil incilis Hancock, 1830

PERCIFORMES

Cichlidae            Cichla orinocensis Humboldt, 1821

                     Cichla pinima Kullander & Ferreira, 2006

                     Cichla pleiozona Kullander & Ferreira, 2006

                     Cichla temensis Humboldt, 1821

                     Crenicichla johanna Heckel, 1840

                     Crenicichla lugubri Heckel, 1840

                     Crenicichla sp.

                     Geophagus proximus (Castelnau, 1855)

                     Geophagus sp. 1

                     Geophagus sp. 2

                     Geophagus surinamensis (Bloch, 1791)

                     Crenicichla semifasciata (Heckel, 1840)

Sciaenidae           Pachypops fourcroi (Lacepede, 1802)

                     Plagioscion auratus (Castelnau, 1855)

                     Plagioscion squamosissimus (Heckel, 1840)

                     Plagioscion surinamensis (Bleeker, 1873)

PLEURONICTIFORMES

Achiridae            Achirus achirus (Linnaeus,1758)

                     Apionichthys dumerili (Kaup,1858)

Paralichthyidae      Citharichthys spilopterus Gunther, 1862

                     Syacium papillosum (Linnaeus, 1758)

RAJIFORMES

Potamotrygonidae     Potamotrygon motoro (Muller & Henle, 1841)

                     Potamotrygon orbignyi (Castelnau, 1855)

                     Potamotrygon sp.

SILURIFORMES

Ariidae              Sciades couma (Valenciennes, 1840)

                     Sciades herzbergii (Bloch, 1794)

Aspredinidae         Aspredinichthys filamentosus (Valenciennes, 1840)

                     Aspredo aspredo (Linnaeus, 1758)

Auchenipteridae      Ageneiosus aff. ucayalensis Castelnau, 1855

                     Ageneiosus inermis (Linnaeus, 1766)

                     Pseudauchenipterus nodosus (Bloch, 1794)

                     Trachelyopterus galeatus (Linnaeus, 1766)

Doradidae            Lithodoras dorsalis (Valenciennes 1840)

                     Lithodoras sp.

Heptapteridae        Pimelodella gr altipinnis (Steindachner, 1864)

                     Rhamdia quelen (Quoy & Gaimard, 1824)

Loricariidae         Acanthicus hystrix Agassiz, 1829

                     Ancistrus sp. 1

                     Ancistrus sp. 2

                     Hypostomus plecostomus (Linnaeus, 1758)

                     Hypostomus sp.

                     Loricaria cf. cataphracta Linnaeus, 1758

                     Peckoltia sp. 1

                     Peckoltia sp. 2

Pimelodidae          Brachyplatystoma rousseauxi (Castelnau, 1855)

                     Brachyplatystoma vaillanti (Valenciennes, 1840)

                     Hypophthalmus marginatus Valencie nnes, 1840

                     Pimelodus blochii Valenciennes, 1840

                     Platystomatichthys sturio (Kner, 1858)

                     Propimelodus aff. eigenmanni (Van der

                     Stigchel, 1946)

TETRAODONTIFORMES

Tetraodontidae       Colomesus psittacus (Bloch & Schneider, 1801)

Family               TL (cm)     Cs
                     min-max

CHARACIFORMES

Anostomidae          20.5-32     A(3 Mc)

                     23-26       A(3 Tc)

Characidae           8-12        C(2, 3 Tc)

                     -           O(2 Tc)

                     12.8        A(3 Tc)

                     7           O(3 Mc)

                     19-24.5     A(3 Mc)

Ctenoluciidae        31.5-37.5   A(2 Tc)

Curimatidae          11-16.2     C(3 Tc) A(3 Mc)

Cynodontidae         34          A(3 Tc)

Erythrinidae         23-25.5     A(1, 3 Tc)

Hemiodontidae        19.5-23     O(2 Tc)

CLUPEIFORMES

Engraulididae        7.8-16.8    A(1, 2 Mc)

                     7-11        A(3 Mc; 3 Tc) O(1 Mc)

                     19.4-22.5   A(3 Tc). O(3, 2 Mc)

                     17.5-21.2   A(2, 3 Tc). O(3 Mc)

Pristigasteridae     20-23       O(1, 2 Mc)

                     17.3-52.5   C(1 Mc) O(2 Tc)

CYPRINODONTIFORMES

Anablepidae          15.3-23     C(2 Tc); A(3 Tc)

GYMNOTIFORMES

Apteronotidae        25.5-52     A(3 Tc)

                     30-36       A(3 Tc)

                     26          A(3 Tc)

Rhamphichthyidae     36.5-78     C(3 Tc) A(1 Tc) O(3 Mc; 2 Tc)

                     50-101      C(3 Tc) A(1,2 Tc) O(3 Mc)

Sternopygidae        33-41.5     A(2 Tc)

                     30.2-58     C(1, 3 Tc) A(2 Tc) O(1, 3 Mc)

MUGILIFORMES

Mugilidae            12.2-55     C(2 Tc); O(3 Mc)

PERCIFORMES

Cichlidae            58-69.5     A(2 Tc)

                     25.5-39     A(2 Tc)

                     15.3-63     A(2 Tc)

                     18.5-60     C(2 Cr)

                     19.2-24.6   A(1, 3 Tc)

                     23.5-27     A(1 Tc)

                     16-18       A(2 Mc)

                     8.5-23.5    C(1, 2, 3 Tc) A(3 Mc)

                     16.5        A(1 Tc)

                     15          A(1 Tc)

                     10          O(2 Tc)

                     18.5-32.5   A(3 Tc)

Sciaenidae           10.5-23.5   C(1,2, 3 Tc) O(3 Mc)

                     15.5-31     A(2 Mc; 3 Tc) O(2 Tc)

                     9.5-35.5    C(1,2 Mc; 1, 2, 3 Tc) A(3 Mc)

                     13-27       C(3 Tc) A(1, 2 Tc; 2, 3 Mc)

PLEURONICTIFORMES

Achiridae            7-13        C(2 Tc)

                     12-14.2     O(2 Tc)

Paralichthyidae      -           O(2 Tc)

                     9.5-11.5    A(2 Tc)

RAJIFORMES

Potamotrygonidae     26-29       C(1 Tc) A(2 Tc)

                     24-38       C(2 Tc)

                     21.6-35.8   A(2 Tc) O(2 Tc)

SILURIFORMES

Ariidae              26-44       A(3 Tc) O(3 Mc)

                     19-23       O(2 Mc)

Aspredinidae         25.5        A(3 Tc)

                     19-20       A(3 Tc) O(3 Mc)

Auchenipteridae      9.7-27      C(3 Tc) A(2 Tc) O(2, 3 Mc)

                     35          A(3 Tc)

                     6.5-7.5     A(3 Tc) O(2 Tc)

                     12-21.5     C(3 Tc) A(1 Tc; 3 Mc)

Doradidae            10.17-21    C(1,2 Mc; 1, 3 Tc) O(3 Mc)

                     21-150      A(3 Tc)

Heptapteridae        13-22       C(3 Tc) A(2 Tc)

                     20-21       A(3 Tc)

Loricariidae         43          O(2 Mc)

                     15          A(3 Tc)

                     15-19       A(3 Tc)

                     14-31       A(3 Mc, 3 Tc) O(2 Tc)

                     20          O(2 Mc)

                     17.5-29     A(3 Mc; 2, 3 Tc)

                     8.2-15      A(2, 3 Mc)

                     33-45       O(2, 3 Mc)

Pimelodidae          25.5-35     O(1 Mc)

                     22-37       C(3 Tc)

                     16.8-40     C(1, 3 Tc) O(1, 2 Mc)

                     16.8-22     C(3 Tc) O(2, 3 Mc)

                     25          A(3 Tc)

                     22.5        A(3 Tc)

TETRAODONTIFORMES

Tetraodontidae       10.5        O(2 Tc)
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Title Annotation:Original Article
Author:Viana, A.P.; Lucena Fredou, F.
Publication:Brazilian Journal of Biology
Date:May 1, 2014
Words:5954
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