Fish stomach contents in benthic macroinvertebrate assemblage assessments/Conteudo estomacal de peixes em avaliacoes de comunidades de macroinvertebrados bentonicos.
Human occupation of river basins has deteriorated water quality, limited the quantity and availability of freshwater resources for multiple human uses, and diminished opportunities for wildlife conservation. Therefore, the conflict between population and economic growth and aquatic ecosystem conservation has become a substantial challenge (Dudgeon et al., 2006; Limburg et al., 2011). Increasingly, biological assemblage assessments have been used as tools to evaluate anthropogenic impacts on aquatic ecosystems (Barbour et al., 1998; Li et al., 2010; Tupinambas et al., 2014). Benthic macroinvertebrate communities have frequently been used in these assessments because of their sensitivity to environmental changes and their ease of sampling (HeUawell, 1986; Rosenberg and Resh, 1993; Doledec and Statzner, 2008). Benthic macroinvertebrates are associated with organic and inorganic substrates (Fleituch, 2003) and are important elements in the bottom-up trophic processes of aquatic ecosystems (Northcote, 1988), converting algae and organic debris into animal tissue (Graca, 2001) available for fish consumption. Thus, benthic macroinvertebrates reflect the physical-chemical-biological quality of freshwaters and are important in aquatic food-webs.
Benthic macroinvertebrates are sampled through use of multiple gears (e.g., Surber sampler, dredges, kick-nets, rock baskets) depending of the type of ecosystem (streams, rivers, lakes), substrates (organic and inorganic), and study objectives (Buss and Borges, 2008; Chadd, 2010). In large rivers, sampling is mostly limited to margins for logistical and financial reasons (Bartsch et al., 1998; Reece and Richardson, 2000; Hughes et al., 2012); therefore, many habitats remain un-sampled and the taxonomic richness of river benthos is substantially underestimated in surveys (Hughes et al., 2012).
To complement traditional macroinvertebrate sampling, especially when concurrent with fish sampling, some authors have suggested using stomach content analysis of benthophagous fishes (Callisto et al., 2002; Russo et al., 2002; Galina and Hahn, 2004). The rationale for using fish gut contents as a tool to assess benthic macroinvertebrate communities is based on two factors. 1) Morphological and physiological adaptations aid fish in finding and consuming macroinvertebrates from many substrates and micro-habitats that are difficult to sample with conventional sediment sampling gear in large, deep, fast rivers (Gerking, 1994; Fugi et al., 2001). 2) Most environmental studies in Brazil focus only on the fish fauna, especially those involved with environmental licensing. Therefore, stomach contents analysis of benthophagous fishes can easily yield ancillary information about benthic macroinvertebrate communities.
We evaluated the efficacy of using stomach content analysis of three commonly occurring benthophagous fishes belonging to three different orders and foraging strategies (Eigenmannia virescens (Valenciennes, 1836) --Gymnotiformes, electrical; Iheringichthys labrosus (Lutken, 1874)--Siluriformes, olfactory; and Leporinus amblyrhynchus Garavello and Britski, 1987--Characiformes, visual) as a proxy for providing information about benthic macroinvertebrate communities. We tested three hypotheses: 1) benthic macroinvertebrate taxa in fish stomachs and sediments are similar; 2) the proportional abundances of benthic macroinvertebrate taxa in fish stomachs and sediments are similar, especially when assessed by habitat type; and 3) samples from benthophagous fish can add taxa to inventories quicker than additional sediment samples.
2. Material and Methods
2.1. Study area
The Rio Grande, located in the state of Minas Gerais, southeast Brazil (Figure 1), is a highly regulated river (12 hydroelectric power plants and dams installed along the river's length) with a length of 1,300 km and a catchment area of 143,000 km2 (Santos, 2010). The sampling stations were located in a river reach located about 5 km downstream of the Itutinga Reservoir in the upper area of the Rio Grande (Figure 1).
The region's climate is humid subtropical (Koppen-Geiger classification: Cwb) with dry winters (April-September, mean 107 [+ or -] 12 mm precipitation [month.sup.-1]) and wet summers (October-March, mean 1410 [+ or -] 156 mm precipitation [month.sup.-1]) (Van Den Berg and Oliveira-Filho, 2000). The vegetation is cerrado (tropical savanna) (Van Den Berg and Oliveira-Filho, 2000).
2.2. Ecological sampling
We sampled benthic macroinvertebrates and fish for six consecutive days in each of the three different periods of the hydrological regime in 2010: January (high water level), March (falling water) and July (low water level). We sampled biota from three different habitat types (backwater, beach, riffle) (Table 1). Because of the relative low number of fish stomachs collected from each sampling, we did not consider seasonal variations.
2.2.1. Fish sampling and stomach contents analysis
We collected fish using two gill nets (each net 10 m X 1.6 m, 2.4 to 16 cm between opposing knots) placed in the three different habitat types (Table 1) in each of the three seasons, exposed for 24 hours and inspected at 06:00 and 18:00, during six consecutive days (total of 36 samples). All captured specimens and their stomachs were fixed in a 10% formalin solution in the field. In the laboratory, we measured each fish's standard length and weight, tagged each specimen, and placed it in 70% alcohol. Because of their greater abundances and foraging capacities, three benthophagous fish species were selected for stomach contents analysis. We evaluate 16 Eigenmannia virescens with sizes ranging from 12 to 19 cm standard length, 15 Iheringichthys labrosus ranging from 5 to 14 cm standard length, and 13 Leporinus amblyrhynchus ranging from 14 to 20 cm standard length. The stomachs were dissected and the food items found were identified (Gandini et al., 2012).
2.2.2. Benthic macroinvertebrates
We collected benthic macroinvertebrates from sediments through use of a Petersen dredge (0.0375 [m.sup.2]). During each of the six consecutive days, four replicates were collected from each of three habitat types in each of three periods giving a total of 216 benthic macroinvertebrate samples. The samples were washed through 1.0, 0.5 and 0.25 mm sieves and preserved in 70% alcohol. Individuals from both stomachs and sediments were identified to family level, whenever possible, by using taxonomic keys (Perez, 1988; Merritt and Cummins, 1998; Mugnai et al., 2010). Voucher specimens were deposited in the reference collection of the Instituto de Ciencias Biologicas of the Universidade Federal de Minas Gerais.
2.3. Data analyses
To run all the following analyses, the data from sediment and stomachs were standardized. For each taxon, the number of individuals within each sample was divided by the total number of individuals (sediment samples) and the volume within each stomach was divided by the total volume (fish stomachs).
To test hypothesis 1 we used an analysis of similarity (ANOSIM, [alpha] = 0.05) with log (x+1) transformed data from the Bray-Curtis distances to assess the significance of differences between benthic macroinvertebrate composition of samples from fish stomachs and sediments. ANOSIM analyses were performed with PRIMER 6.0 (Anderson et al., 2008). ANOSIM values of R > 0.75 indicate distinct groups, 0.50 < R < 0.75 indicates separate but moderately overlapping groups, 0.25 < R < 0.50 indicates separate but strongly overlapping groups, and R < 0.25 represents groups that cannot be distinguished (Maroneze et al., 2011a). A randomization process using Monte Carlo testing with 9,999 interactions was conducted to validate the R values observed. A value of p < 0.05 indicates that the R value observed was not randomly obtained.
To test our second hypothesis, we first used Spearman's correlation analyses to assess the significant correlations between macroinvertebrate taxa from sediment samples against those from fish stomachs. For those that were significant, we then regressed the log (x+1) transformed relative abundances of benthic macroinvertebrate taxa from the sediment from those in fish stomachs to illustrate some alimentary preferences. We used STATISTICA 7.0 software (StatSoft, 2007) in both analyses.
To test our third hypothesis, we calculated and plotted the cumulative observed richness for benthic macroinvertebrate families from stomach contents and sediment samples through use of EstimateS 8.2.0 (Colwell, 2009). We used STATISTICA 7.0 software (StatSoft, 2007) for graphs. To test for statistically significant differences in macroinvertebrate assemblage composition between stomach and sediment samples we used a test of homogeneity of dispersions (PERMDISP) with PRIMER 6.0 software (Anderson et al., 2008). PERMDISP (permutational analysis of multivariate dispersions) calculates the distances between observations and their centroids for a group, and then compares the averages of these distances among groups through use of ANOVA. We conducted pairwise tests to assess the significance of differences. We assumed that the greater the dispersion or variability, the more effective the method is at sampling a wide range of taxa.
We collected 33 macroinvertebrates taxa from the 216 sediment samples and 23 taxa from the 44 fish stomach samples (Table 2). We collected 20 taxa from E. virescens, 6 taxa from I. labrosus and 10 taxa from L. amblyrhinchus. Chironomids were the dominant group in both sediment (>80%) and fish stomach (> 63%) samples. Thirteen taxa were collected from sediments but not fish stomachs, and one taxon (Philopotamidae) found in the stomachs of L. amblyrhinchus was not present in the sediment samples (Table 2).
The Global R values obtained by ANOSIM indicated that benthic macroinvertebrate taxa from fish stomachs were significantly separated from those from sediment samples (Table 3). However, there was strong overlapping between fish and sediment samples from backwater and beach habitats, and fish and sediment samples from riffle habitats were indistinguishable.
We observed significant and positive correlations in macroinvertebrate abundances only between sediment samples and E. virescens, especially in riffle habitats (Table 4). However, E. virescens consumed several taxa at proportionately greater rates than occurred in the sediments (Figure 2).
Comparing taxa accumulation curves for fish stomach and sediment samples we observed that E. virescens had a relatively high potential to collect benthic macroinvertebrate taxa (Figure 3). The PERMIDISP analysis revealed significant greater differences in benthic macroinvertebrate community dispersions from fish stomach samples than from sediment samples (F = 18.513; p = 0.001; Table 5). The dispersion of benthic macroinvertebrate taxa from E. virescens and I. labrosus were significantly different from those from backwater and beach sediments, but not from riffle sediments. Leporinus amblyrhynchus had the greatest mean dispersion of all (Table 5).
Dominance of chironomids is common in stomachs of E. virescens (Castro and Cassati, 1997; Tupinambas et al., 2007; Brandao-Goncalves et al., 2009), I. labrosus (Fagundes et al., 2008; Maroneze et al., 2011b; Masdeu et al., 2011), and L. amblyrhynchus (Callisto et al., 2002; Mendonca et al., 2004; Maroneze et al., 2011b). The three fish species studied have high foraging capacities because of their morphological and physiological adaptations (Gerking, 1994; Fugi et al., 2001). Nonetheless, the predominance of chironomids at the site and aquatic ecosystems in general (Maroneze et al., 2011a) seems to drive the food of the studied fishes. In addition, chironomid larvae have a high nutrient content and high digestibility (Armitage, 1995). However, some alimentary preferences have been observed in fish species (e.g., Strauss, 1979), especially in E. virescens.
Benthic macroinvertebrate community composition in sediment samples and fish stomachs exhibited low similarity. Therefore, we reject our first hypothesis; although, the benthic macroinvertebrates in fish stomachs were more similar to those in riffle sediments than to those in other habitats. This dissimilarity between gut contents and sediments indicates that fish feed opportunistically, select certain prey over others, or both (Hyslop, 1980; Kasumyan and Doving, 2003). However, the observed differences may arise from insufficient sample sizes, differential prey availability, and varied prey digestion rates (Strauss, 1979).
Our second hypothesis was that there would be positive and significant correlations in the abundances of benthic macroinvertebrate taxa from fish stomachs and sediment samples. We accepted this hypothesis only for E. virescens and in all three habitat types. This suggests that E. virescens exploits all three habitat types, despite its tendency for territorial behavior and occupancy of pools with submerged vegetation and snags (Brandao-Goncalves et al., 2009).
The taxa accumulation curves show that E. virescens had a more rapidly ascending curve than the sediment samples. In addition, fish stomach samples had higher dispersion values than sediment samples, likely because of the high foraging capacities of the fish. L. amblyrhynchus, especially, showed significantly higher dispersion values than the other fish species and consequently added one taxa absent from the sediment and from the other fish species studied (Philopotamidae). Therefore, we conclude that stomach content analysis of at least one benthophagous fish species can be a useful proxy to assess benthic macroinvertebrates communities, and a means to add new taxa to conventional sediment samples. Consequently, we accept our third hypothesis only for E. virescens.
Because of limitations in environmental laws, it is common in Brazil to use only fish assemblages for evaluating human impacts on catchments and rivers during environmental impact evaluations and licensing processes. In those cases, stomach content analyses can be useful to amplify the assessment of human impacts, and to add additional bioindicators. To do so, we recommend focusing on mobile benthophagous fishes.
We thank colleagues that contributed to this paper from the Laboratory of Ecology of Benthos (UFMG), Laboratory of Ichthyology (UFLA) and CEMIG (P&D ANEEL). We also thank to Education Secretariat of Minas Gerais (SEE-MG) for the permission to THT attending the doctoral course at UFMG, to CNPq for PhD scholarship in Brazil, to CAPES for Sandwich PhD scholarship and to CITAB- UTAD to receive the first author during 10 months. MC received a research grant and a research fellowship from the Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq no. 302960/2011-2 and 475830/2008-3) and from the Fundacao de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG no. PPM-00077/13).
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Tupinambas, TH. (a) *, Pompeu, PS. (b), Gandini, CV (b), Hughes, RM. (c) and Callisto, M. (a)
(a) Departamento de Biologia Geral, Universidade Federal de Minas Gerais--UFMG, Av. Antonio Carlos, 6627, CP 486, CEP 31270-910, Belo Horizonte, MG, Brazil
(b) Departamento de Biologia, Universidade Federal de Lavras--UFLA, Campus Universitario, CP 3037, CEP 37.200-000, Lavras, MG, Brazil
(c) Amnis Opes Institute and Department of Fisheries and Wildlife, Oregon State University--OSU, Corvallis, Oregon, 97333, USA
* e-mail: email@example.com
Received: June 11, 2013--Accepted: October 7, 2013--Distributed: March 31, 2015 (With 3 figures)
Table 1. Environmental characteristics of the Rio Grande sampling sites. General characteristics backwater beach riffle Average depth (m) 1 1 1 Average flow ([m.sup.3] [s.sup.-1]) 0 0 0.48 Predominant substrate particle size <0.50 mm 0.50-1.0mm >1.0mm Aquatic macrophytes absent absent present Average organic matter (%) 1.62 0.52 0.7 Table 2. Proportional abundances (mean and standard deviation) and total richness of benthic macroinvertebrate assemblage samples from sediment and fish stomachs. Benthophagous fish stomachs Taxa E. virescens (N=16) I. labrosus (N=15) Baetidae 1.5 [+ or -] 3.65 0 Bivalvia 0.1 [+ or -] 0.39 8.99 [+ or -] 15.36 Ceratopogonidae 3.22 [+ or -] 8.17 0 Chironomidae 66.47 [+ or -] 20.28 69.83 [+ or -] 26.93 Elmidae 3.2 [+ or -] 5.06 0 Empididae 0.06 [+ or -] 0.25 0 Gelastocoridae 0 0 Gomphidae 0 0 Gyrinidae 0 0 Helichopsychidae 1.01 [+ or -] 4.03 0 Hidracarina 1.98 [+ or -] 3.85 1.93 [+ or -] 5.25 Hirudinea 0.35 [+ or -] 1.39 0 Hydrophilidae 0 0 Hydropsychidae 4.92 [+ or -] 12.83 9.24 [+ or -] 22.34 Hydroptilidae 0 0 Leptoceridae 0.2 [+ or -] 0.81 0 Leptophlebiidae 0.49 [+ or -] 1.78 0 Leptoyphidae 1.81 [+ or -] 4.6 0 Libellulidae 0 0 Muscidae 0 0 Naucoridae 0 0 Nematoda 4.31 [+ or -] 16.63 3.71 [+ or -] 7.68 Oligochaeta 0.77 [+ or -] 2 0 Ostracoda 0.13 [+ or -] 0.52 6.29 [+ or -] 11.77 Philopotamidae 0 0 Polycentropodidae 0 0 Polymitarcyidae 0.26 [+ or -] 1.04 0 Psephenidae 0 0 Pyralidae 0.06 [+ or -] 0.25 0 Simuliidae 7.76 [+ or -] 16.71 0 Staphilinidae 0 0 Tipulidae 1.4 [+ or -] 4.6 0 Vellidae 0 0 Total richness 20 6 Benthophagous Sediment samples fish stomachs Taxa L. amblyrhynchus Petersen Dredge (N=13) (N=216) Baetidae 0 0.94 [+ or -] 1.16 Bivalvia 0 0.04 [+ or -] 0.14 Ceratopogonidae 0 0.45 [+ or -] 0.51 Chironomidae 54.96 [+ or -] 43.01 83.14 [+ or -] 20.44 Elmidae 0 0.49 [+ or -] 0.56 Empididae 0 0.09 [+ or -] 0.21 Gelastocoridae 0 0.02 [+ or -] 0.10 Gomphidae 0 0.11 [+ or -] 0.18 Gyrinidae 0 0.01 [+ or -] 0.04 Helichopsychidae 2.46 [+ or -] 8.88 0.01 [+ or -] 0.06 Hidracarina 1.62 [+ or -] 3.23 0.04 [+ or -] 0.09 Hirudinea 0 0.05 [+ or -] 0.14 Hydrophilidae 0 0.15 [+ or -] 0.24 Hydropsychidae 16.76 [+ or -] 29.58 5.17 [+ or -] 11.77 Hydroptilidae 11.24 [+ or -] 29.56 1.25 [+ or -] 3.08 Leptoceridae 3.4 [+ or -] 9.23 0.15 [+ or -] 0.32 Leptophlebiidae 1.58 [+ or -] 3.56 0.15 [+ or -] 0.36 Leptoyphidae 7.48 [+ or -] 10.31 3.05 [+ or -] 2.5 Libellulidae 0 0.1 [+ or -] 0.15 Muscidae 0 0.02 [+ or -] 0.08 Naucoridae 0 0.03 [+ or -] 0.08 Nematoda 0 0.05 [+ or -] 0.08 Oligochaeta 0 1.75 [+ or -] 0.97 Ostracoda 0 0.01 [+ or -] 0.03 Philopotamidae 0.25 [+ or -] 0.89 0 Polycentropodidae 0.25 [+ or -] 0.89 0.24 [+ or -] 0.46 Polymitarcyidae 0 0.05 [+ or -] 0.13 Psephenidae 0 0.02 [+ or -] 0.07 Pyralidae 0 0.9 [+ or -] 1.72 Simuliidae 0 1.2 [+ or -] 3.93 Staphilinidae 0 0.02 [+ or -] 0.07 Tipulidae 0 0.25 [+ or -] 0.32 Vellidae 0 0.03 [+ or -] 0.14 Total richness 10 35 Table 3. ANOSIM results comparing macroinvertebrate taxa collected from sediment versus fish stomachs. ANOSIM backwater R p E. virescens 0.498 0.001 * I. labrosus 0.349 0.002 * L. amblyrhynchus 0.380 0.001 * beach - E. virescens 0.464 0.001 * I. labrosus 0.300 0.004 * L. amblyrhynchus 0.328 0.004 * riffle - E. virescens 0.259 0.002 * I. labrosus 0.268 0.001 * L. amblyrhynchus 0.235 0.006 * * significant (P<0.05). Table 4. Spearman correlations comparing macroinvertebrate abundances in fish stomachs with those in sediment samples from different habitat types. Spearman's correlation backwater R t(n-2) p E. virescens 0.466 2.933 0.006 * I. labrosus 0.175 0.989 0.330 L. amblyrhynchus 0.327 1.929 0.063 beach E. virescens 0.432 2.667 0.012 * I. labrosus 0.102 0.573 0.571 L. amblyrhynchus 0.307 1.798 0.081 riffle E. virescens 0.576 3.921 0.000 * I. labrosus 0.190 1.080 0.288 L. amblyrhynchus 0.343 2.035 0.050 * * significant (P<0.05). Table 5. Average distance to the centroid and standard errors from PERMIDISP analysis, comparing the variability in benthic macroinvertebrate assemblages collected from fish stomachs and sediments. The superscript letters represent pairwise tests indicating significant differences among samples. PERMDISP analyses Tool Average and standard errors Eigenmannia virescens (N=16) 29.03 [+ or -] 3.07 (a) Iheringichthys labrosus (N=15) 29.17 [+ or -] 3.77 (a) Leporinus amblyrhynchus (N=13) 45.42 [+ or -] 5.18 (b) Backwater (N=72) 11.12 [+ or -] 1.39 (c) Beach (N=72) 13.81 [+ or -] 2.11 (c) Riffle (N=72) 27.38 [+ or -] 2.08 (a) (a, b, c) letters represent significant differences.
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|Title Annotation:||Original Article|
|Author:||Tupinambas, T.H.; Pompeu, P.S.; Gandini, C.V.; Hughes, R.M.; Callisto, M.|
|Publication:||Brazilian Journal of Biology|
|Date:||Jan 1, 2015|
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