Factors determining the structure of fish assemblages in Tarumã River, Jaru Biological Reserve, Machado River drainage, northern Brazil

Igor D. Costa^1,2 , Natalia N. Santos Nunes³ and Carlos E. C. Freitas⁴

PDF: EN    XML: EN  | Supplementary: S1  S2 | Cite this article

Abstract​

---

Introduction​

---

The Amazon basin is the largest ecosystem of the Neotropical region in the northern South America with an area of over 8 million km² (Sioli, 1984). The basin is distributed between the Brazilian and Guiana shield, from the pre-Andean areas as far as the Atlantic Ocean (Gibbs, 1967; Leite, Rogers, 2013). The flood pulse is the phenomenon that drives the fluvial dynamic of this ecosystem (Junk et al., 2011). It is characterized by a monomodal flood with an annual cycle of rising, high, receding and low water seasons, resulting in variation up to 10 m in the central portion of the Basin (Junk et al., 2011). Annually, the flooding could inundate more than 750,000 km² of the floodplain (Wittmann et al., 2017). Nevertheless, the lateral extension and duration of the flooding is dependent of the annual precipitation and local geomorphology (Junk et al., 2011). The annual flooding promotes lateral connectivity that influences life cycles of many organisms within floodplain aquatic habitats (Arrington et al., 2006; Neves dos Santos et al., 2008; Hurd et al., 2016). Lateral migrations performed by small (<15 cm as adults) and larger species (Fernandes, 1997) are primary causes of seasonal changes in the fish assemblages structure (Röpke et al., 2016).

The ichthyofauna of larger rivers and their adjacent floodplains of the Amazon basin has been studied for a long time (Freitas, Garcez, 2004; Junk et al., 2007; Röpke et al., 2016; Jézéquel et al., 2020; Duponchelle et al., 2021). Recently, as a result of environmental studies associated with large hydroelectric projects, the fish diversity of southeastern basins has been relatively well-studied. Specifically, studies that have been carried out, include those related to the trophic structure, composition and distribution of the fishes of the Madeira River (Araújo et al., 2009; Torrente-Vilara et al., 2011), fish taxonomic inventories and studies of fish communities living in rapids of the Middle and Lower Xingu River basin (Barbosa et al., 2015; Zuluaga-Gómez et al., 2016) and studies about the influence of protected areas on fish assemblages and fisheries of the Tapajós River (Keppeler et al., 2017). Nevertheless, the fish fauna of the rivers that drain the western portion of the Brazilian Shield have received little attention. In general, depth, water clarity, water temperature, dissolved oxygen and total suspended matter are among the environmental variables with the greatest influence on fish assemblage structures and species distribution (Peláez, Pavanelli, 2019). In addition, the presence of rapids and waterfalls increases the level of endemism (Oberdorff et al., 2019). Therefore, factors structuring the fish assemblages in the western portion of the Brazilian could be different than those observed in larger rivers and adjacent floodplains.

Several studies have shown that protecting forests is important for conserving the aquatic environment and fish fauna (Bruner et al., 2001; Azevedo-Santos et al., 2018; Frederico et al., 2018). However, although 43% of the Brazilian Amazon is classified as protected areas, most of the protected areas extension was established to protect terrestrial rather than aquatic components (Veríssimo et al., 2011). Among the few that include aquatic systems, the Jaru Biological Reserve (Rebio Jaru) was established on July 11^th, 1979, under Federal Decree-law N^o. 83,716, and is managed by the Instituto Chico Mendes Conservação da Biodiversidade /Ministério do Meio Ambiente – ICMBio/MMA (Justina, 2009). This protected unit was created to reduce the changes in ecosystems and habitat degradation, which have been growing in Rondônia state (ICMBio, 2010). The Rebio Jaru is located in the area between the Madeira and Tapajós rivers and it is considered one the most important area of endemism of the southern Amazon (Haffer, 1997; ICMBio, 2010).

This study evaluated the influence of environmental variables on the structure of fish assemblages in the Tarumã River, a pristine river in the southwestern Amazon that is partially located inside the Rebio Jaru, while also taking into account the changes between high and low water seasons. The contribution of species in each season to the fish assemblage, as well as the description trophic categorization based on the literature, in high and low water seasons were investigated. Our hypothesis is that the fish assemblages respond closely to physicochemical variables that vary between seasons of the hydrological cycle (high and low water seasons). Our results elucidated the influence of environmental variables on the fish diversity for a little studied a conservation area of the Amazon basin.

Material and methods

---

Sampling sites. The Jaru Biological Reserve (Rebio Jaru) has a total area of 47,733 km²(Brasil, 2010), with a high level of conservation and pristine forests. The protected area this localized in an area which has a humid, tropical climate with temperatures varying between 23 °C and 26 °C. The average annual rainfall ranges from 1,700 to 2,400 mm and the dry season occurs between May and October (Justina, 2009). The Rebio Jaru’s hydrographic network is part of the Machado River Basin and is located in eastern Rondônia State, northern Brazil. The Tarumã River, the main sub-basin of the Rebio Jaru, is almost entirely (99%) within the Rebio Jaru and thus extremely well preserved (Fig. 1). The Tarumã River has many rapids and flows across the granitic formation of the Serra da Providência and Jamari complex (Justina, 2009).

Sampling. We collected fish in the main channel of the Tarumã River in March (high water season) and September (low water seasons) in 2015 five sites (R1 – 09°27’19”S 61°40’43”W; R2 – 09°32’15”S 61°40’13”W; R3 – 09°42’46”S 61°39’42”W; R4 – 09°46’23”S 61°38’45”W; R5 – 09°47’04”S 61°40’19”W) (Fig. 1), totaling 10 samples. The average distance between the sites was 48 km (distance_Min = 10 km and distance_Max = 100 km). Samplings were performed in the river channel using eight gillnets of standard size of 2 m in height and 20 m in length, and mesh sizes varied from 30 to 100 mm between opposite knots. A single sampling was performed at each site in high and low water season. At each sampling site, the fishing nets were set during the morning, from 8:00 am to 12:00 pm, and at night, from 8:00 pm to 5:00 am. For the same period, we used a trotline with four 5/0 hooks with ends tied either to the vegetation on the riverbank or to mooring spikes. We used pieces of piranha, Serrasalmus rhombeus (Linnaeus, 1766), as bait on the trotline hooks.

FIGURE 1 | Map of the study area showing the collection stations in the drainage systems in the Jaru Biological Reserve (shaded area), Rondônia, Brazil. Circles represent collection points in the river channels of the Tarumã River.

Environmental variables were measured between 8:00 am and 9:00 am at the center of the river channel. We recorded four physical-chemical variables immediately before the fish samplings: dissolved oxygen (mg/l), electrical conductivity (mS/cm²), temperature (°C) and pH with an YSI-85 data logger. Four physical variables were also measured: depth (m) with the aid of a measuring tape with a weight; transparency (cm) with a Secchi disk; width (m) of the river using a GPS device and water velocity (Wv) with a flow meter (General Oceanics model 2030 R mechanical) that has a six digit odometer style counter and can indicate a minimum velocity of 10 cm/s. We calculated the average of four measurements of depth, water transparency, width and water velocity to standardize the measurement of environmental variables.

The specimens captured with the nets and trotline were sacrificed in a solution of clove oil (Eugenol, 2 drops per liter; cf. AVMA, 2001) and subsequently fixed in a 10% formalin solution and preserved in 70% ethanol. For species identifications, we consulted the most currently accepted taxonomic literature and identification keys (Queiroz et al., 2013). The classifications followed Nelson et al. (2016). Specimens were deposited in the Fish Collection of the Universidade Federal do Mato Grosso, Cuiabá (CPUFMT), Museu de Zoologia da Universidade de São Paulo, São Paulo (MZUSP), Ichthyology collection at the Universidade Federal de Rondônia (UFRO-I), and Laboratório de Ictiologia de Ribeirão Preto da Universidade de São Paulo, Ribeirão Preto (LIRP).

Aiming to describe the trophic categories of species in each period of the hydrological cycle, the trophic categorization of the sampled species was described through the use of the literature (evisceration and analysis of gut contents were not performed). Species were classified and described as detritivores, herbivores (more than 60% of the diet consists of Phanerogam plant structures); omnivores (when no feature of animal or vegetable origin alone reaches more than 60% of the diet), insectivores (over 60% of the diet consists of aquatic and terrestrial insects); invertivores (more than 60% of the diet is generally comprised of invertebrates, including insects, but with no preference for the latter), carnivores (over 60% of the diet comprises various types of animal resources, such as vertebrates and invertebrates), piscivorous (more than 60% of the diet is composed by fish, fish larvae or fins and scales) (Röpke, 2008), iliophagous (ingest silt or sand substrate looking for food of animal, plant or detritus origins) planktivores (predominantly feed on plankton) (Zavala-Camin, 1996).

Statistical analyses. The water physical-chemical variables, used to characterize each site in Tarumã River, were summarized in a matrix, which was the basis for a principal component analysis(PCA). The PCA was performed to ordinate the sites in high water and low water seasons according to their environmental similarity, while preserving the Euclidean distance among sites based on eigenvectors (Borcard et al., 2018). A similarity percentage analysis (SIMPER) then determined the individual contribution of each species (Oksanen et al., 2017), thus clarifying those that exerted the strongest influence in high water and low water seasons. As a potential source of collinearity between abiotic variables could be the spatial distance between sampling sites, we used Moran’s I statistic (Fortin et al., 1989) to test for spatial autocorrelation. As width, Wv, conductivity and altitude showed spatial autocorrelation (as shown in the Tab. S1), a partial redun­dancy analysis (pRDA) with a variation par­titioning method (Borcard, Legendre, 2002) was used to quantify the relative importance of environmental variables and spatial distances (positive eigenvectors of a principal coordinates of neighborhood matrix – PCNM) to the variation in species composition. We prepared two matrices for the analysis: a matrix of fish species abundances after performing a Hellinger transformation, which makes community composition data reliable for linear modeling (Legendre, Gallagher, 2001) and a matrix of environmental factors (dissolved oxygen, electrical conductivity, temperature, hydrogen potential, transparency, depth, width and water velocity). The pRDA is similar to multiple regres­sion models, except that it allows for the analysis of multiple response variables. Previously, to remove collin­earity among variables, a forward selection (α = 0.05) procedure was applied to select and evaluate sets of environmental variables that each explained significant additional varia­tion in river assemblage composition and abundance (Ter Braak, Smilauer, 1998). Significance of canonical axes and variation explained by environmental variables were based on 10,000 Monte Carlo permutations. The VEGAN package (Oksanen et al., 2017) was used to run pRDA and PCNM analyses; the function “princomp” in the “vegan” package was used for the PCA and the APE Package (Paradis et al.,2004) was used to run MORAN I. All analyses were performed in R 3.5.0 (R Development Core Team, 2018). The results were considered significant when P ≤ 0.05.

Results​

---

The average depth of the Tarumã River during the low water season was 2.8 ± 0.9 m; the average width was 32.8 ± 7.8 m; and the average water velocity 0.4 m.s^-1. During the wet season, the average depth, width, and water velocity values were 5.6 ± 1.2 m; 41.9 ± 4.0 m; and 0.3 ± 0.1 ms^-1, respectively. The average transparency in the low water season was 1.2 ± 2.1 cm and the average transparency in the high water seasons 1.1 ± 0.4 cm. The first two axes of the PCA summarized 61.8% of the variation in the environmental matrix (PC1 = 41.6% and PC2 = 20.2%; Tab. 1). The ordination of the samples in the space formed by these axes evidenced that sampling sites in the high water period are more similar than sampling sites in low water, and that the depth, temperature, dissolved oxygen and electrical conductivity were the most important variables for explaining these differences (Fig. 2).

FIGURE 2 | Ordination of sampling sites in the Tarumã River basin studied during the high water (black circle) and low water (white circle) season, along the first two axes of the Principal Component Analysis (PCA).

TABLE 1 | Descriptors of the fish assemblages, environmental variables (mean ± SD), and scores on the first two axes of the principal components (PCA) in the high water and low water seasons of the Tarumã River.

A total of 223 fish belonging to five orders, fourteen families and twenty-eight species were sampled (see Tab. S2). Characiformes was the most abundant and diverse of the orders in both seasons of the hydrological cycle, followed by Siluriformes and Cichliformes. In the high water season, the most abundant species were Myloplus rubripinnis (Müller & Troschel, 1844), Serrasalmus compressus Jégu, Leão & Santos, 1991,and Serrasalmus rhombeus. In the low water season, the piranha S. rhombeus was the most abundant, followed by Myloplus lobatus (Valenciennes, 1850) and Prochilodus nigricans Spix & Agassiz, 1829. Piscivorous were the most abundant trophic category in both seasons (n_{Low-water (Lw)} = 73.58%; n_{High-water (Hw)} = 53.54%), followed by herbivores (n_Lw = 21.17%; n_Hw = 29.29%), detritivores (n_Lw = 20.16%) and omnivores (n_Hw = 12.12%) (Tab. 2).

TABLE 2 | Taxons, species code, numerical abundance of the species sampled during the high water (Hw) and low water (Lw) seasons, trophic categorization (TC) (CAR = Carnivores, DET = Detritivores, HER = Herbivores, ILI = Iliophagous, INS = Insectivores, INV = Invertivores, ONI = omnivores, PIS = piscivorous, PLA = planktivores, LEP = lepidophagous) and references of the species collected in the Tarumã River, Jaru Biological Reserve, Machado River basin, northern Brazil. * = in process of deposit in Museu de Zoologia da Universidade de São Paulo, São Paulo (MZUSP). ** = specimens not listed in collection.

Seven species contributed to 72% of the dissimilarity of the fish assemblages between the hydrological seasons. M. rubripinnis (4.6%), S. compressus (3.2%), S. rhombeus (3.0%), B. cuvieri (1.2%), M. lobatus (0.8%), Hydrolycus armatus (Jardine, 1841) (0.8%)and P. nigricans (0.4%) showed the highest abundance during the high water season. However, S. rhombeus (6.0%), M. lobatus (4.0%), P. nigricans (3.8%), S. compressus (2.8%), H. armatus (2.4%), Boulengerella cuvieri (Spix & Agassiz, 1829)(2.0%)and M. rubripinnis (0.2%) were the dominant species during the low water seasons (Fig. 3; Tab. 3).

TABLE 3 | Results of SIMPER analysis of the fish assemblage between high (H) and low (L) water seasons.

FIGURE 3 | Mean abundance and relative contribution of the most important species accounted by SIMPER analysis for both seasons of the hydrological cycle. Black and white bars represent the mean abundance of each species ate high water and low water season, respectively. The gray circles are the relative contribution estimated by the SIMPER Analysis.

The association of the composition of fish species and the seasons, environmental variables and spatial distances explained 33 % (pRDA1 = 21%; pRDA2 = 12%) of the assemblage composition variation (Radj² = 0.23; F = 1.90; p = 0.03). Assemblage composition was significantly influenced by environmental variables and accounted for 26% (pRDA1 = 18%; pRDA2 = 8%) (Radj² = 0.43; F = 1.21; p = 0.02), but none of the spatial predic­tors presented significant effects (Radj² = 0; F = 0.69; p = 0.79). The pRDA indicated that six variables were redundant, therefore these variables were excluded from the environmental data set. The forward selec­tion procedure showed that depth, water velocity and pH were the environ­mental variables that accounted for significant (P < 0.05) portions of the total variance in fish species composition. The pRDA with these three environmental variables produced an ordination in which all canonical axes were significant (Monte Carlo test; P < 0.05). The first axis of pRDA separated the low water season sampling points with predominance of M. rubripinnis, Hydrolycus tatauaia Toledo-Piza, Menezes & Santos, 1999 and S. compressus from high water season with predominance of M. lobatus and P. nigricans. The most important abiotic variables for species composition, positively related to the first axis of analysis were depth (F = 2.20; p = 0.05) and pH (F = 2.69; p = 0.03), associated with H. tatauaia, M. rubripinnis,and S. compressus; and water velocity, that presented negative values in axis 1 of the pRDA (F = 2.56; p = 0.03), associated with B. cuvieri, S. rhombeus,and P. nigricans (Fig. 4).

FIGURE 4 | Ordination of the Partial Redundancy Analysis (pRDA) on fish species composition (see codes on Tab. 2) with sites in high water (black circle) low water (white circle) season and abiotic variables relationships (arrows). Dep = Depth; Wv = Water velocity; pH = Hydrogen potential.

Discussion​

---

The species composition of the Tarumã River basin was influenced by environmental variables as predicted by our hypothesis, however, this composition differed seasonally. As indicated by pRDA, the fish assemblages sampled during high water were positively associated with chemical variables: dissolved oxygen and temperature. During the low water season, the reduction of the water body was determinant for the negative association the fish assemblages and the physical variables of depth and width.

Our pRDA results demonstrated that, depth and dissolved oxygen were significant determinants of the structure of fish assemblages as found in other studies conducted in Neotropical rivers (Tejerina-Garro et al., 1998; Petry et al., 2003; Arantes et al., 2013; Arantes et al., 2018). Deeper aquatic habitats in the floodplain support greater abundance of fish species, as they are more stable during periods of extreme drought (Arantes et al., 2013). Previous studies showed that the lateral flooding changes the proportion of suspended and dissolved substances in the water, with consequent alterations of the physicochemical variables of lotic systems (Melack, Forsberg, 2001). Nevertheless, Bayley (1995) indicates that when the water level increases in high water seasons the decomposition rates of organic matter also increases, resulting increased levels of dissolved oxygen. In general, floodplain water bodies have lower concentrations of dissolved oxygen, probably as a result of the combination of elevated amounts of organic matter and the inhibiting effects of the vegetation cover in the aquatic photosynthesis process (Arantes et al., 2018).

Most rivers in the Amazon basin are extremely poor in carbonate buffering capacity (Sioli, 1984), while pH is controlled predominantly by the concentration of these organic acids (Belger, Forsberg, 2006). Although pH was an important variable in fish assemblage structure in our analysis, it did not show much variation between the low and high water seasons. However, we highlight that the pH values ​​of the Tarumã River (_(Lw) = 6.4; _(Hw) = 6.2) were similar to those found for other tributaries in the Amazon region. Barbosa et al. (2010) describe that the pH in the Amazon River was nearly constant (~6.5), whereas on the floodplain it increased from an average of 6.7 during low water to 7.7 at receding state. The pH promotes physiological constraints upon aquatic organisms, this influences ionic balance (Matsuo, Val, 2002) and a host of other physiological processes in fishes, including oxygen affinity of hemoglobin, digestion, and osmotic balance (Val, Almeida-Val, 1995). Clearwaters of the Upper Orinoco River, Upper Casiquiare River, Upper Siapa River, as well as the Tarumã River, are associated with more moderate pH, but also with higher levels of suspended particulate matter, including clay, particularly during periods of high flow (Winemiller et al., 2008). Most of the clearwater rivers have high water transparency during periods of base-flow conditions, but many of these rivers may become slightly to moderately turbid during periods of high water (Winemiller et al., 2008). In clearwater rivers, sustained low water conditions result in lower water transparency owing to higher concentrations of phytoplankton (Cotner et al., 2006).

Fluctuations in the water-level strongly influence the water velocity of rivers, which in turn change limnological variables and assemblage composition (Affonso et al., 2015). Corroborating with previous studies (Willis et al., 2015) our results show that water velocity negatively influences the fish assemblage structure. In the Tarumã River the composition of fish species, in more complex habitats in the low water period, possibly was associated with the greater production of peripheral algae, favoring the occurrence of algivores such as P. nigricans. The occurrence of structurally more complex habitat within the river during low waters, provides refuge and food for species of low trophic fish (prey), thus favoring an increase in the abundance of piscivorous fish such as B. cuvieri and S. rhombeus. In fast-flowing environments, which is common in periods of high water, the current velocity introduces an element of physical complexity that influences the use of horizontal and vertical aquatic habitats by fishes (Wood, Bain, 1995).

In both hydrological periods, piscivorous, followed by herbivores, were the most representative group in abundance. Many studies on trophic ecology in clear water basins, including in the Trombetas, Mucajaí and Teles Pires rivers, have analyzed the trophic structure of the fish assemblage pointing out the greater representativeness of piscivorous and herbivore fish in the samples (Dary et al., 2017). However, the greater representativeness of piscivorous in fish assemblages was also pointed out by Ferreira et al. (1988), Ferreira (1993), Zuanon (1999), Dary et al. (2017), Araújo et al. (2009), and Lima et al. (2020) for the Mucajaí, Trombetas, Xingu, Teles Pires and Madeira rivers, respectively, with their drainage basins located in the Guiana and Brazilian shields, which have geomorphologies similar to the Tarumã River. Similar to our study, herbivorous fish also constituted a large part of the biomass and abundance of these clear water rivers (Zuanon, 1999; Dary et al., 2017). This fact indicates that clear water rivers with low primary production (compared to white water rivers, see Melack, Forsberg, 2001) can sustain high fish abundance and biomass, probably due to the rapid assimilation of local productivity in the biomass of fish (Dary et al., 2017). Due to the seasons of the hydrological cycle, and the trophic ecology of the fish, a classic pattern of species distribution (predominance of frugivorous/omnivorous species in high water and piscivorous/carnivorous in low water seasons) has been observed in the Amazonian rivers in several studies (Costa, Freitas, 2015; Castello et al., 2015; Duarte et al., 2019). During rising and high water seasons, expansions in the aquatic environment toward the forest favors the exploration of various habitats and broadens the food spectrum of fishes (Noveras et al., 2012; Loebens et al., 2020). In these seasons, fishes inhabit river channels and floodplain lakes in order to spawn and migrate laterally on to the advancing littoral zone (Fernandes, 1997). The advancing littoral zone allows fish of all ages to feed on abundant food sources (i.e., detritus, insects, fruits and seeds) found in vegetated floodplain habitats (Goulding, 1980). During low water season, the reduction of the aquatic environment area leads to food scarcity for most fish species (Resende et al., 1996).

For carnivorous/piscivorous fishes this pattern may be inverted. During the high water season, fish species disperse over the floodplain in search of different food sources and shelter, which decreases their accessibility to predators. During the low water season, prey species are more concentrated in the restricted water bodies and become more available to potential predators, such as S. rhombeus, H. tatauaia, and S. compressus (Ferreira et al., 2014). This season can be characterized as a “biological interaction phase”, since space (i.e., size and number of habitats) decreases while density of individuals and species increases (Ward et al., 1999), thus increasing biotic interactions (Espínola et al., 2017).

Ecological dynamics in rivers with tropical floodplains are governed by deterministic and stochastic mechanisms (Hurd et al., 2016). Improved understanding of the mechanisms that regulate the dynamic structure of fish assemblages is extremally needed. As previously proposed by several studies (Junk et al., 1983; Saint-Paul et al., 2000; Hoeinghaus et al., 2003; Siqueira-Souza, Freitas, 2004; Freitas, Garcez, 2004; Torrente-Vilara et al., 2011; Freitas et al., 2013; Costa, Freitas, 2015; Cella-Ribeiro et al., 2017; Arantes et al., 2018; Costa et al., 2020), our results have also shown the importance of environmental variables as drivers of fish assemblages. In particular, our results reveal the great importance of the flood pulse, as a key environmental factor to the assemblage structure in the western portion of the Amazon basin. Our recommendation is to increase efforts, by the public and private sector, towards the protection of Amazonian hydrographic basins in order to guarantee functionality (ecosystem services) and connectivity between aquatic environments. We emphasize that greater financial support and the implementation of adequate infrastructure to carry out studies in protected areas, are needed for understanding its environmental dynamics, as well as for decision-making in the reassessment of the limits of part of the existing reserves. There is a great concern for the future of these areas, especially when we considering the current environmental policies in progress in Brazilian territory. Rivers constitute the main axes of PAs in the Amazon and must be conserved to promote the adequate preservation of headwaters and hydrological connectivity. This understanding further serves as a baseline in order to support the efficient management of exploited species, as well as aiding in the development of conservation strategies against anthropic and natural environmental changes.

Acknowledgments​

---

The authors are grateful to the staff members of the Instituto Chico Mendes de Conservação da Biodiversidade (ICMBio) for their help and assistance during the fieldwork. We would like to thank the staff at the Ichthyology and Fishing Laboratory, Universidade Federal de Rondônia, Carolina R. C. Doria for allowing us to use the facilities. This study was funded by Jaru Biological Reserve.

References​

---

Anjos MRD, Machado NG, Pedersoli MA, Pedersoli NRB, Barros BS, Lourenço IH, Barreiros JP. Survey of fish species from the Lower Roosevelt River, Southwestern Amazon basin. Biota Neotrop. 2019; 19(4):3–10. https://doi.org/10.1590/1676-0611-BN-2018-0717

Affonso AG, Queiroz HL, Novo EMLM. Abiotic variability among different aquatic systems of the central Amazon floodplain during drought and flood events. Braz J Biol. 2015. 75:60–69.

Arantes CC, Castello L, Cetra M, Schilling A. Environmental influences on the distribution of arapaima in Amazon floodplains. Environ Biol Fish. 2013; 96(10–11):1257–67. https://doi 10.1007/s10641-011-9917-9.s

Arantes CC, Winemiller KO, Petrere M, Castello L, Hess LL, Freitas CE. Relationships between forest cover and fish diversity in the Amazon River floodplain. J Appl Ecol. 2018; 55(1):386–95. https://doi.org/10.1111/1365-2664.12967

Araújo TRD, Ribeiro AC, Doria CRDC, Torrente-Vilara G. Composition and trophic structure of the ichthyofauna from a stream downriver from Santo Antonio Falls in the Madeira River, Porto Velho, RO. Biota Neotrop. 2009; 9(3):21–29. http://dx.doi.org/10.1590/S1676-06032009000300001

Arrington DA, Winemiller KO. Habitat affinity, the seasonal flood pulse, and community assembly in the littoral zone of a Neotropical floodplain river. J N Am Benthol Soc. 2006; 25:26–141. https://doi.org/10.1899/0887-3593(2006)25[126:HATSFP]2.0.CO;2

AVMA Panel on Euthanasia. American Veterinary Medical Association. 2000 Report of the AVMA Panel on Euthanasia. J Am Vet Med Assoc. 2001; 218(5):669–96. https://doi.org/10.2460/javma.2001.218.669

Azevedo-Santos VM, Frederico RG, Fagundes CK, Pompeu PS, Pelicice FM, Padial AA, Oliveira FJ. Protected areas: A focus on Brazilian freshwater biodiversity. Divers Distrib. 2018; 25(3):442–48. https://doi.org/10.1111/ddi.12871

Barbosa CCF, Moraes Novo EML, Melack JM, Gastil-Buhl M, Pereira Filho W. Geospatial analysis of spatiotemporal patterns of pH, total suspended sediment and chlorophyll-a on the Amazon floodplain. Limnology. 2010; 11(2):155–66. https://doi.org/10.1007/s10201-009-0305-5

Barbosa TAP, Benone NL, Begot TOR, Gonçalves A, Sousa L, Giarrizzo T, Montag LFDA. Effect of waterfalls and the flood pulse on the structure of fish assemblages of the middle Xingu River in the eastern Amazon basin. Braz J Biol. 2015; 75(1):78–94. http://dx.doi.org/10.1590/1519-6984.00214bm

Bayley PB. Understanding large river: floodplain ecosystems. BioScience. 1995; 45:153–58. https://doi.org/10.2307/1312554

Belger L, Forsberg BR. Factors controlling Hg levels in two predatory fish species in the Negro River basin, Brazilian Amazon. Sci Total Environ. 2006; 367(1):451–59. https://doi.org/10.1016/j.scitotenv.2006.03.033

Borcard D, Legendre P. All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices. Ecol Model. 2002; 153:51–68. https://doi.org/10.1016/S0304-3800(01)00501-4

Borcard D, Gillet F, Legendre P. Numerical ecology with R. New-York: Springer; 2018.

BRASIL. Ministério do Meio Ambiente – MMA. Reserva biológica do Jaru. Porto Velho: Instituto Chico Mendes de Conservação da Biodiversidade; 2010.

Bruner AG, Gulhson RE, Rice RE, Fonseca GAB. Effectiveness of parks in protecting tropical biodiversity. Science. 2001; 291:125–28. https://doi.org/10.1126/science.291.5501.125

Castello L, Isaac VJ, Thapa R. Flood pulse effects on multispecies fishery yields in the Lower Amazon. R Soc Open Sci. 2015; 2:150–62. https://doi.org/10.1098/rsos.150299

Cella-Ribeiro A, Doria CCR, Dutka-Gianelli J, Alves H, Torrente-Vilara G. Temporal fish community responses to two cascade run-of-river dams in the Madeira River, Amazon basin. Ecohydrology. 2017; 10:e1889. https://doi.org/10.1002/eco.1889

Costa ID, Freitas CEC. Factors determining the structure of fish assemblages in an Amazonian River near to oil and gas exploration areas in the Amazon basin (Brazil): establishing the baseline for environmental evaluation. Zoologia. 2015; 32:351–59. https://doi.org/10.1590/S1984-46702015000500004

Costa ID, Mazzoni R, Petry AC. Fish assemblages respond to forest cover in small Amazonian basins. Limnologica. 81(2020); 125757. https://doi.org/10.1016/j.limno.2020.125757

Cotner JB, Montoya JV, Roelke DL, Winemiller KO. Seasonally variable riverine production in the Venezuelan llanos. J N Am Benthol Soc. 2006; 25(1):171–84. https://doi.org/10.1899/0887-3593(2006)25[171:SVRPIT]2.0.CO;2

Dary EP, Ferreira E, Zuanon J, Röpke CP. Diet and trophic structure of the fish assemblage in the mid-course of the Teles Pires River, Tapajós River basin, Brazil. Neotrop Ichthyol. 2017; 15(4):12–23. https://doi.org/10.1590/1982-0224-20160173

Duarte C, Magurran AE, Zuanon J, Deus CP. Trophic ecology of benthic fish assemblages in a lowland river in the Brazilian Amazon. Aquat Ecol. 2019; 53(1):707–18. https://doi.org/10.1007/s10452-019-09720-5

Duarte C, Py-Daniel LHR, Deus CPD. Fish assemblages in two sandy beaches in lower Purus river, Amazonas, Brazil. Iheringia Ser Zool. 2010; 100(4):319–28. https://doi.org/10.1590/S0073-47212010000400006

Duponchelle F, Isaac VJ, Doria, CRC, Van Damme PA, Herrera-R GA, Anderson EP et al. Conservation of migratory fishes in the Amazon basin. Aquat Conserv. 2021; 31(5):1087–105.

Espínola LA, Rabuffetti AP, Abrial E, Amsler ML, Blettler MCA, Paira AR, Santos LN. Response of fish assemblage structure to changing flood and flow pulses in a large subtropical river. Mar Freshwater Res. 2017; 68(2):319–30. https://doi.org/10.1071/MF15141

Fernandes CC. Lateral migrations of fishes in Amazon floodplains. Ecol Freshw Fish. 1997; 2(1):36–44. https://doi.org/10.1111/j.1600-0633.1997.tb00140.x.

Ferreira E, Santos GM, Jégu M. Aspectos ecológicos da ictiofauna do rio Mucajaí, na área da ilha Paredão, Roraima, Brasil. Amazoniana. 1988; 10(3):339–52.

Ferreira FS, Vicentin W, Costa FEDS, Súarez YR. Trophic ecology of two piranha species, Pygocentrus nattereri and Serrasalmus marginatus (Characiformes, Characidae), in the floodplain of the Negro River, Pantanal. Acta Limnol Bras. 2014; 26:381–91. https://doi.org/10.1590/S2179-975X2014000400006

Ferreira J. Cerrado: um ecossistema desprezado. Ecologia e Desenvolvimento. 1993. 23:39–47.

Fortin MJ, Drapeau P, Legendre P. Spatial autocorrelation and sampling design in plant ecology. Vegetatio. 1989; 83:209–22. https://doi.org/10.1007/bf00031693

Frederico RG, Zuanon J, De Marco P, Jr. Amazon protected areas and its ability to protect stream dwelling fish fauna. Biol Conserv. 2018; 219(1):12–19. https://doi.org/10.1016/j.biocon.2017.12.032

Freitas CEC, Garcez RCS. Fish communities of natural channels between floodplain lakes and Solimoes-Amazonas River (Amazon-Brazil). Acta Limnol Bras. 2004; 16:273–80.

Freitas CE, Siqueira-Souza FK, Humston R, Hurd LE. An initial assessment of drought sensitivity in Amazonian fish communities. Hydrobiologia. 2013; 705(2):159–71. https://doi.org/10.1007/s10750-012-1394-4

Gibbs RJ. Geochemistry of the Amazon River System: Part I. The factors that control the salinity and the composition and concentration of the suspended solids. Geol Soc Am Bull. 1967; 78(10):1203–32. https://doi.org/10.1130/0016-7606(1967)78[1203:TGOTAR]2.0.CO;2

Goulding M. The fishes and the forest: explorations in Amazonian natural history. New York: Univ. of California Press; 1980.

Haffer J. Contact zones between birds of southern Amazonia. Ornithol Monogr. 1997; 48(1):281–305. https://doi.org/10.2307/40157539

Hoeinghaus DJ, Layman CA, Arrington DA, Winemiller KO. Spatiotemporal variation in fish assemblage structure in tropical floodplain creeks. Environ Biol Fishes. 2003; 67:379–87. https://doi.org/10.1023/A:1025818721158

Hurd LE, Sousa RG, Siqueira-Souza FK, Cooper GJ, Kahn JR, Freitas CE. Amazon floodplain fish communities: habitat connectivity and conservation in a rapidly deteriorating environment. Biol Conserv. 2016; 195:118–27. https://doi.org/10.1016/j.biocon.2016.01.005

ICMBio. Plano de manejo da Reserva Biológica do Jaru. Brasília: ICMBIO/MMA; 2010.

Jézéquel C, Tedesco PA, Darwall W, Dias MS, Frederico RG, Hidalgo M et al. Freshwater fish diversity hotspots for conservation priorities in the Amazon Basin. Conserv Biol. 2020; 34(4):956–65.

Junk WJ, Piedade MTF, Schöngart J, Cohn-Haft M, Adeney JM, Wittmann F. A classification of major naturally-occurring Amazonian lowland wetlands. Wetlands. 2011; 31:623–40. https://doi.org/10.1007/s13157-011-0190-7

Junk WJ, Soares GM, Carvalho FM. Distribution of fish species in a lake of the Amazon river floodplain near Manaus (Lago Camaleão), with special reference to extreme oxygen conditions. Amazoniana. 1983; 7:397–431. Available from: http://hdl.handle.net/21.11116/0000-0004-6B48-4

Junk WJ, Soares MGM, Bayley PB. Freshwater fishes of the Amazon rivers basin: their biodiversity. Aquat Ecosyst Health Manag. 2007; 10(2):153–73. https://doi.org/10.1080/14634980701351023

Justina EED. Zoneamento geoambiental da reserva biológica do Jaru e zona de amortecimento-RO, como subsídio ao seu plano de manejo. São Paulo: Universidade Estadual Paulista; 2009.

Keppeler FW, Hallwass G, Silvano RAM. Influence of protected areas on fish assemblages and fisheries in a large tropical river. Oryx. 2017; 51(2):268–79. https://doi.org/10.1017/S0030605316000247

Legendre P, Gallagher ED. Ecologically meaningful transformations for ordination of species data. Oecologia. 2001; 129(2):271–80. https://doi.org/10.1007/s004420100716

Leite RN, Rogers DS. Revisiting Amazonian phylogeography: insights into diversification hypothesis and novel perspectives. Org Divers Evol. 2013; 13:639–64. https://doi.org/10.1007/s13127-013-0140-8

Lima MA, Doria CR, Carvalho AR, Angelini R. Fisheries and trophic structure of a large tropical river under impoundment. Ecol Ind 2020; 113:106–62. https://doi.org/10.1016/j.ecolind.2020.106162

Loebens SC, Farias EU, Freitas CEC, Yamamoto KC. Influence of hydrological cycle on the composition and structure of fish assemblages in an igapó forest, Amazonas, Brasil. Bol Inst Pesca. 2020; 45(3):427–32. https://doi.org/10.20950/1678-2305.2019.45.1.432

Lonardoni AP, Goulart E, Oliveira EF, Abelha MCF. Hábitos alimentares e sobreposição trófica das raias Potamotrygon falkneri e Potamotrygon motoro (Chondrichthyes, Potamotrygonidae) na planície alagável do alto rio Paraná, Brasil. Act Scient. 2006; 28(3):195–202.

Matsuo AY, Val AL. Low pH and calcium effects on net Na+ and K+ fluxes in two catfish species from the Amazon River (Corydoras: Callichthyidae). Braz J Med Biol Res, 2002; 35(3):361–67. https://doi.org/10.1590/S0100-879X2002000300012

Melack JM, Forsberg BR. Biogeochemistry of Amazon floodplain lakes and associated wetlands. New York: Oxford University Press; 2001. https://doi.org/10.1093/oso/9780195114317.003.0017

Mérona B, Rankin-de-Mérona J. Food resource partitioning in a fish community of the central Amazon floodplain. Neotrop Ichthyol. 2004; 2(2):75–84. http://dx.doi.org/10.1590/ S1679-62252004000200004

Moura AN, Araújo EL, Bittencurt-Oliveira MC, Pimentel RMM, Albuquerque UP. Reservatórios do Nordeste do Brasil: biodiversidade, ecologia e manejo. Bauru. 2010.

Nelson JS, Grande TC, Wilson MV. Fishes of the world. UK: John Wiley & Sons; 2016.

Noveras J, Yamamoto KC, Freitas CEC. Use of the flooded forest by fish assemblages in lakes of the National Park of Anavilhanas (Amazonas, Brazil). Acta Amaz. 2012; 42(4):567–72. https://doi.org/10.1590/S0044-59672012000400015

Oberdorff T, Dias MS, Jézéquel C, Albert JS, Arantes CC, Bigorne R et al. Unexpected fish diversity gradients in the Amazon basin. Sci Adv. 2019; 0:1–10. https://doi.org/10.1126/sciadv.aav8681

Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’hara RB, Wagner H. Vegan: community ecology package. R package version 2.3-0. https://cran.r-project.org/web/packages/vegan/index.html; 2017.

Paradis E, Claude J, Strimmer K. APE: analysis of phylogenetics and evolution in R language. J Bioinform. 2004. 20(2):289–90. https://doi.org/10.1093/bioinformatics/btg412.

Peláez O, Pavanelli CS. Environmental heterogeneity and dispersal limitation explain different aspects of β-diversity in Neotropical fish assemblages. Freshw Biol. 2019; 64(3):497–505. https://doi.org/10.1111/fwb.13237

Peterson CC, McIntyre P. Ontogenetic diet shifts in Roeboides affinis with morphological comparisons. Env E Biol Fish. 1998; 53(1):105–10.

Petry P, Bayley PB, Markle DF. Relationships between fish assemblages, macrophytes and environmental gradients in the Amazon River floodplain. J Fish Biol. 2003; 63(3):547–79. https://doi.org/10.1046/j.1095-8649.2003.00169.x

Pouilly MF, Lino JG, Bretenoux P, Rosales C. Dietary-morphological relationships in a fish assemblage of the Bolivian Amazonian floodplain. J Fish Biol. 2003; 62(5):1137–58. http://dx.doi.org/10.1046/j.1095-8649.2003.00108.x

Queiroz LJ, Torrente-Vilara G, Vieira FG, Ohara WM, Zuanon J, Doria CR. Fishes of Cuniã Lake, Madeira River Basin, Brazil. Check List. 2013; 9(3):540–48. https://doi.org/10.15560/9.3.540

R Development Core Team. R: a language and environment for statistical computing. Retrieved from. R Foundation for Statistical Computing, Vienna, Austria. 2018. Available from: https://www.r-project.org/

Reis RE, Kullander SO, Ferrai Jr, CJ. Check list of the freshwater fishes of South and Central America. Porto Alegre: EDIPUCRS. 2003.

Resende EK, Pereira RAC, de Almeida VLL, Silva AG. Alimentação de peixes carnívoros da planície inundável do Rio Miranda, Pantanal, Mato Grosso do Sul, Brasil. Mato Grosso do Sul: Embrapa Pantanal-Boletim de Pesquisa e Desenvolvimento; 1996. Available from: http://www.infoteca.cnptia.embrapa.br/infoteca/handle/doc/789740

Röpke CP. Estrutura trófica das assembléias de peixes em biótopo de herbáceas aquáticas nos rios Araguaia (Tocantins) e Trombetas (Pará), Brasil. [Master Dissertation]. Manaus: Instituto Nacional de Pesquisas da Amazônia; 2008.

Röpke CP, Amadio SA, Winemiller KO, Zuanon J. Seasonal dynamics of the fish assemblage in a floodplain lake at the confluence of the Negro and Amazon Rivers. J Fish Biol. 2016; 89(1):194–212. https://doi.org/10.1111/jfb.12791

Santos GM, Merona B. Juras AA, Jegu M. Peixes do baixo rio Tocantins: 20 anos depois da usina hidrelétrica Tucuruí. Brasília: Eletronorte; 2004

Santos GM, Ferreira EJG, Zuanon JAS. Peixes comerciais de Manaus. Manaus: ProVárzea; 2006.

Santos NR, Ferreira EJ, Amadio S. Effect of seasonality and trophic group on energy acquisition in Amazonian fish. Ecol Freshw Fish. 2008; 17(2):340–48. https://doi.org/10.1111/j.1600-0633.2007.00275.x

Saint-Paul U, Zuanon J, Correa MAV, García M, Fabré NN, Berger U, Junk WJ. Fish communities in central Amazonian white- and blackwater floodplains. Environ Biol Fishes. 2000; 57(3):235–50. https://doi.org/10.1023/A:1007699130333

Sioli H. The Amazon and its main affluents: hydrography, morphology of the rivers courses, and river types. In: Sioli H, editor. The Amazon: limnology and landscape ecology of a mighty tropical river and its basin. London, Dordrecht; 1984.

Siqueira-Souza FK, Freitas CEC. Fish diversity of floodplain lakes on the lower stretch of the Solimões river. Braz J Biol. 2004; 64(3a):501–10. http://dx.doi.org/10.1590/S1519-69842004000300013

Tejerina-Garro FL, Fortin R, Rodríguez MA. Fish community structure in relation to environmental variation in floodplain lakes of the Araguaia River, Amazon Basin. Environ Biol of Fishes. 1998; 51(4):399–410. https://doi.org/10.1023/A:1007401714671

Ter Braak CT, Smilauer P. CANOCO reference manual and user’s guide to Canoco for Windows: software for canonical community ordination (version 4). New York: Ithaca; 1998.

Torrente-Vilara G, Zuanon J, Leprieur F, Oberdorff T, Tedesco PA. Effects of natural rapids and waterfalls on fish assemblage structure in the Madeira River (Amazon Basin). Ecol Freshw Fish. 2011; 20(4):588–97. https://doi.org/10.1111/j.1600-0633.2011.00508.x

Torrente-Vilara G, Cella-Ribeiro A, Hauser M, Röpke C, Freitas MH, Doria CRDC, Zuanon, J. Spatial segregation between Chalceus guaporensis and Chalceus epakros (Osteichthyes: Characiformes) in the Madeira River, Amazon Basin. Acta Ama, 2018; 48(3): 239–47.  https://doi.org/10.1590/1809-4392201703022

Val AL, Almeida-Val V. Fishes of the Amazon and their environment. Berlin, Springer-Verlag, 1995.

Veríssimo A, Rolla A, Vedoveto M, Futada, SDM. Protected areas in the Brazilian Amazon: challenges e opportunities. Belém: Imazon; 2011.

Ward JV, Tockner K, Schiemer F. Biodiversity of floodplain river ecosystems: ecotones and connectivity. River Res Appl. 1999; 15(1):125–39. https://doi.org/10.1002/(SICI)1099-1646(199901/06)15:1/3<125::AID-RRR523>3.0.CO;2-E

Willis CM, Richardson J, Smart T, Cowan J, Biondo P. Diet composition, feeding strategy, and diet overlap of 3 sciaenids along the southeastern United States. Fish Bull. 2015; 113(3):290–301. https://doi.org/10.7755/FB.113.3.5

Winemiller KO, López-Fernández H, Taphorn DC, Nico LG, Duque AB. Fish assemblages of the Casiquiare River, a corridor and zoogeographical filter for dispersal between the Orinoco and Amazon basins. J Biogeogr, 2008; 35(9):1551–63. https://doi.org/10.1111/j.1365-2699.2008.01917.x

Wittmann F, Marques MC, Damasceno Júnior G, Budke JC et al. The Brazilian freshwater wetscape: Changes in tree community diversity and composition on climatic and geographic gradients. PLoS ONE. 2017; 12:e0175003. https://doi.org/10.1371/journal.pone.0175003

Wood BM, Bain MB. Morphology and microhabitat use in stream fish. Can. J. Fish. Aquat. Sci. 1995; 52(7):1487–98. https://doi.org/10.1139/f95-143

Zavala-Camin LA. 1996. Introdução aos estudos sobre alimentação natural de peixes. Maringá: EDUEM; 1996.

Zuanon J. História natural da ictiofauna de corredeiras do Rio Xingu, na região de Altamira, Pará. [Doctoral Thesis]. Campinas: Universidade Estadual de Campinas; 1999.

Zuluaga-Gómez MA, Fitzgerald DB, Giarrizzo T, Winemiller KO. Morphologic and trophic diversity of fish assemblages in rapids of the Xingu River, a major Amazon tributary and region of endemism. Environ Biology Fishes. 2016; 99(2):647–58. https://doi.org/10.1007/s10641-016-0506-9

Authors

---

Igor D. Costa^1,2 , Natalia N. Santos Nunes³ and Carlos E. C. Freitas⁴

^[1]    Instituto do Noroeste Fluminense de Educação Superior, Universidade Federal Fluminense, Avenida João Jasbick, s/nº, Aeroporto, 28470-000 Santo Antônio de Pádua, RJ, Brazil. igorbiologia@yahoo.com.br (corresponding author).

^[2]    Universidade Federal de Rondônia, Mestrado Profissional em Gestão e Regulação de Recursos Hídricos (PROF-ÁGUA), Campus Ji-Paraná, Rua Rio Amazonas, 351, Jardim dos Mi­grantes, 76900-726 Ji-Paraná, RO, Brazil.

^[3]    Universidade Federal de Rondônia, Programa de Pós-Gra­duação em Ciências Ambientais, Av. Norte Sul 7300, 76940-000 Rolim de Moura, RO, Brazil. nataliansnunes@gmail.com.

^[4]    Universidade Federal do Amazonas, Departamento de Ciências Pesqueiras, Av. Gen. Rodrigo Otávio, 3000, Coroado II, 69077-000 Manaus, AM, Brazil. freitasc50@gmail.com.

Authors Contribution

---

Igor David Costa: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Writing-original draft, Writing-review and editing.
Natalia Neto dos Santos Nunes: Formal analysis, Supervision, Visualization.
Carlos Edwar de Carvalho Freitas: Formal analysis, Methodology, Supervision, Validation, Visualization, Writing-original draft, Writing-review and editing.

Ethical Statement​

---

Samplings were conducted under the licenses SISBIO 47345–1 and 40663–2.

Competing Interests

---

The authors declare no competing interests.

How to cite this article

---

Costa ID, Nunes NNS, Freitas CEC. Factors determining the structure of fish assemblages in Tarumã River, Jaru Biological Reserve, Machado River drainage, northern Brazil. Neotrop Ichthyol. 2021; 19(4):e200111. https://doi.org/10.1590/1982-0224-2020-0111

Copyright​

---

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Distributed under

Creative Commons CC-BY 4.0

© 2021 The Authors.

Diversity and Distributions Published by SBI

Accepted June 30, 2021 by Caroline Arantes

Submitted October 21, 2020

Epub December 13, 2021