How does fragmentation by small dams affect stream ichthyofauna in the upper Paraná River basin?

Gilberto Nepomuceno Salvador^1,2 , Carlos Bernardo Mascarenhas Alves¹, Débora Reis de Carvalho³, Paulo Santos Pompeu⁴, Cecília Gontijo Leal^3,4, Paulo Sérgio Formagio¹, Robert Mason Hughes^5,6,✝ Rosalva Sulzbacher⁴ and Rafael Pereira Leitão^1,2

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Associate Editor: Fernando Carvalho

Section Editor: Fernando Pelicice

Editor-in-chief: José Birindelli

Abstract​

Introduction​

Fluvial systems are longitudinally connected watercourses, with downstream processes being strongly influenced by the context found in upstream regions (Allan, Castillo, 2007). This premise is one of the main foundations of the River Continuum, Serial Discontinuity, and Riverscape Concepts, as they consider the entire fluvial system as a dynamically interconnected sequence of physical gradients and biotic adaptations (Vannote et al., 1980; Ward, Stanford, 1983; Fausch et al., 2002). While this connection is an important factor for the life cycle of aquatic species (Mazzoni et al., 2006), this natural dynamic can be altered by human activities at various spatial extents (Alford, 2014; Brejão et al., 2021; Salvador et al., 2025).

One of the main anthropogenic impacts on freshwater biodiversity is the fragmentation of water bodies (Fuller et al., 2015; Agostinho et al., 2016). This fragmentation can result from various human-made structures, with dam construction being the most common (Fuller et al., 2015). A series of studies focus on the effect of this impact on Neotropical fish fauna (e.g., Suzuki et al., 2011; Loures, Pompeu, 2012; Salvador et al., 2022), however, few are aimed at understanding the effects of this fragmentation on small water bodies. The ease of constructing weirs and small dams (hereafter collectively referred to as “small dams”) has transformed streamscapes. The primary purpose of these structures is water storage in rural areas. It is estimated that 85% of European dams are small dams (Čanjevac, 2020). These structures trigger a series of changes in stream biota and processes, including changes in water and sediment flow, organic matter processing, and thermal and light regimes (Ward, Stanford, 1983; Stanford, Ward, 2001), negatively affecting their aquatic biota (Leitão et al., 2018; Salvador et al., 2023; Drager et al., 2025).

Fish are a key group for assessing degradation in neotropical streams, as they respond to several anthropogenic impacts (e.g., Sanches et al., 2016; de Carvalho et al., 2017; Salvador et al., 2022) across different spatial and temporal scales (e.g., Brejão et al., 2018; Zeni et al., 2020) and from the perspective of distinct ecological traits (Alvarenga et al., 2021; Benone, Montag, 2021; Soares, Nakamura, 2021; Teresa et al., 2021). Stream fishes exhibit diverse life history strategies, many of which are closely linked to upstream-downstream connectivity or fragmentation (Mazzoni, Barros, 2021). However, whereas the effects of larger dams on downstream fish fauna are well known (Power et al., 1996; Granzotti et al., 2018; Fráguas, Pompeu, 2021), the impacts of small dams on stream fauna remain largely unexplored, especially in tropical regions (Salvador et al., 2023).

Small dams can substantially alter stream physical habitat by disrupting natural flow regimes and changing channel morphology, including modifications in width, depth, slope, sediment loads and substrate composition (Januchowski-Hartley et al., 2013; Leal et al., 2016). Consequently, tolerant and sensitive fish species may exhibit different responses to these changes (Cooper et al., 2017), with some families such as Loricariidae and Trichomycteridae being sensitive to fragmentation, while Cichlidae showed tolerance (Salvador et al., 2023). Because of their typically greater dietary plasticity and tolerance to environmental variations, non-native species may be favoured by dams and associated lentic environments (Agostinho et al., 2016; Martelo et al., 2024). Non-native species are those translocated beyond their natural ranges (Simberloff, 2013). After translocation, these species must overcome multiple barriers before dispersing into new systems, and reservoirs can facilitate this process (Agostinho et al., 1999; Blackburn et al., 2011; Pfauserová et al., 2021). Many non-native species have traits that confer advantages in degraded environments, such as accessory respiration and high reproductive capacity (Van Kleunen et al., 2010). In impaired ecosystems, non-native species may not only share niches and occupy similar trophic levels as native species but also exploit resources and habitats unoccupied by native species (Irz et al., 2004; da Silva et al., 2025). Moreover, the dispersal of these species can significantly affect lotic stretches both upstream and downstream (Agostinho et al., 2007). However, this effect is influenced by distance, which may act as a confounding factor as it increases (Ward, Stanford, 1984).

The demand for water in rural areas has led to an increase in the number of small rural dams (Grill et al., 2019). This scenario becomes even more critical in areas that have become drier and hotter, such as the Cerrado (Hofmann et al., 2021). It is one of Brazil’s main biomes, covering an area of over 2 million km² (Klink, Machado, 2005). It is considered a hotspot, showing a high degree of endemism across various groups (Myers et al., 2000; Klink, Machado, 2005). Anthropogenic pressures on this system include the construction of large dams, mining, and the replacement of natural vegetation with agricultural systems (Klink, Machado, 2005; Fernandes, Pessôa, 2011; Salvador et al., 2020). Its landscapes are drained by major river basins, including the upper stretch of the Paraná. The impact of anthropogenic changes on the fish fauna of Cerrado streams has been studied in recent years from several perspectives (de Carvalho et al., 2017; Barbosa et al., 2019; Alvarenga et al., 2021). However, the fragmentation of these systems remains overlooked.

In this context, here we assessed whether fragmentation processes affect Cerrado stream fish richness and abundances and whether the distance from small dams is a relevant factor modulating potential changes in that ichthyofauna. We hypothesized that stream fragmentation would negatively affect the richness and abundance of native fish species, while we expect the opposite response for non-native species, adversely affecting Loricariidae and Trichomycteridae, while beneficially affecting Cichlidae.

Material and methods

Study area. We sampled 136 stream sites (75 to 150 m in extent), ranging from first to third order (sensu Strahler), within the upper Paraná River basin, which extends predominantly through Brazilian territory, covering states in the Southeast and Central-West regions. It is drained by major rivers, such as the Paranaíba, Grande, Tietê, and Paranapanema. The basin undergoes intense landscape transformation, including large agricultural areas, major urban centers, and extensive fragmentation due to hydropower dams. The sites were distributed across four hydrological units (HUs), each of them draining into a different reservoir, all located in the Cerrado biome. The Nova Ponte Hydrological Unit was sampled in 2009 (39 streams), Volta Grande Hydrological Unit in 2011 (29 streams), São Simão Hydrological Unit in 2012 (37 streams), and Furnas Hydrological Unit in 2023 (31 streams) (Fig. 1). Sampling sites were randomly selected using the Generalized Random-Tessellation Stratified (GRTS) method (Olsen, Peck, 2008), ensuring representativeness of the HU’s land-use mosaic, including mechanized agriculture (e.g., soy, corn, and coffee), pastures, urban areas, and natural vegetation, such as natural fields and Cerrado physiognomies. This procedure ensures coverage of landscape natural and degradation gradients while maintaining spatial independence across samples (Macedo et al., 2014).

FIGURE 1| Stream sampling sites in the São Simão (37), Nova Ponte (39), Volta Grande (29), and Furnas (31) Hydrological Units, in the upper Paraná River basin.

Explanatory variables. To understand how fragmentation affects the stream fish fauna, the number of small dams was calculated from a 5 km buffer around each sampling site. This distance was chosen based on the home range of neotropical stream fish (Mazzoni, Barros, 2021). Given the spatial variation of the sites, we used WGS 84/Plate Carrée (EPSG: 32662) as the Coordinate Reference System (CRS). This choice ensured that area and distance calculations were carried out without error, even with the wide spatial distribution across sites. The small dam count was conducted manually using high resolution image present in Google Earth, because some dams were small and often undetected in land-use classifications. However, we used the 2022 MapBiomas project classification (Souza et al., 2020) as a supplementary tool for detection. Because the number of dams may be related to drainage size, we used small dam density as a proxy for fragmentation. To do this, we divided the number of dams per buffer area by the length of the analyzed drainage, obtaining the number of dams per stream/km.

To test the effect of the distance to the dam on the ichthyofauna, we calculated the hydrological distance between each stream site and its closest dam, regardless of any direction, upstream or downstream. For this, we used the “shortest path” tool in QGIS, which calculates the most efficient route between two locations. The calculation was performed between the sampling site and the closest dam, in kilometers, using the hydrographic network provided by SISEMA (2019).

Fish sampling. Fish were collected using semicircular hand nets (0.8 m², 5 mm mesh) and a seine (3 m x 1.5 m, 5 mm mesh) during the dry season. This method is used to estimate fish assemblage composition and abundance because of its ability to sample multiple stream microhabitats (Uieda, Castro, 1999). Sampling was standardized within hydrological units but varied among them. In the Nova Ponte, São Simão, and Volta Grande HUs, fish were collected along a 150 m reach by two people for 2 h in each site. In the Furnas HU, sampling was conducted over 75 m by two people for 1 h on each site. The collected specimens were euthanized with eugenol (Fernandes et al., 2016), fixed in 10% formalin, and stored in 70% ethanol. In the laboratory, species were identified to the lowest possible taxonomic level according to specialized literature (e.g., Graça, Pavanelli, 2007; Ota et al., 2018; Ribeiro et al., 2019) and classified as native or non-native according to Bueno et al. (2021). Voucher specimens were deposited in the ichthyological collection of the Universidade Federal de Lavras (CIUFLA) (Tab. S1).

Data analysis. To assess the effects of fragmentation and the distance to dams on the species richness and abundance of stream fish, we used generalized linear mixed models (GLMM). We chose to use a mixed analysis because differences between locations and spatial variations in response patterns can significantly affect the analysis (Fagundes et al., 2015; Sousa et al., 2023), with the hydrological units included as a random variable in the models. We used small dam density and the hydrological distance between the site and the closest dam as a predictor variable. For this latter analysis, we excluded all buffers that were free of dams. Native and non-native species were analyzed separately, because their responses may be contradictory (Salvador et al., 2023) and we had a specific hypothesis for each of them. The models were based on a Poisson distribution and were executed using the “lme4” package in R (Bates et al., 2015; R Development Core Team, 2020). Considering that species responses to environmental changes are mediated by their set of ecological traits (e.g., morphology, physiology, behavior), it is expected that different fish groups will exhibit distinct responses. In this context, as a complementary approach, we tested the effect of fragmentation by small dams and dam distance for each family using a Threshold Indicator Taxa Analysis (TITAN) (King et al., 2011). TITAN analysis combines a nonparametric change-point approach with indicator species analysis to identify the transition point along an environmental gradient and its direction (increase or decrease) and magnitude (variation in abundance). Magnitudes are standardized by z-scores to allow comparisons among taxa, and the 95^th percentile range obtained by bootstrap indicates the slope of the threshold response. Community-level change points were determined separately for positive and negative responses, based on the largest cumulative z⁺ and z⁻ values. The criteria adopted for TITAN were α < 0.05, purity ≥ 0.95, and reliability ≥ 0.95. Purity represents the proportion of bootstrap replicates with the same response direction, and reliability indicates the proportion of change points with significant p-values (α < 0.05) (Baker, King, 2010). For this analysis, we opted to combine data from native and non-native species since phylogenetically closely related species exhibit more similar functional and ecological attributes than distantly related ones (Soares, Nakamura, 2021).

Results​

We recorded a total of 23,600 fish specimens, identified across 112 species, distributed among six orders and 23 families (Tab. S1). The hydrographic unit with the greatest species richness was São Simão, with 67 recorded species, followed by Furnas (44), Nova Ponte (41), and Volta Grande (40). The average native species richness per sampling point was highest in São Simão (10.1 ± 4.3), followed by Nova Ponte (8.7 ± 3.8), Volta Grande (6.3 ± 3.0), and Furnas (4.3 ± 2.1). Non-native species accounted for nine species in total, with São Simão recording the highest richness (5), followed by Volta Grande (4), Furnas (3), and Nova Ponte (2). The average richness of non-native species was highest in São Simão (1.2 ± 0.7), followed by Furnas (0.5 ± 0.8), Nova Ponte (0.4 ± 0.6), and Volta Grande (0.3 ± 0.5). Overall abundance was highest in Nova Ponte, with 11,530 individuals recorded, followed by São Simão (5,629), Volta Grande (3,537), and Furnas (2,904). The average number of native individuals was highest in Nova Ponte (281 ± 349), followed by São Simão (78 ± 67), Volta Grande (71 ± 77), and Furnas (57 ± 57). For non-native individuals, the average was highest in São Simão (73 ± 89), followed by Volta Grande (18 ± 54), Nova Ponte (15 ± 38), and Furnas (7 ± 21) (Tab. S2).

We identified a wide range of stream fragmentation in all the four HUs, with some sites having close to 0.8 dams/km in the buffer zone, whereas others were free of barriers. The average dam density was 0.19 ± 0.15 dams/km, with 17 sites unfragmented by dams. The mean values were similar across the HUs, with a density of 0.21 ± 0.16 dams/km in São Simão, 0.20 ± 0.16 in Furnas, 0.19 ± 0.12 in Volta Grande and 0.14 ± 0.14 in Nova Ponte.

Small dam density negatively affected both native (z = -22.990; p < 0.001) and non-native (z = -12.826; p < 0.001) fish abundances. The average abundance of native fish in dam-free sites was 134 individuals (indicated by the intercept), decreasing by approximately 74% when density approached 1 dam/km. The effect was more prominent in Nova Ponte HU and less evident in the other HUs (Fig. 2). The abundance of non-native species in dam-free sites was 28 individuals, decreasing by about 78% on sites with one dam/km. The decline in the abundance of non-natives also varied among HUs but followed a different pattern from that observed for native species, being more pronounced in the São Simão HU. Although the effects on fish abundance, fragmentation did not affect native (z = -1.463; p = 0.144) or non-native (z = -0.184; p = 0.853) species richness (Fig. 2).

FIGURE 2| Variation in richness (A and B) and abundance (C and D) of native (A and C) and non-native (B and D) fish species as a function of dam density in the Furnas, Nova Ponte, São Simão, and Volta Grande Hydrological Units, upper Paraná River basin.

We observed an increased abundance of native fishes (z = -20.180; p < 0.001) with proximity to dams. According to our model, sites located close to dams hosted 128 native fish, decreasing by 13.4% for every kilometer travelled upstream. Conversely, the abundance of non-native fishes decreased with proximity to dams (z = 4.459; p < 0.001). The average number of non-native fish was 16 individuals, decreasing by 5.6% per kilometer upstream. These values were also influenced by the HU, with a stronger effect in Nova Ponte for native fish and in Furnas for non-native fish (Fig. 3). In the São Simão HU, both native and non-native fish abundance slightly increased with dam distance, whereas in the Volta Grande HU, only non-native fish abundances increased with dam distance. As observed with dam density, dam distance did not affect native species (z = 0.042; p = 0.967) or non-native species (z = -0.324; p = 0.745) richness (Fig. 3).

FIGURE 3| Variation in richness (A and B) and abundance (C and D) of native (A and C) and non-native (B and D) fish in relation to the distance from dams in the Furnas, Nova Ponte, São Simão, and Volta Grande Hydrological Units, upper Paraná River basin.

Small dam fragmentation affected the occurrence of two fish families, with the effects varying by HU. In the Furnas and Nova Ponte HUs, Trichomycteridae was negatively affected, whereas in São Simão, Cichlidae was negatively affected. None of the families responded to the fragmentation gradient in the Volta Grande HU and no family responded positively to fragmentation in any HU (Fig. 4; Tab. S3). None of the families responded to the dam distance in any HU (Tab. S4).

FIGURE 4| Responses of the Trichomycteridae and Cichlidae family to the fragmentation gradient in the Furnas (A), Nova Ponte (B), and São Simão (C) Hydrological Units, upper Paraná River basin.

Discussion​

In this study, we examined how small dam-induced fragmentation impacts the fish fauna of stream ecosystems in the Cerrado. Our hypothesis that the stream fragmentation would negatively affect the richness and abundance of native fish species, while having the opposite effect on non-native species, was partially supported. We observed the reduced abundance of both native and non-native individuals as small dam density increased, with distinct patterns amongst Hydrological Units (HUs). The negative effects were particularly stronger for the fish families Trichomycteridae and Cichlidae. No family was found to benefit from fragmentation. On the other hand, we observed that dam proximity increased the abundance of native individuals, while the opposite effect was observed for non-native fishes. This result was also differed by HU. Although fragmentation affected fish abundance, neither dam density nor dam distance influenced species richness, contrary to our hypothesis.

Aquatic habitat fragmentation has detrimental impacts on lotic fauna (Poulet, 2007; Agostinho et al., 2016). Reduced fish abundances in highly fragmented streams may be related to the life history traits of certain fish species. Although considered sedentary (Casatti, 2005; Hirt et al., 2011), many stream fish species exhibit longitudinal ontogenetic segregation (Menezes, Caramaschi, 2000; Mazzoni et al., 2004), which can be disrupted by fragmentation caused by small dams and other small barriers (Wilkes et al., 2019; Salvador et al., 2023). Additionally, substantial portions of the allochthonous resources that sustain stream fauna may be retained behind small dams (Januchowski-Hartley et al., 2013; do Amaral et al., 2025). The energy flow in streams is closely linked to the headwater-to-mouth direction (Webster, Patten, 1979; Ensign, Doyle, 2006). However, small dams can disrupt this cycle in streams, as they act as retainers of particulate matter (Sow et al., 2016). Increased fragmentation may lead to a cascading effect, resulting in a decrease in the total energy of the system and a consequent reduction in the overall abundance of individuals.

The effects of fragmentation on the abundance of non-native species contradicted our hypothesis. Based on the findings of non-native fish species being favored in fragmented systems (Agostinho et al., 1999; Becker et al., 2016; Salvador et al., 2023), we also expected a positive effect of dam density on this fish group for small streams. It is also common for these species to be released into artificial environments (Poulet, 2007; Bueno et al., 2021), subsequently dispersing into adjacent streams (Poulet, 2007; Salvador et al., 2023). However, we found negative effects of fragmentation on non-native species. Our sampling focused on streams and revealed Knodus aff. moenkhausii (Eigenmann & Kennedy, 1903) as a dominant non-native species, commonly found in abundance throughout rivers and streams of the Cerrado (Teresa, Casatti, 2013). This is a nektonic species whose ecology resembles that of other Characids found in the basin (Ceneviva-Bastos et al., 2015; Paiva et al., 2025). Despite being non-native, we believe this species experiences fragmentation impacts like a native species, thereby partially masking the expected responses of non-native species.

The differences in fish assemblage responses to fragmentation among Hydrological Units have three possible explanations. First, the diversity and structure of communities can modulate the biological responses even considering the same type of disturbance (Sousa et al., 2023). For example, the fish assemblage in the São Simão HU is more diverse and has unique records compared to the other HUs (Fagundes et al., 2015). These species may exhibit distinct ecological and functional traits that influence the response of this unit differently compared to other pools. Second, another possibility relates to natural river basin differences (e.g., slope, lithology, climate), and this process can modulate the species pool, thereby affecting the community’s dynamics (Cassemiro et al., 2023). For example, the variation in climate and relief between the HUs of Volta Grande and São Simão, which have undulating terrain and a tropical climate, while Nova Ponte and Furnas have more hilly terrain and a humid subtropical climate (Alvares et al., 2013). Lastly, there may be substantial differences in current and historical land use extent and intensity throughout an HU. In our study, the Volta Grande HU is markedly more disturbed than the other HUs (Macedo et al., 2018). High levels of land use disturbance can overwhelm the stream fragmentation disturbance. Land use, natural environmental differences, and local habitat conditions can all affect the fish fauna in a catchment (de Carvalho et al., 2017). These prior impacts may act in synergy with fragmentation, leading to distinct responses amongst Hydrological Units.

The fragmentation effect had a negative impact on two distinct families. In both Furnas and Nova Ponte HUs, Trichomycteridae individuals were strongly affected by fragmentation. These species are considered indicators of good environmental quality (de Carvalho et al., 2017), and fragmentation may increase their susceptibility to decline. Contrary to expectations, Cichlidae individuals were negatively affected by fragmentation in São Simão HU. In general, species in this family tend to benefit from lentic environments and are favored by barriers (Kullander, 2003; Salvador et al., 2023). In São Simão HU, among the four cichlid species detected, only Crenicichla jaguarensis Haseman, 1911 is a reofilic species (Kullander, 2003). However, this species was recorded in only two sites, ruling out the possibility that it was a major factor of the observed response. This suggests that the variations of this group resulting from fragmentation in São Simão are related to other factors, such as the relatively high levels of land use disturbance in the HU (Macedo et al., 2018).

The increase in native fish abundance near the dam can be explained by the accumulation of fish downstream of these structures, as schools tend to gather near the barrier created by the dam (Agostinho et al., 2007). Another factor that helps explain the increase in abundances is that some stream species, particularly Characiformes and Cichliformes, are adaptable to lentic environments (Kullander, 2003; Abelha, Goulart, 2008). These environments can act as buffer zones that facilitate dispersion beyond the reservoir (Poulet, 2007; Salvador et al., 2023). However, we observed that this influence was strongest within the first kilometers, becoming virtually null after 3 or 4 km, which helps distinguish between the responses to fragmentation and distance.

On the other hand, the reduction in non-native species abundance near the dam contradicts our expectations. Many non-native species exhibit high adaptability to lentic environments (Johnson et al., 2008), and therefore proximity to these habitats would be expected to increase their abundance, as previously observed in streams fragmented by tailings dams (Salvador et al., 2023). However, the dominance of the non-native species K. aff. moenkhausii may reverse this pattern. Although it has also been recorded in lentic environments (Sulzbacher et al., 2025), it is commonly associated with lotic habitats (Teresa, Casatti, 2013), and when combined with its numerical dominance among non-native species (accounting for 80% of the non-native abundance), it may contribute to the reversal of the expected trend, as observed in the present study.

As most streams in the Cerrado are currently composed of a mosaic of impoundments and free-flowing sections that often occur in close succession, information on the effects of these structures is crucial for assessing their ecological status and for their management and conservation. Although we detected how stream fragmentation affects fish abundance and diversity, there are many questions remaining. We recommend that future studies focus on understanding the effect of variables in addition to those evaluated in our study, such as reservoir size, age, dam height, and seasonal drawdown (Fergus et al., 2020). Other important questions are related to how these structures affect the stream habitat characteristics (Leal et al., 2016) and how drainage networks influence these responses. Factors such as reservoir and stream slopes may be crucial in this assessment. Lastly, catchment and site conditions are likely key drivers of the fish assemblages occurring near small dams on small streams (Ligeiro et al., 2013; Leitão et al., 2018).

In recent years, the removal of barriers in rivers and streams has become increasingly common in many countries (Bellmore et al., 2017). However, these actions remain scarce in Neotropics. The creation of a research group, like the Adaptive Management of Barriers in European Rivers (AMBER) project in Europe, focused on the restoration of river and stream connectivity, could be an important step to drive these initiatives in Brazil. Understanding the effect of small dam removals, the transformations in local and downstream characteristics, and how aquatic fauna will respond to this removal, is essential to understanding cost-benefit relationships. Along with this effort, it would also be important to study the life histories of stream fish, focusing primarily on their home ranges, a research area that is still underdeveloped considering our rich biodiversity (Mazzoni, Barros, 2021).

Acknowledgments​

We would like to thank everyone who contributed to making this work possible. Many individuals participated in the field collections across each hydrological unit, assisted with species identification, and supported the funding organizations that financed the expeditions and scholarships for those involved in these projects. We would like to especially thank Nara Junqueira, Dennys Drager, and Gabriela Ronzani for their assistance. In the lovely memory of Bob Hughes, who changed the Brazilian freshwater fish science.

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Authors

Gilberto Nepomuceno Salvador^1,2 , Carlos Bernardo Mascarenhas Alves¹, Débora Reis de Carvalho³, Paulo Santos Pompeu⁴, Cecília Gontijo Leal^3,4, Paulo Sérgio Formagio¹, Robert Mason Hughes^5,6,✝ Rosalva Sulzbacher⁴ and Rafael Pereira Leitão^1,2

^[1]    Universidade Federal de Minas Gerais, Av. Pres. Antônio Carlos, 6627, Pampulha, 31270-901, Belo Horizonte, MG, Brazil. (GNS) curimata_gilbert@hotmail.com (corresponding author), (PSF) psformaggio@hotmail.com, (RPL) ecorafa@gmail.com, (CBMA) cbmalves@ufmg.br.

^[2]    Programa de Pós-Graduação em Ecologia, Conservação e Manejo da Vida Silvestre, Universidade Federal de Minas Gerais, Av. Pres. Antônio Carlos, 6627, Pampulha, 31270-901, Belo Horizonte, MG, Brazil.

^[3]    Lancaster Environment Centre, Bailrigg, Lancaster, Zip Code LA1 4YW, UK. (DRC) deboracarvalhobio@gmail.com, (CGL) c.gontijoleal@gmail.com.

^[4]    Departamento de Ecologia e Conservação, Universidade Federal de Lavras, Câmpus Universitário, Cx. Postal 3037, 37200-000, Lavras, MG, Brazil. (PSP) pompeups@gmail.com, (RS) rosalvasulzbacher@gamil.com.

^[5]    Amnis Opes Institute, 2895 SE Glenn Street, Corvallis, OR, 97333, USA. (RMH) hughes.bob@amnisopes.com.

^[6]    Department of Fisheries, Wildlife, & Conservation Sciences, Oregon State University, Nash 104, Corvallis, OR, 97331, USA.

^[✝]    In memoriam

Authors’ Contribution

Gilberto Nepomuceno Salvador: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing-original draft, Writing-review and editing.

Carlos Bernardo Mascarenhas Alves: Conceptualization, Data curation, Funding acquisition, Investigation, Project administration.

Débora Reis de Carvalho: Conceptualization, Data curation, Investigation.

Paulo Santos Pompeu: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology.

Cecília Gontijo Leal: Data curation, Formal analysis, Methodology.

Paulo Sérgio Formagio: Conceptualization, Funding acquisition, Investigation, Project administration.

Robert Manson Hughes: Conceptualization, Formal analysis, Investigation, Methodology.

Rosalva Sulzbacher: Conceptualization, Formal analysis, Investigation, Methodology.

Rafael Pereira Leitão: Formal analysis, Investigation, Methodology, Writing-review and editing.

Ethical Statement​

This research was approved by the Ethics Committee for Animal Use of the Universidade Federal de Lavras (CEUA number 11–23/year 2023) and Collection License SISBIO number 10327–6.

Competing Interests

The author declares no competing interests.

Data availability statement

The data supporting the findings of this study are available from the corresponding author, Gilberto Salvador, upon reasonable request.

AI statement

The ChatGPT (OpenAI) model was used to assist with grammatical correction and editing of the English text.

Funding

This work was funded by ELETROBRAS (Project IBI-FURNAS) and Companhia Energética de Minas Gerais (CEMIG – Peixe-vivo and ProEcos Project GT599). CBMA and PSF were supported by Eletrobras. GNS was supported by the Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG APQ–00401–19) and Eletrobras, RPL was supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq 314464/2023–9), DRC and CGL were supported by UKRI Future Leaders Fellowship (MR/W011085/1), RS was supported by FAPEMIG, RMH received a Fulbright Brasil Distinguished Scholarship.

Supplementary Material

Supplementary material S1

Supplementary material S2

Supplementary material S3

Supplementary material S4

How to cite this article

Salvador GN, Alves CBM, Carvalho DR, Pompeu PS, Leal CG, Formagio PS, Hughes RM, Sulzbacher R, Leitão RP. How does fragmentation by small dams affect stream ichthyofauna in the upper Paraná River basin? Neotrop Ichthyol. 2025; 23(4):e250139. https://doi.org/10.1590/1982-0224-2025-0139

Copyright​

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