Immediate effects of channelization on fish assemblages in two urban tropical streams

Flavia Begnini¹, Luciano Lazzarini Wolff², Taise Miranda Lopes¹, Franco Teixeira-de-Mello³ and Rosilene Luciana Delariva^1,2,4

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Associate Editor: Andrea Bialetzki

Section Editor: Fernando Pelicice

Editor-in-chief: José Birindelli

Abstract​

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Introduction​

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Urbanization is a historical process that involves the progressive occupation and transformation of rural and natural landscapes in cities or metropolises (McGrane et al., 2014; Ortega et al., 2021). This process has been driven by the continued growth of the human population and migration to cities in search of opportunities and access to services (Seto et al., 2012; UN, 2022). Along with transformations, the expansion of global urban areas has brought a series of alterations to natural processes, including deforestation, habitat fragmentation, pollution, soil impermeabilization, and changes in the local water cycle (Alberti, 2005; McGrane et al., 2014).

Among the ecosystems affected by urbanization are urban streams, which have their microbasins located within urban areas or flow toward them (Cunico et al., 2009; Ortega et al.,2021; Bertora et al., 2024). The most conspicuous impacts on these streams areassociated with the discharge of domestic and industrial effluents (McGrane et al., 2014; Alvareda et al., 2020; Bertora et al., 2024), which significantly increase concentrations of nutrients and contaminants, leading to higher water conductivity and suspended solids, as well as reduced dissolved oxygen (Meyer et al., 2005; Daga et al., 2012; Teixeira de Mello et al., 2024). However, organic and chemical pollution are not the sole drivers of urban streams. These systems are also characterized by altered hydrological regimes and substantial physical deterioration of instream habitats (Walsh et al., 2005; McGrane et al., 2014). The removal of native vegetation and the expansion of impermeable surfaces increase surface runoff in urban areas, ultimately leading to higher peak flows during rainfall events (Chen, Olden, 2020; Guimarães et al., 2021). In line with these hydrological changes, urban streams have also undergone multiple alterations, including being channelized, straightened, redirected and even covered over due to urban expansion (Jurajda, 1995; McGrane et al., 2014; González-Trujillo, 2016). Together, these impacts have intensified pollution, reduced self-purification capacity, increased instantaneous discharges, and led to a significant loss of environmental heterogeneity (Walsh et al., 2005; Chen, Olden, 2020).

In addition to stormwater management strategies, watercourse channelization has recently been integrated into the design of urban linear parks. These parks have emerged as innovative urban solutions, combining representative green spaces within city landscapes and becoming established along modified watercourses, while also providing recreational and aesthetic benefits (Riechers et al., 2019; Wantzen et al., 2022). Stream channelization in linear parks includes the construction of drainage infrastructures, which often involves widening and sealing the natural channel with artificial materials such as concrete, rock and gabion structures along banks (Walsh et al., 2005; McGrane et al., 2014). The stream is then diverted into an artificial channel until the concrete sets and construction is completed. Afterward, the stream’s average depth tends to decrease, leading to a local increase in the water flow (González-Trujillo, 2016; Archer et al., 2019).

Streambed concreting primarily impacts ecosystems by replacing natural substrates and reducing habitat heterogeneity (Chen, Olden, 2020; Barrios, Teixeira de Mello, 2022; Moi et al., 2022). However, ecosystem processes are also impacted by reduced materials and energy inputs resulting from canopy removal, ultimately altering the structure and composition of aquatic communities (Grimm et al., 2008; Ramirez et al., 2012; Lisi et al., 2018). Additionally, channelization promotes enhanced water temperatures by enlarging the cross-sectional channel and thus creating more exposure to sunlight on the concrete (Hawley, Bledsoe, 2013; McGrane et al., 2014). All these changes act as environmental filters, reducing sensitive aquatic taxa while favoring tolerant species (Walsh et al., 2005; Bertora et al., 2024), including fish communities (Hermoso et al., 2011; Carvalho, Tejerina-Garro, 2015; Benejam et al., 2016; Allan et al., 2021; Tesitore, Teixeira de Mello, 2023).

The initial alterations in fish assemblage composition and functionality in channelized and urbanized streams are typically evident at the taxonomic level. These early changes are characterized by the decline of slow-moving species that depend on specific microhabitats, generally associated with heterogeneous benthic environments (Boët et al., 1999; Larentis et al., 2021; Bertora et al., 2024). Such species generally exhibit slow growth, late maturation, and low fecundity, often occurring at low population densities (Ortega et al., 2021; Zhang et al., 2024). As habitat simplification intensifies, additional species less tolerant to structural homogenization are progressively excluded, while channelization tends to favor morphotypes adapted to shallow, uniform substrates and accelerated flow conditions (Barrios, Teixeira de Mello, 2022). Thus, species exhibiting greater swimming performance and high trophic plasticity, typical characteristics of opportunistic and generalist fish, tend to dominate, as these enable resource exploitation in environments with reduced structural complexity, such as channelized streams (Boët et al., 1999; Antoniazzi et al., 2023).

Species exhibiting broad trophic plasticity are generally more tolerant to degraded environments. Many of these species also display viviparous reproduction, a strategy typically favored under disturbed conditions, which facilitates the establishment of large populations with low per capita biomass (Lamothe et al., 2018; Cruz, Pompeu, 2020; Larentis et al., 2021). A notable example are the poeciliids, small-bodied fishes consistently identified as reliable bioindicators of anthropogenic disturbance in urban streams (Benejam et al., 2016; Magalhães, Jacobi, 2017; Vidal et al., 2018; Ganassin et al., 2019; Garcia et al., 2021; Larentis et al., 2022). Therefore, the increased abundance of poeciliids in degraded environments is in part due to their reproductive characteristics and their lower individual investments in growth, which require fewer resources and less variety (Lamothe et al., 2018; Cruz, Pompeu, 2020).

Environmental alterations directly affect fish populations by disrupting their natural organization and energy balance. In undisturbed ecosystems, fish assemblages typically exhibit a dynamic equilibrium, where a few large-bodied species at higher trophic levels account for most of the per capita biomass, while numerous small-bodied individuals dominate the lower levels of the food web (Dias, Garro, 2010; Oliveira, Garro, 2010). However, under anthropogenic pressures such as river channelization this balance shifts, favoring tolerant, opportunistic, and small-bodied species characterized by low per capita biomass (Dias, Garro, 2010; Oliveira, Garro, 2010; Moi, Teixeira de Mello, 2022). Therefore, metrics of species abundance and biomass have proven to be effective tools for assessing fish assemblage structure and detecting early signs of environmental degradation.

Although a number of streams in Brazil have already been channelized, few studies have conducted biotic assessments of such interventions (Macedo et al., 2020; Macedo et al., 2022). Even these studies have focused solely on assessing aquatic invertebrates, while the fish fauna impacted by urban stream channelization has not been evaluated. Notwithstanding, the few studies by countries in the global North on river channelization have produced long-term contrasting results on fish structuring (Lennox, Rasmussen, 2016; Miranda et al., 2023), highlighting a lack of attention to the immediate status of fish fauna assessed simultaneously with the implementation of channelization works. In this study, we have the opportunity to semi-experimentally evaluate the effects of channelization, both under way and recently completed, in two urban streams located in the Iguaçu and Piquiri river basins (Upper Paraná), which belong to two global biogeographic regionalizations of Earth’s freshwater biodiversity (Feow, 20215). This immediate assessment is crucial because the intense impacts of channelization can promptly reduce fish richness, improve opportunists or even reset this fauna, potentially causing local extinctions (Dudgeon et al., 2006).

Considering the drastic changes in the substrate, microhabitats, marginal vegetation, and water physical and chemical conditions, we aimed to evaluate how these alterations influence the structure and composition of the local fish fauna assemblages. Environmental data, fish richness, abundance, and biomass collected across three phases (before intervention, during, and after channelization) along channelized and unchannelized sites, were used to answer the following questions: (i) Did environmental variables (physico-chemical, hydrological and habitat structure) differ between phases and channelized and unchannelized sites for each stream? (ii) Are there differences in the taxonomic composition of fish species across the channelization phases and sites? (iii) Did fish assemblage metrics (richness, abundance, and biomass) vary throughout the channelization process? (iv) Are variations in fish species composition and abundance associated with changes in environmental variables between channelized and unchannelized sites?

We hypothesize that channelization may lead to shifts in environmental conditions of streams and, consequently, in the structure and composition of fish assemblages, potentially favoring small-bodied and disturbance-tolerant species, while negatively affecting those more sensitive to habitat alteration. In addition, we predict that major impacts on fish fauna occur during the channelization phase, with a reduction in species richness and biomass, and an increase in the abundance of tolerant species due to streambed excavation and straightening. This approach is relevant for predicting the ecological consequences of similar stream modifications in other regions and conducting policy on biodiversity and planning of urban landscapes.

Material and methods

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Study area. In this study, we assessed two streams located in distinct river basins: the Iguaçu River basin and the Piquiri River basin. The Iguaçu River basin (Ecoregion 346) has a total drainage area of 55,180 km² and an extension of 1,320 km, covering 116 municipalities and elevations ranging from 136 m and 1,350 m above sea level (Feow, 2021; Parolin et al., 2010). Its springs are located on the western slope of the Serra do Mar, with its mouth seven kilometers downstream from Iguaçu Falls, flowing into the Paraná River. Geological events that occurred millions of years ago in the Pleistocene period resulted in the formation of several natural barriers, providing the basin with a high degree of endemism of fish species. According to Mezzaroba et al. (2021), the basin has a richness of 133 species, about 69% of which are endemic to this hydrographic network. The Piquiri River basin (Ecoregion 344) has a drainage area of 24,156 km², with altitudes ranging from 188 m to 1,180 m above sea level. It is the third-largest drainage area in Paraná (Parolin et al., 2010). Unlike the Iguaçu River basin, which is geographically isolated and has a high number of endemic species, the Piquiri River maintains greater connectivity with the Paraná River basin, with about 154 species recorded with low endemicity (Cavalli et al., 2018; Dos Reis et al., 2020).

The streams analyzed here are located in the urban area of ​​the municipality of Cascavel, in the western region of the state of Paraná. Cascavel is the fifth most populous city in the state, with 364,104 inhabitants according to the IBGE (2024). The region has a humid subtropical climate, characterized by hot and rainy summers and cool winters, with average temperatures ranging from 11.5 to 28.6°C and average annual rainfall of 205 mm and 179 mm (Hales, Petry, 2019). The landscape is divided into intensive agricultural surroundings, urban, and industrial areas.

The Coati Chico stream, part of the Iguaçu River basin, originates from groundwater emergence in the Santa Felicidade neighborhood, located in the southern part of the city, and flows through the urban area until it discharges into the Quati River. Stream sections contain patches of native riparian vegetation; however, exotic shrubs and grasses dominate in most of the study area. Additionally, there are nearby buildings, bank erosion, sediment deposition, and significant amounts of litter accumulating in the streambed and surrounding areas. The Amambay stream, which belongs to the Piquiri River basin, is formed by the confluence of three springs, all located within the urban perimeter of Cascavel in the Morumbi neighborhood. It exhibits a high degree of anthropogenic influence, with a narrow strip of exotic riparian vegetation at most sites, while native vegetation is only present in a small riparian strip at site 1 (upstream). The region has a humid subtropical climate, characterized by hot and rainy summers and cool winters, with average temperatures ranging from 11.5 to 28.6°C and average annual rainfall of 205 mm and 179 mm (Hales, Petry, 2019). The landscape is divided into intensive agricultural surroundings, urban, and industrial areas.

The study used the quasi-experimental design established by Block et al. (2001), which included phases before, during and after the channelization and was adapted to the specific characteristics of each stream and channelized reach (Tab. S1). Because these are different basins and therefore present different species compositions, this is the ideal scenario for the study objective, as the structural engineering design was the same for both locations, allowing comparisons in the degree of impact. Furthermore, the streams presented the same degree of anthropogenesis, meaning they are located in an urban context.

The entire channelization of Coati Chico stream was carried out over a stretch of approximately 500 meters. Within this stretch, two sampling points (S2 and S3) were included, which before the interventions were characterized by a backwater area and a predominance of gravel substrate (Fig. 1). Site 4 (S4), downstream, is not channelized but is directly affected by the proximity of a channelized passage under a road. Site 5 (S5) is also downstream and separated from S4 by a waterfall approximately 10 m high, which acts as a natural biogeographic barrier, likely preventing certain fish groups from moving upstream (Fig. 1; Tab. S1). The upstream sampling site 1 (S1) is also not channelized. The last three sampling sites, as well as S2 and S3 before channelization, were treated as unchannelized in the statistical analyses. For Amambay stream, channelization occurred along a 110-meter stretch. Sixty meters of this reach were designated as site 2 (Figs. 1–2), having been recently channelized (Fig. 2). Site S3 had already been channelized in 2018, extending beyond the sampled reach to approximately 890 meters downstream. Originally, site 3 presented a riffle and pool environment, with a substrate predominantly composed of pebbles, gravel, and sand/clay. Sites 1 and 4 are located upstream and downstream, respectively (Fig. 1). In all sampling phases, sites 1 and 4, as well as site 2 (before channelization), were treated as unchannelized, while S3 (before, during, and after channelization phases) and S2 (during and after) were considered channelized (Figs. 1–2; Tab. S1).

FIGURE 1| Study area in the context of the State of Paraná, Iguaçu and Piquiri River basins and sampling sites in the stretch of influence of Coati Chico (A) and Amambay streams (B), Cascavel, Paraná State, Brazil.

FIGURE 2| Sites that underwent the channelization process and their respective phases in Coati Chico and Amambay streams. W = width; D = depth; F = flow; S = substrate. 

Samplings

Environmental variables. To evaluate the influence of environmental conditions on the spatial-temporal dynamics of the fish assemblage, a set of hydrological, physicochemical, and habitat variables was measured. For this, in each 60-meter sampling site, seven transects perpendicular to stream flow and equidistant at 10 m from each other were determined. The first transect started at 0 m (start of the sampling stretch), the second at 10 m, the third at 20 m, and so on until the seventh transect at 60 m (end of the sampling stretch). In each transect, the following physical and chemical variables of the water were measured: water temperature (°C), pH, conductivity (µS/cm-1), dissolved oxygen (mg/L), oxygen saturation (%), total dissolved solids (g/L) and turbidity (NTU) using the multiparameter probe (Horiba®). Furthermore, the channel width (m) at each transect was measured using a tape measure, and three depth measurements (cm) were taken at the left, middle, and right bank. The water flow was estimated in each transect using the average current speed, calculated as the displacement time of a floating object. The flow was then estimated in m/s by dividing the distance of 1 meter travelled by the object by its average time of displacement, calculated from five throws.

To quantify the habitat structures, the 60-meter sampling sites were divided into three subsections (0–20 m; 21–40 m; 41–60 m). Visual inspections were conducted at each subsection, and quantitative evaluation of the bottom substrate followed the classification of Gordon et al. (1992) for natural continuous substrate, boulders (> 80 mm in diameter), cobbles (80–25 mm), gravel (25–5 mm), and sand/clay. The following substrates were also quantified: artificial material (concrete blocks, tires, tiles, trash), artificial substrate (channelization), organic structures (branches, leaves, trunks, and macroalgae), and macrophytes, totaling overall a percentage of 100% for each sampling site. Furthermore, the percentage of shade over the stream channel was quantified. The occurrence of different mesohabitats (runs, riffles, and pools) was recorded.

Fish assemblages. Three fish and environment samplings were conducted during three phases: one before channelization (May 2023), one during channelization (January 2024), and the last one six months after channelization (October 2024 for Amambay stream and December 2024 for Coati Chico stream) (Tab. S1). The fish were sampled using the electrofishing method. This procedure used equipment consisting of a portable alternating current generator (220V, 50–60Hz, 3.4–4.1 A, 100W), connected to two electrodes by a flexible multifilament cable 60 m long. The capture electrode itself is a circular net with an aluminum frame and a net bag (1.5 mm mesh). Both are connected to the main cable by a 1.5 mm diameter conductive wire. A 60-meter stretch of each sampling site was delimited, and two passes of the electrodes were conducted in a downstream-upstream direction, each pass lasting approximately 40 min.

After capture, the fish were placed in plastic bags, euthanized, and fixed in 4% formalin. The identification of the species was carried out following the taxonomic keys and phylogenetic reviews presented by Dias, Zawadzki (2018), Ota et al. (2018) and Neves et al. (2020) for the Piquiri River basin and Dos Reis et al. (2021), Larentis et al. (2019), Garavello, Shibatta (2016), Rosso et al. (2016) Baumgartner et al. (2012), Garavello et al. (2012), Garavello, Sampaio (2010) for the Iguaçu River basin. For Cichlidae, the taxonomic classification and nomenclature followed Fricke et al. (2025) and Betancur-R. et al. (2017). Voucher specimens of all species examined were deposited in the fish collection at LIEB (Laboratório de Ictiologia e Ecologia e Biomonitoramento), Universidade Estadual do Oeste do Paraná, Cascavel, Paraná (uncatalogued specimens), and NUP (Coleção ictiológica do Núcleo de Pesquisas em Limnologia, Ictiologia e Aqüicultura – Nupélia), Universidade Estadual de Maringá, Maringá, Paraná.

Data analysis. To characterize the sampling sites and identify variations in physical-chemical variables and habitat structures between channelized and unchannelized sections, two separate matrices of environmental variables were constructed. The matrix of environmental variables was standardized in two ways. In the first matrix, three transects were established for each site as spatial replicates, and the mean values ​​of the physical-chemical variables were calculated from these replicates (T1, T2, and T3; T4 and T5; T6 and T7). Habitat structures were measured only at three fixed transects per site, and therefore, mean values were not calculated for these variables. In the second matrix, the coefficient of variation [(standard deviation/mean) × 100] was calculated for each site, considering all sampled transects — seven transects for physical-chemical variables and three transects for hydrological and habitat variables.

Principal Component Analysis (PCA) was used to reduce data dimensionality and identify patterns in the variation of environmental variables among sampling sites, using the “pca” function of the “FactoMiner” package. The data matrix consisted of water physical-chemical variables and habitat characteristics, considering three transects per site. Before the analyses, water physical-chemicals were standardized (mean zero and standard deviation one), and habitat characteristics were transformed using the robust centered log-ratio (rCLR) approach to account for their compositional nature. The decomposition of eigenvalues and eigenvectors was performed from the covariance matrix, and the first two principal components (PC1 and PC2) were used to interpret the variation patterns. The contribution of each variable to the principal components was analyzed based on the eigenvector coefficients, considering the significant variables with the axes with p-value < 0.05. The visualization of the sample groups was performed using a biplot (function “fviz_pca_biplot” of the “factoextra” package), which allowed for the interpretation of the relationships between the sampled sites and the environmental variables.

To assess the difference in environmental variables between the channelization effect and the sampling sites, a Permutational Multivariate Analysis of Variance (PERMANOVA; Anderson, 2001) was applied using the Euclidean dissimilarity matrix. PERMANOVA was conducted using the “adonis2” function of the “vegan” package, employing an additive model without interaction between factors due to the imbalance in factor levels. To verify whether the differences detected by PERMANOVA could be attributed to differences in the multivariate dispersion of the groups, a Multivariate Dispersion Analysis (PERMDISP) was performed. Dispersion was assessed from the distances to the centroid of each group in the dissimilarity matrix, using the “betadisper” function of the “vegan” package. The associated permutation test was applied with 999 permutations.

Species richness was estimated using the rarefaction method based on the Krebs (1989) algorithm. This method is appropriate since species richness can increase in direct proportion to the number of individuals sampled. The rarefied richness graphic was visually compared between before, during, and after channelization phases for each site and stream.

To assess the degree of environmental disturbance of the assemblage, ABC curves were constructed for each period and site, based on fish abundance and biomass data, using the k-dominance plot approach (Lambshead et al., 1983), and the index proposed by Meire, Dereu (1990). If the biomass curve is consistently above the individual curve, the result will be positive, characterizing an undisturbed assemblage. In contrast, a negative value suggests a disturbed assemblage. Overlapping curves produce a value close to zero and imply moderate environmental stress (Dias, Tejerina-Garro, 2010; Oliveira, Tejerina-Garro, 2010).

To assess differences in the composition of fish assemblages between the channelization effect and the sampling sites, a PERMANOVA was applied using the Bray-Curtis dissimilarity matrix. The matrix was constructed from the numerical abundance data of the standardized species using the Hellinger method, with 999 permutations. The dispersion of the groups was also evaluated through PERMDISP.

To investigate the relationship between environmental variables and fish assemblage composition, a Distance-Based Redundancy Analysis (db-RDA; Legendre, Anderson, 1999) was performed using the Bray-Curtis dissimilarity matrix from the numerical abundance data of the species, with Hellinger transformation. Initially, a progressive selection of variables (forward selection) was applied, using the “forward.sel” function of the “adespatial” package, to identify an optimal subset of environmental variables that significantly explain the variation in the composition of the assemblages, reducing redundancy and the risk of overfitting the model. The db-RDA was conducted using the “capscale” function of the “vegan” package, considering only the selected variables. The significance of the global model and the canonical axes was tested employing restricted permutations (999 permutations) with the “anova.cca” function of the “vegan” package. The contribution of fish species to db-RDA was calculated using the “envfit” function (Oksanen et al., 2015), with 999 permutations. The interpretation of the results was based on the percentage of variance explained by the first canonical axes and on the analysis of the scores of the environmental variables, represented graphically in a triplot. All statistical analyses were performed in R software, using the “vegan” and “adespatial” packages.

To assess a general pattern of the channelization effect on fish assemblage attributes (total abundance, total biomass, species richness, and ABC curve index), linear models with Gaussian distribution and identity link function were adjusted, considering environmental variables, the channelization effect, and streams as predictor variables. The interaction of categorical variables was considered in the models. All environmental variables were standardized (mean = 0, standard deviation = 1) to facilitate the interpretation of coefficients and ensure comparability between predictors. To select the most parsimonious model, the Akaike Information Criterion was applied, using the stepwise elimination procedure based on AIC minimization. The process was performed using the “stepAIC” function of the “MASS” package, which allows for the inclusion and exclusion of variables to optimize model fit. The quality of the final model adjustments was assessed by analyzing the residuals, verifying normality and homoscedasticity through standardized residual plots. In addition, the significance of the predictors was tested using the “Anova” function of the “car” package, considering a significance level of 5% (α = 0.05). All data analyses and graphs were conducted in R software.

Results​

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Environmental variables. The analysis of environmental variables from the Principal Component Analysis (PCA) revealed that the first two component axes explained 38.73% of the total variance of the data for Coati Chico stream, with the first axis (PC1) responsible for 21.17% of the variance and the second (PC2) for 17.56% (Figs. 3A–B). The PC1 axis showed a strong positive correlation with the variables gravel (0.88), sand/clay (0.64), dissolved oxygen (0.48), flow (0.45), depth (0.41), continuous natural substrate (0.33), and a negative correlation with artificial material (-0.68), artificial substrate (-0.55) and boulders (-0.55). The PC2 axis was mainly influenced by the positive correlation with the variables shade (0.72), boulders (0.69), depth (0.47), conductivity (0.46), pH (0.40), artificial material (0.38), dissolved oxygen (0.32), and a negative correlation with artificial substrate (-0.71), orp (-0.52), and macrophyte (-0.45). The PERMANOVA indicated significant differences for the effect factor (channelized and unchannelized; Pseudo-F_(1.44) = 8.45; p = 0.001) and sampling sites (Pseudo-F_(3.44) = 4.44; p = 0.001) for the environmental variables of Coati Chico stream. The PERMIDISP indicated homogeneity in the dispersion of the data for both factors.

FIGURE 3| Principal Component Analysis (PCA) based on Euclidean distance matrices of environmental variables: A–B. Coati Chico stream (A. Effect factor; B. Sampling sites); C–D. Amambay stream (C. Effect factor; D. Sampling sites).

For Amambay stream, the first two axes of the PCA explained a total significance of 44.84% for the data, with the first axis (PC1) responsible for explaining 30.12% of the variation, and the second axis (PC2) 14.72% (Figs. 3C–D). The PC1 axis showed a strong positive correlation with the variables depth (0.77), continuous natural substrate (0.68), shade (0.56), cobbles (0.50), gravel (0.49), flow (0.41), and a negative correlation with artificial substrate (-0.92), artificial material (-0.68), boulders (-0.64), width (-0.57). The PC2 axis was positively influenced by dissolved oxygen (0.65), sand/clay (0.65), flow (0.49), gravel (0.44), cobbles (0.36), and negatively by temperature (-0.76), continuous natural substrate (-0.48), and macrophyte (-0.35). The PERMANOVA indicated significant differences for the effect factor (channelized and unchannelized) (Pseudo-F_(1.35) = 12.17; p = 0.001) and sampling sites (Pseudo-F_(3.35) = 8.06; p = 0.001) for the environmental variables of Amambay stream. The PERMIDISP indicated homogeneity in the dispersion of data for both factors.

Fish assemblages. In total, 20,157 specimens distributed among 27 species were captured. In Coati Chico stream, 12 species were captured, belonging to 6 families and 4 orders (Tab. 1), with greater richness for Tricomycteridae (5 species), Loricariidae (2 species), and Heptapteridae (2 species). The remaining families were represented by only one species (Acestrorhamphidae, Cichlidae, and Poeciliidae). In Amambay stream, 15 species belonging to 9 families and 6 orders were captured (Tab. 2). The families with the greatest richness were Poeciliidae (3 species), Acestrorhamphidae, Erythrinidae and Cichlidae with 2 species. The remaining families were represented by only one species (Gymnotidae, Heptapteridae, Loricariidae, Synbranchidae). In addition, two non-native species were recorded, Poecilia reticulata Peters, 1859 for both streams and Xiphophorus hellerii Heckel, 1848 for Amambay stream. The other species were all native to the Piquiri and/or Iguaçu River basins, and none are listed as threatened (Tabs. 1–2).

TABLE 1 | List of species from Coati Chico stream for the three collections. Threat categories (TC) according to ICMBio (2018) and IUCN (2022). SO = species origin and status in the lower Piquiri River basin (N = native; NN = non-native); Nomenclature of threat categories according to the IUCN (International Union for Conservation of Nature and Natural Resources) Red List threat degrees: LC = Least Concern. *Species not yet described according to Dos Reis et al. (2020). NUP = deposit number in the scientific collection.

Taxa

SO

TC

Before

During

After

NUP

S1

S2

S3

S4

S5

S1

S2

S3

S4

S5

S1

S2

S3

S4

S5

CHARACIFORMES

Acestrorhamphidae

Psalidodon bifasciatus

N

LC

X

X

X

X

X

X

X

X

X

X

X

X

26075

SILURIFORMES

Heptapteridae

Rhamdia branneri

N

LC

X

X

X

X

26072

Rhamdia voulezi

N

LC

X

X

X

X

X

X

X

X

X

X

X

X

26071

Loricariidae

Ancistrus mullerae

N

LC

X

X

26074

Hypostomus derbyi

N

LC

X

X

X

26073

Trichomycteridae

Cambeva aff. davisi

N

LC

X

X

26081

Cambeva plumbea

N

LC

X

X

X

X

X

X

X

X

X

X

26080

Cambeva sp. 1*

N

_

X

X

X

X

X

26078

Cambeva sp. 2*

N

_

X

X

X

X

X

26077

Cambeva sp. 3*

N

_

X

X

X

X

X

X

X

X

X

X

26079

CICHLIFORMES

Cichlidae

Geophagus iporangensis

N

LC

X

26076

CYPRINODONTIFORMES

Poeciliidae

Poecilia reticulata

NN

_

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

26082

Total abundance

48

402

665

44

38

375

251

142

24

40

254

609

1714

114

50

TABLE 2 | List of species from Amambay stream for the three collections. Threat categories (TC) according to ICMBio (2018) and IUCN (2022). SO = species origin and status in the lower Piquiri River basin (N = native; NN = non-native); Nomenclature of threat categories according to the IUCN (International Union for Conservation of Nature and Natural Resources) Red List threat degrees: NA = Not Assessed; LC = Least Concern. *Species not yet described according to Dos Reis et al. (2020). NUP = deposit number in the scientific collection.

Taxa

SO

TC

Before

During

After

NUP

S1

S2

S3

S4

S1

S2

S3

S4

S1

S2

S3

S4

CHARACIFORMES

Acestrorhamphidae

Astyanax lacustris

N

LC

X

X

X

X

X

26069

Psalidodon aff. paranae

N

LC

X

X

26059

Psalidodon bifasciatus

N

LC

X

X

X

X

X

X

X

X

X

X

X

X

26061

Erythrinidae

Hoplias malabaricus

N

LC

X

X

X

26057

Hoplias argentinensis

N

LC

X

X

X

26067

GYMNOTIFORMES

Gymnotidae

Gymnotus inaequilabiatus

N

LC

X

26070

SILURIFORMES

Heptapteridae

Rhamdia quelen

N

LC

X

X

X

X

X

X

X

X

X

X

X

X

26064

Loricariidae

Hypostomus ancistroides

N

LC

X

X

X

26066

Trichomycteridae

Cambeva sp. 4*

N

NA

X

X

X

X

X

X

X

X

X

X

X

26063

SYNBRANCHIFORMES

Synbranchidae

Synbranchus marmoratus

N

LC

X

X

X

X

X

X

26068

CICHLIFORMES

Cichlidae

Cichlasoma paranaense

N

LC

X

X

26065

Geophagus iporangensis

N

LC

X

X

X

26058

CYPRINODONTIFORMES

Poeciliidae

Phalloceros circummontanus

N

LC

X

X

X

X

X

X

X

X

X

X

X

X

26062

Poecilia reticulata

NN

–

X

X

X

X

X

X

X

X

X

X

X

26056

Xiphophorus hellerii

NN

–

X

X

X

X

X

X

26060

Total abundance

57

941

1878

573

35

249

4234

832

50

231

3823

2376

The channelization significantly affected the richness and abundance of species in the stretches under intervention. Specimens of Cambeva were not recorded for this stretch or had their abundance drastically reduced (Tabs. 1–2). Site S5CC (downstream of the waterfall) (Tab. 1), was the only one that recorded the presence of Loricariidae.

The rarefaction analysis showed varying patterns for the expected species richness among the sampling sites (Fig. 4). Although an asymptote was not reached for most of the rarefaction curves, sites S1CC, S2CC, S3CC, S4CC and S2A (Figs. 4A–D, G) demonstrated higher richness before channelization with a reduction in expected richness during channelization, and increasing trends after channelization, especially for S3A (Fig. 4H) with higher expected richness than for the phase before channelization. Sites S5CC, S1A and S4A (Figs. 4E–F, I) showed higher expected richness during channelization.

FIGURE 4| Species rarefaction curves for each channelization phase and their respective sampling sites and phases using abundance (axis x) and richness (axis y). A-E. Coati Chico stream (CC) (A. S1; B. S2; C. S3; D. S4; E. S5); F-I. Amambay stream (A) (F. S1; G. S2; H. S3; I. S4). Black line: before channelization; Red line: during channelization; Blue line: after channelization.

Negative values of the ABC index demonstrate an increase in the individuals’ abundance with low biomass for the sites subjected to channelization (Fig. 5). The upstream sites (S1CC and S1A) and S5CC (downstream of the waterfall) presented positive values for the ABC index, showing an undisturbed fish assemblage, mainly for before channelization. However, the sites that were under channelization intervention (S2CC, S3CC, and S2A) presented negative values for the period before channelization, with accentuated values for the period during and after channelization. The downstream sites (S4CC, S5CC, S3A, and S4A) were also impacted by channelization, as demonstrated by the positive values found for before channelization, with subsequent inversion of the curves, obtaining values tending to zero or becoming negative for after channelization.

FIGURE 5| ABC curves for ranking/abundance and biomass. Black lines indicate abundance and gray lines indicate biomass. Coati Chico stream (CC) and Amambay stream (A).

The species composition of Coati Chico stream showed significant differences for the sampling sites (PERMANOVA, Pseudo-F_(1.14) = 3.59; p = 0.003), while in Amambay stream, the composition showed differences for the channelization effect (PERMANOVA; Pseudo-F_{(1.11 )}= 1.31; p = 0.27) and sampling sites (PERMANOVA; Pseudo-F_(3.11) = 6.05; p = 0.002).

Relationship between environmental variables and fish assemblages. The Distance-Based Redundancy Analysis (db-RDA) indicated that the composition of fish species was significantly related to the environmental variables, indicating distribution patterns for the channelized effect and the sampling sites. The db-RDA explained 88.68% of the variation in dissimilarities in species composition and effect for Coati Chico stream. The CAP 1 axis (73.64%; F = 21.80; p = 0.001) represented an environmental gradient mainly related to temperature and boulders, while the CAP 2 axis (15.04%; F = 4.45; p = 0.011) reflected variations associated with conductivity and organic structures. The unchannelized site (S5) was correlated with lower temperature, a higher number of boulders and organic structures, whereas the channelized sites (S2 and S3, during and after intervention) were strongly associated with higher temperatures and lower number of boulders (Figs. 6A–B). The species Ancistrus mullerae Pavanelli & Zawadzki, 2009 (p = 0.0127), Hypostomus derbyi (Haseman, 1911) (p = 0.0004), Psalidodon bifasciatus (Garavello & Sampaio, 2010) (p = 0.0001) Rhamdia branneri Haseman, 1911 (p = 0.0002), and Rhamdia voulezi Haseman, 1911 (p = 0.0001) were associated significantly with the db-RDA axes aligned with unchannelized sites, whereas P. reticulata (p = 0.0001) was associated with channelized sites (Figs. 6A–B; Tab. S2).

FIGURE 6| Distance-based Redundancy Analysis (db-RDA) explaining variation in species composition and environmental variables. A–B. Coati Chico stream (A. Effect factor; B. Sampling sites); C–D. Amambay stream (C. Effect factor; D. Sampling sites).

For Amambay stream, the db-RDA explained 100% of the variation in dissimilarities in species composition and effect (channelized and unchannelized). The CAP 1 axis (82.85%; F = 12.17; p = 0.001) represented an environmental gradient related mainly to boulders, while the CAP 2 axis (17.15%; F = 2.52; p = 0.045) reflected variations associated with dissolved oxygen. The unchannelized site (S1) was correlated with higher numbers of boulders, whereas the channelized sites (S2 and S3) were strongly associated with conditions of fewer boulders and dissolved oxygen (Figs. 6C–D). The species Cambeva sp. 4, P. bifasciatus and R. quelen were found in unchannelized sites, whereas Phalloceros circummontanus Souto-Santos, Mejia, Arcila & Buckup, 2025, P. reticulata, Synbranchus marmoratus Bloch, 1795, and X. helleri were associated with channelized sites in the db-RDA axes (Figs. 6C–D; Tab. S3).

Linear models revealed that species richness and the ABC index differed significantly regarding the channelized effect in both streams, with higher species richness and ABC index values observed at unchannelized sites. Abundance and biomass also differed significantly between streams, with lower abundance and higher biomass recorded in Coati Chico stream. However, the interaction between stream identity and channelized effect was not significant for any of the attributes evaluated, suggesting a consistent pattern of channelization across both streams. Total abundance showed a positive relationship with the ORP, width, gravel sediment, the presence of artificial substrates and shade, while it demonstrated a negative relationship with the temperature, and the proportion of cobbles. Total biomass was positively related to the proportion of gravel and shade. The species richness showed a positive relationship with the artificial substrate and macrophytes, and a negative relationship with the temperature and proportion of boulders. Finally, the ABC curve index revealed a positive relationship with the pH and a negative association with temperature and shade (Fig. 7; Tab. S4).

FIGURE 7| Coefficient estimates of the environmental variables from linear models for the response variables. A. Abundance; B. Biomass; C. Species richness; D. Index ABC.

Discussion​

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The results of our study demonstrate that channelization exerts strong pressure on pre-existing urban fish assemblages by altering physico-chemical and habitat conditions. Sites most directly impacted exhibited lower species richness, abundance, and biomass, along with an increase in the abundance of tolerant species after channelization, confirming our predictions. These findings are consistent with other studies that have shown that this type of intervention leads to a cumulative loss of heterogeneous instream habitats (Keller, 1978; Brooker, 1985; Shankman, Pugh, 1992; Lau et al., 2006; Lennox, Rasmussen, 2016; Miranda et al., 2023; Stowe et al., 2023). The cascading ecological effects observed here were mainly driven by altered hydrological conditions and reduced habitat availability, which strongly shaped assemblage structure across channelized sites, regardless of the basin analyzed.

Channelized sites exhibited simplification of environmental conditions, characterized mainly by reduced depth, increased flow rate, and loss of habitat heterogeneity. The reinforcement of riverbanks with gabions also diminished riparian vegetation and shade, leading to microclimatic alterations such as higher water temperature and lower dissolved oxygen. Such outcomes were expected, considering the intense substrate disturbance, deviation from the original course to facilitate the construction of the concrete structure, as well as the removal of material from the banks to the natural riverbed, caused by the operation of machinery during the channelization process (for more details, see Fig. 2). Thus, from the environmental disturbances caused, the entire aquatic ecosystem begins to be affected. These changes are consistent with previous studies indicating that channelization reduces environmental heterogeneity and acts as an ecological filter (Miranda et al., 2023), ultimately constraining species richness and favoring tolerant species (Lennox, Rasmussen, 2016). Fish species richness and composition in the studied streams followed the expected patterns for their respective basins, with higher richness in the Piquiri River basin and lower in the Iguaçu River (Baumgartner et al., 2012; Dos Reis et al., 2020; Larentis et al., 2021). However, channelization led to a marked loss of species, particularly affecting sensitive taxa such as Cambeva spp. and P. bifasciatus. The persistence of reduced richness even six months after the intervention suggests that short-term resilience of fish assemblages is limited under such intense habitat alteration. This is particularly concerning given that Cambeva species in the study area remain undescribed, highlighting the vulnerability of cryptic biodiversity in urban streams and reinforcing the risk of losing species before they are formally recognized.

Channelization effects were not restricted to directly modified sites but also extended upstream and downstream. In Coati Chico stream, species richness temporarily increased in nearby upstream and downstream sections during the intervention. However, it declined again during the phase after channelization. The same pattern was observed for Amambay stream. This pattern is likely related to the system’s disrupted hydrological connectivity and additional barriers created by infrastructure works, which reduced the free-roaming area and intensified habitat fragmentation. Overall, these patterns suggest that channelization can generate cascading effects throughout the stream network, with results varying according to the scale and configuration of the intervention (Ahmednur et al., 2024).

Concomitant with the loss of richness, channelization also affected fish assemblage in terms of abundance and biomass, as reflected by the ABC index. Several sites already presented negative ABC values before channelization, indicating pre-existing disturbances associated with urban contamination. These negative values, caused by the overlap of the abundance curve over the biomass curve, are consistent with dominance processes typically observed under strong anthropogenic pressures (Magurran, 1988; Peressin, Cetra, 2014; Santos et al., 2015; Mise et al., 2018). In our study, dominance was largely driven by the proliferation of poeciliids, particularly P. reticulata and P. circummontanus, which are recognized as opportunistic species thriving in disturbed urban streams (Carvalho et al., 2019; Garcia et al., 2021). Similar patterns involving other poeciliids, such as Cnesterodon decemmaculatus and Jenynsia lineata, have been commonly found in urban streams across southern South America (Benejam et al., 2016; Vidal et al., 2018; Paracampo et al., 2020; Bertora et al., 2024). In addition, the negative ABC values were intensified during channelization in Coati Chico stream, and after channelization in Amambay stream, reflecting immediate and medium-term effects on assemblage structure. For S2CC and S3CC, despite the indication of improved conditions experienced by the species during the interventions, this perception was masked, as richness experienced a sharp decline, influencing the ABC index results. Regarding S2A, the presence of downstream channelization (S3A) since 2018 and the proximity between the sites provided a longer period of accommodation, allowing this area to function as a dispersal source. These results highlight how restrictive environmental conditions of the channel can play a limiting role in colonization and succession processes, triggering long-term effects.

Notably, the dominance process observed in channelized sites can be attributed to changes in environmental variables. Water quality, physical structure, and habitat complexity were significantly correlated with fish assemblage composition, highlighting the divergence between channelized and unchannelized sites. Unchannelized sites exhibited greater habitat heterogeneity, characterized by the presence of boulders, woody debris, and organic substrates, often shaded by riparian vegetation. These structural features favored a more functionally diverse assemblage, including benthic detritivores and invertivores such as A. mullerae, H. derbyi, Rhamdia spp., and Cambeva spp., which are strongly dependent on rocky substrates and fast-flow habitats (Larentis et al., 2021; Delariva et al., 2018; Baldasso et al., 2019, 2024). In addition, species such as P. bifasciatus, which exploit backwaters and pools and feeds on allochthonous resources, were also abundant in these sites (Delariva, Neves, 2020). Overall, these findings emphasize that structural heterogeneity increases the availability of microhabitats, providing refuge, feeding areas, and breeding sites for different species (Hewitt et al., 2010; Stein et al., 2014; Ortega et al., 2018, 2021). Even when located in an urban environment, habitat diversity is directly related to high fish richness and abundance, supported by assemblages composed of multiple functional guilds, highlighting the ecological importance of habitat complexity in mitigating the impacts of urbanization (Moi et al., 2024).

In contrast, the channelized sites demonstrated opposite correlations with higher water temperatures, lower dissolved oxygen, and fewer boulders. This may be relevant considering the close interaction between high temperature and low dissolved oxygen concentration (Bernhardt et al., 2022; Zhi et al., 2023). Together, these two variables are the driving force behind metabolism, as they can affect fish physiology, growth, and fecundity (Fuller et al., 2022). The absence of mesohabitat types and natural substrates (i.e., rocks, cobbles, gravel, sand/clay), evidenced by the negative correlation with boulders in linear models, further highlights the structural simplification caused by channelization. Under these conditions, the assemblage was dominated by small and tolerant species such as X. helleri, P. reticulata (non-native) and P. circummontanus (native). Their viviparous reproduction, rapid life cycle, and high feeding plasticity allow them to persist in disturbed habitats, where other species are excluded (Carvalho et al., 2017; Cruz, Pompeu, 2020; Santos et al., 2023; Pessoa et al., 2025). Although channelization is an artificial structure with no ecological purpose related to aquatic biota, it may inadvertently function as a refuge for tolerant and invasive non-native species. In the absence of larger predators that would normally regulate their populations, these simplified stream fragments can provide safe habitats from which such species persist and potentially disperse to other disturbed river reaches (Boon et al., 2023).

Overall, the linear models corroborate convergent effects of channelization on fish assemblage attributes in both streams. Species richness was higher at upstream sites, where streambed structure remained unaltered despite reduced connectivity. Otherwise, species richness and the ABC index exhibited significant variations in response to channelization, while differences in fish abundance and biomass were observed between streams, likely reflecting disparities in the intensity and timing of channel modifications. Amambay stream, which has included a channelized section since 2018, showed a pattern of higher fish abundance but lower biomass compared to Coati Chico stream, a trend consistent with patterns commonly reported in impacted environments (Peressin, Cetra, 2014; Santos et al., 2015; Mise et al., 2018). Nonetheless, linear models also revealed increased richness at sites with a greater presence of artificial substrates. This result, although unexpected, can be explained by the greater richness observed at site S3 in Amambay stream.

Amambay stream, which has included a channelized section since 2018, showed a pattern of higher fish abundance but lower biomass compared to Coati Chico stream, a trend consistent with patterns commonly reported in impacted environments (Peressin, Cetra, 2014; Santos et al., 2015; Mise et al., 2018). Interestingly, linear models also revealed an increase in species richness at sites with a greater proportion of artificial substrates. This unexpected result is primarily driven by the comparatively high richness recorded at site S3 in Amambay stream. This section exhibited many erosive changes in the artificial substrate, representing a problem from the infrastructure perspective, but considering the ecological processes it provided greater heterogeneity and presence of microhabitats. Altogether, these peculiarities created favorable conditions for the recolonization by species with greater adaptive abilities at this site. Finally, the positive influence of artificial substrate and stream width on fish abundance appears to be associated with the channelization process, which transforms streams into wider and shallower systems (Lennox, Rasmussen, 2016; Stowe et al., 2023).

In summary, our results demonstrate the immediate and negative effects of channelization in the urban streams analyzed, corroborating the hypothesis that this intervention promotes significant changes in environmental variables and, consequently, in the composition and structure of fish assemblages (Fig. 8). The replacement of heterogeneous substrate by impermeable concrete and the exposure of the banks led to marked alterations in environmental conditions. Channelized sections were associated with reduced depth, increased width, and higher light incidence, which were then associated with temperature rise and oxygen depletion. Despite the differences in pre-existing species richness between the Iguaçu and Piquiri basins, the immediate effects of channelization were convergent for both streams, with a drastic reduction in richness and biomass, and an increase in abundance, especially during the channelization process. The most significant changes in composition reflected the loss of sensitive species and the dominance of small-sized and tolerant species, enhancing the impacts on an ichthyofauna that was already impoverished by urbanization. Nevertheless, our assessment was limited to a short temporal window after channelization and focused exclusively on fish assemblages, which constrains the detection of delayed ecological responses and excludes insights from other biological groups that could provide a more comprehensive view of community-level impacts.

FIGURE 8| Summary of the effect of channelization on environmental characteristics and fish assemblage. Red arrows indicate decreasing or negative effects on significant variables in the study area. Blue arrows indicate increasing significant variations in the study area that favors the dominance process.

Despite these limitations, we recognize that the impact of this infrastructure occurred similarly for both streams in the short term. However, the recolonization and recruitment processes at these sites may occur differently for both streams, as these ecological processes will occur according to the natural physical characteristics of each basin, as they depend on factors such as water connectivity for locomotion, good water quality parameters (such as temperature and dissolved oxygen), and carrying capacity for species to feed and reproduce. Therefore, we speculate that Coati Chico stream will experience the most impaired recolonization process and that recolonization there will likely occur more slowly, due to the presence of the waterfall downstream of the affected area, which naturally limits the upstream reaches for the arrival of new individuals. All these characteristics have direct implications for management. We recommend actions such as restoring riparian vegetation adjacent to the gabion structure and improving connectivity between channelized sites and other segments of the drainage network, which may favor recolonization by sensitive species. Future research should prioritize long-term monitoring programs to assess both the persistence of channelization impacts and the effectiveness of restoration efforts. Furthermore, comparative studies across diverse urban contexts, incorporating multiple biological groups, will provide a broader understanding of ecological responses to habitat alterations. Together, these approaches increase our ability to predict the ecological consequences of channelization and inform evidence-based urban planning strategies that will enable improved urban infrastructure development combined with aquatic biodiversity conservation.

Acknowledgments​

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We acknowledge the support of the Universidade Estadual do Oeste do Paraná (UNIOESTE), as well as the contributions of the LIEB-UNIOESTE (Laboratório de Ictiologia, Ecologia e Biomonitoramento) team for their assistance in fieldwork and laboratory analyses. Access and permits were provided by Cascavel City Hall.

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Authors

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Flavia Begnini¹, Luciano Lazzarini Wolff², Taise Miranda Lopes¹, Franco Teixeira-de-Mello³ and Rosilene Luciana Delariva^1,2,4

^[1]    Programa de Pós-Graduação em Conservação e Manejo de Recursos Naturais, Universidade Estadual do Oeste do Paraná, Campus Cascavel, Rua Universitária, 1619, 85819-110, Cascavel, PR, Brazil. (FB) flavia.begnini@gmail.com, (TML) taisemlopes@gmail.com.

^[2]    Laboratório de Ictiologia, Ecologia e Biomonitoramento (Lieb), Universidade Estadual do Oeste do Paraná, Campus Cascavel, Rua Universitária, 1619, 85819-110, Cascavel, PR, Brazil. (LLW) luciano.lazzarini.wolff@gmail.com.

^[3]    Departamento de Ecología y Gestión Ambiental, Universidad de la República, CURE Tacuarembó, 20100, Maldonado, Uruguay. (FTM) frantei@cure.edu.uy.

^[4]    Programa de Pós-Graduação em Biologia Comparada, Universidade Estadual de Maringá, Av. Colombo, 5790, PGB – Bloco G80, Sala 201, 87020-900, Maringá, PR, Brazil. (RLD) rosilene.delariva@unioeste.br (corresponding author).

Authors’ Contribution

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Flavia Begnini: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing-original draft.

Luciano Lazzarini Wolff: Conceptualization, Data curation, Methodology, Visualization, Writing-review and editing.

Taise Miranda Lopes: Data curation, Formal analysis, Methodology, Visualization, Writing-review and editing.

Franco Teixeira-de-Mello: Formal analysis, Methodology, Supervision, Validation, Visualization, Writing-review and editing.

Rosilene Luciana Delariva: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Validation, Visualization, Writing-review and editing.

Ethical Statement​

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Experiments were approved by the Ethics Committee for Animal Use in Experiments of the Universidade Estadual do Oeste do Paraná ethics protocol (CEUA n^o 14–22 and 08–24) and collection licenses of SISBIO #25039.

Competing Interests

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The author declares no competing interests.

Data availability statement

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The data supporting this study are available from UNIOESTE. Restrictions apply to the availability of these data, which were used under license for this study. Data are available from the authors upon reasonable request and with permission from RLD.

AI statement

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The authors did not use any AI-assisted technologies in the creation of this manuscript or its figures.

Funding

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This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001 – to FB and a postdoctoral scholarship to TML provided by the Araucária Foundation/SETI. Financial support was provided by Cascavel City Hall. FTM received funding from the Universidad de la República through Espacio Interdisciplinario, Comisión Sectorial de Investigación Científica (CSIC), PEDECIBA, and SNI.

Supplementary Material

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Supplementary material S1

Supplementary material S2

Supplementary material S3

Supplementary material S4

How to cite this article

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Begnini F, Wolff LL, Lopes TM, Teixeira de Mello F, Delariva RL. Immediate effects of channelization on fish assemblages in two urban tropical streams. Neotrop Ichthyol. 2025; 23(4):e250075. https://doi.org/10.1590/1982-0224-2025-0075

Copyright​

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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

© 2025 The Authors.

Diversity and Distributions Published by SBI

Accepted October 23, 2025

Submitted April 30, 2025

Epub February 2, 2026