Climate change affects the potential distribution of a Neotropical freshwater migratory fish

Beatriz Cristina de Paula de Souza¹, Luana Caroliny Possamai², Katia Yasuko Yofukuji³, Taise Miranda Lopes^2,4, Luiz Fernando Esser², José Hilário Delconte Ferreira⁵, Reginaldo Ré⁵, Weferson Júnio da Graça^2,6, Ana Francisca Gomes da Silva¹, Jefferson Matheus Barros Ozório⁷, Dayani Bailly^2,6 and Valéria Flávia Batista-Silva¹

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Associate Editor: Franco Teixeira de Mello

Section Editor: Fernando Pelicice

Editor-in-chief: José Birindelli

Abstract​

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Introduction​

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Climate change, driven by global warming, has been widely discussed in recent decades (Abbass et al.,2022; IPCC, 2023). The global average temperature has already increased by 1.1°C, and future projections are even more alarming, with expected increases ranging from 1.4°C to 4.4°C, depending on greenhouse gas emission levels (Nobre et al.,2019; IPCC, 2023). This thermal increase may cause considerable impacts on both terrestrial (Field et al.,2007; Sales et al.,2021; Bernardinis et al.,2023; IPCC, 2023) and aquatic ecosystems (Woodward et al.,2010; Lopes et al.,2017; Conceição et al.,2023; IPCC, 2023), affecting all levels of biological organization, from individuals to ecosystems (Woodward et al.,2010; Bellard et al., 2012). Among the main threats are local extinctions and the spatial redistribution of species (Cahill et al.,2013; Urban, 2015; Bailly et al., 2021; Sales et al.,2021).

Freshwater environments are among the most sensitive to the effects of climate change, and despite their importance, these environments are increasingly vulnerable to anthropogenic impacts, such as global warming and growing habitat fragmentation (Dudgeon, 2014). The rise in temperatures triggers several changes in the natural dynamics of freshwater systems, altering oxygen concentration, water temperature, pH, water flow, and the frequency and intensity of floods and droughts (Ficke et al., 2007; Döll, Zhang, 2010; Phillips et al.,2015). In this context of growing vulnerability, climate change is expected to affect fish, particularly migratory species (Ruaro et al., 2019; Bailly et al., 2021).

The life cycle of migratory species is strongly synchronized with the hydrological cycle, with the onset of rainfall acting as a trigger for shoal formation and the initiation of migrations, while flood peaks serve as stimuli for spawning (Suzuki et al., 2009; Bailly et al., 2008; Oliveira et al., 2015). Furthermore, gonadal development and oocyte maturation are regulated by factors such as temperature and photoperiod (Suzuki et al., 2009). Consequently, changes in these environmental variables imposed by climate change may compromise the reproduction of Neotropical migratory freshwater fishes. Aggravating this situation, the construction of dams for energy generation can negatively impact the life cycle of these organisms by hindering the upstream reproductive migrations of adults and the passive dispersal of eggs and larvae (Agostinho et al., 2008; Pelicice et al., 2014).

Among the migratory Neotropical fish species in the Paraná-Paraguay basin is Megaleporinus obtusidens (Valenciennes, 1837), commonly known as “piava” or “piapara” (Agostinho et al., 2003; Copatti, Amaral, 2009). Native to South America (Britski et al.,2012), M. obtusidens is widely distributed across the Uruguay, São Francisco, and Paraná-Paraguay River basins (Agostinho et al., 2003; Zaniboni-Filho, Schulz, 2003; Britski et al.,2012), but is considered a non-native species in the Iguaçu River sub-basin (Baumgartner et al., 2012; Reis et al., 2020). This migratory fish can reach up to 49.3 cm in length (Agostinho et al., 2003) and weigh up to 6 kg (Resende, 2003), characteristics that, combined with the quality of its meat, make it a species of high economic value. In the Paraná-Paraguay basin, it is one of the main targets of both commercial and sport fishing (Agostinho et al., 2007; Barletta et al., 2015). However, intense fishing pressure and habitat fragmentation, coupled with the increasing effects of climate change, represent serious threats to the dynamic of their populations, requiring special attention to the management and conservation actions for their habitats (Agostinho et al., 2007; Quirós et al., 2007; Peluso et al., 2022).

Given the rapid pace of environmental changes, understanding how species will respond to climate change is a central challenge for conservation management. Recent studies have increasingly applied Ecological Niche Models (ENMs) to freshwater environments, particularly for fish species, to assess how climate change and other anthropogenic drivers may alter their distributions. In riverine systems, ENMs have been used to evaluate the loss of suitable habitats (Lopes et al., 2017; Ruaro et al., 2019), the impacts of hydrological alterations such as dam construction (Peluso et al., 2022), and to identify potential climate refugia and priority areas for conservation (Bailly et al., 2021). These applications highlight the relevance of ENMs as tools not only for projecting future distributions but also for guiding management and conservation actions in freshwater ecosystems (Peterson et al., 2011; Brun et al., 2020). Therefore, the present study investigated the impacts of climate change on the potential distribution of M. obtusidens, a long-distance migratory species in the Paraná-Paraguay basin. Specifically, we examined its potential distribution under current climate conditions and future scenarios, considering both moderate and pessimistic greenhouse gas emission trajectories. We then performed spatial predictions to identify the main climate refuge areas for M. obtusidens and the climatic-environmental attributes associated with its current occurrence. Understanding the current and future potential distribution of M. obtusidens will provide valuable insights for developing effective conservation strategies for this species in the Paraná-Paraguay basin.

Material and methods

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Study area. The Paraná-Paraguay basin drains about 2,800,000 km² of South American territory. In addition tooccupying large parts of the Southwestern and Southeastern regions of Brazil, it covers parts of Argentina, eastern Bolivia, and Paraguay (Graça et al., 2024; Fig. 1). The basin is mainly formed by Paraná and Paraguay Rivers that supports a high biodiversity and distinct landscapes. The Paraná River, with a length of 4,695 km, is formed by the junction of the Grande and Paranaíba rivers, and flows through southern Brazil, Paraguay, and Argentina. It ranks among the top ten rivers globally in terms of water volume (Brea, Zucol, 2011; Abrial et al., 2021). In the upper reaches of the Paraná River, there is a large floodplain, a dynamic and highly heterogeneous ecosystem that plays an essential role in preserving the biodiversity of this basin (Thomaz et al., 2004). The Paraguay River, stretching 2,550 km, is the fifth largest waterway in South America, originating in the Serra dos Parecis and flowing into the right bank of the Paraná River (Resende, 2003). The upper Paraguay River flows through the Chaco-Pantanal biome, one of the largest continuous alluvial plains in the world, extending across regions of Brazil, Bolivia, and Paraguay. This region is widely recognized for its rich biodiversity, encompassing a mosaic of habitats including temporary and permanent lakes, alluvial forests, and seasonally inundated savannas (Paranhos-Filho et al., 2013).

FIGURE 1| Observed occurrence records of Megaleporinus obtusidens in the Paraná-Paraguay basin.

Occurrence data of the species. The georeferenced occurrence records of M. obtusidens in the Paraná-Paraguay basin were obtained through four databases: SpeciesLink (http://splink.cria.org.br), Global Biodiversity Information Facility (GBIF; http://www.gbif.org/), Base de Datos de Peces de Águas Continentales de Argentina (http://www.pecesargentina.com.ar/; Liotta et al., 2020), and Ictioplata Database (https://app.sedoo.fr/freshwaterfishdata/#/amazonfish; Jézéquel et al., 2020). Occurrence data were obtained from these databases up until September 2025. Additionally, occurrences from the literature were included by searching the Web of Science (Thomson Institute for Scientific Information, ISI; www.isiknowledge.com), Scopus (https://www.scopus.com/) and Google Scholar (https://www.googlescholar.com/), using the terms “Leporinus obtusidens” and “Megaleporinus obtusidens”, encompassing all historical and current taxonomic designations for the species. After compiling all these sources, a total of 1,267 georeferenced occurrence records were obtained. Only records from the native range of the species were considered. Records from introduced populations, such as those from the Iguaçu River basin, were excluded, since M. obtusidens is regarded as non-native in that basin (Baumgartner et al., 2012; Reis et al., 2020).

Subsequently, these occurrence records underwent a rigorous data cleaning process using the R package CoordinateCleaner (Zizka et al., 2019), which tested them against several potential spatial biases, including the coordinates of capital cities, country centroids, equal latitude and longitude, research institution locations, and invalid coordinates. We also excluded records outside the Paraná-Paraguay River basin, which could bias models by introducing different configurations of predictor variables that are not present in our study area. This allows us to make predictions based solely on the arrangements faced by the natural populations within the basin, since there is no migration or gene flow between Paraná-Paraguay and other basins where the species is currently found. After these steps, we tested different grid sizes and selected the 10 km resolution, which maximized record retention while maintaining adequate spatial detail (for more details, please see Seo et al., 2009). The cleaned dataset (941 occurrence records) was then mapped on a regular geographical grid, with a spatial resolution of 10 km, comprising 15,617 cells, covering the river network in the Paraná-Paraguay basin. After this process, 209 occurrence records of M. obtusidens remained (Fig. 1). The grid was constructed in EPSG 6933, an equivalent spatial reference system that maintains a constant area.

Bioclimatic and hydrological variables. The distribution of the species was modeled as a function of bioclimatic and hydrological variables covering the Paraná-Paraguay basin. Present bioclimatic variables (1970–2000; representing 30 years temporal average) and future variables (2050 and 2090) were extracted from the WorldClim 2.1 database (http://www.worldclim.org/; Fick, Hijmans, 2017), with 2.5 arc minutes of spatial resolution. Future climate scenarios and general circulation models available in WorldClim were provided by the Intergovernmental Panel on Climate Change, Sixth Assessment Report (IPCC-AR6; https://www.ipcc.ch/assessment-report/ar6/) considering the new Coupled Model Inter‐comparison Project phase 6 (CMIP6). CMIP6 aims to better understand climate changes arising from natural, unforced variability or in response to changes in radiative forcing in a multi-model context (Eyring et al.,2016). Thus, for future forecasts, we used two Shared Socio-economic Pathways (SSPs), moderate (SSP2–4.5) and pessimistic (SSP5–8.5). The SSPs not only consider carbon emission scenarios but also socioeconomic factors that might change in the next few years, such as population size, education, economic growth, development of new technologies, and urbanization (Riahi et al., 2017). Two atmospheric-ocean general circulation models (AOGCMs) were used: CNRM-CM6-1-HR (Centre National de Recherches Météorologiques) and INM-CM4-8 (Institute of Numerical Mathematics). The Global Circulation Models (GCM) selection was made based on the chooseGCM package (Esser et al., 2025).

After filtering bioclimatic variables by excluding those with higher chance of environmental discontinuities (Booth, 2022), we kept 11 bioclimatic variables available in WorldClim with potential causation effect on species occurrence. We also used seven hydrological variables obtained from HydroSHEDS database (https://www.hydrosheds.org/products/hydrorivers; Lehner, Grill, 2013) aiming for variables with causation effect on species occurrence (Tab. 1). Bioclimatic and hydrological variables were rescaled using a 10 km geographical grid to obtain the climatic-environmental layers for both present and future times. Hydrological variables were considered temporally stationary for future forecasts.

TABLE 1 | Bioclimatic and hydrological variables used in the predictor selection for the ecological niche modeling of Megaleporinus obtusidens in the Paraná-Paraguay basin.

Variable	Description	Source
BIO1	Annual Mean Temperature	WorldClim
BIO2	Mean Diurnal Range	WorldClim
BIO3	Isothermality	WorldClim
BIO4	Temperature Seasonality	WorldClim
BIO5	Max Temperature of Warmest Month	WorldClim
BIO6	Min Temperature of Coldest Month	WorldClim
BIO7	Temperature Annual Range	WorldClim
BIO12	Annual Precipitation	WorldClim
BIO13	Precipitation of Wettest Month	WorldClim
BIO14	Precipitation of Driest Month	WorldClim
BIO15	Precipitation Seasonality	WorldClim
LENGTH_KM	Length of the river reach segment (km)	HydroSHEDS
DIST_DN_KM	Distance from the most downstream pixel of the reach, to the final downstream location along the river network (km)	HydroSHEDS
DIST_UP_KM	Distance from the most downstream pixel of the reach, to the most upstream location along the river network (km)	HydroSHEDS
CATCH_KM	Area of the catchment that contributes directly to the individual reach (km²)	HydroSHEDS
UPLAND_KM	Total upstream area (km²) calculated from the headwaters to the most downstream pixel of the river reach	HydroSHEDS
DIS_AV_CMS	Average long-term discharge estimate for river reach (m³/s)	HydroSHEDS
ORD_STRA	Indicator of river order following the Strahler (1957) ordering system	HydroSHEDS

The Variance Inflation Factor (VIF) was used to evaluate multicollinearity problems in our set of variables. Using the usdm package in R (Naimi, Araújo, 2016), variables were examined for pairwise linear correlations, and in each interaction, the variable exhibiting the highest VIF was excluded. The procedure continued until all variable pairs fell below the collinearity threshold (here 0.5). Thus, the following variables were kept: BIO2, BIO5, BIO14, DIST_DN_KM, CATCH_KM and ORD_STRA (Tab. 2).

TABLE 2 | Variance Inflation Factor (VIF) values for the predictor variables retained in the ecological niche modeling of Megaleporinus obtusidens. All pairwise correlations were below the collinearity threshold (r < 0.5).

Variables	VIF
BIO2	1.3334
BIO5	1.1601
BIO14	1.0348
DIST_DN_KM	1.3035
CATCH_KM	1.3497
ORD_STRA	1.4435

Generation of pseudo-absence data. We generated pseudo-absences to contrast environmental information and allow the use of machine learning-based algorithms. We randomly obtained n pseudo-absences within the study area, where n is equal to the number of occurrence records of the species (209). This procedure was necessary to avoid imbalance issues (Japkowicz, Stephen, 2002). We built a machine learning approach to obtain occurrence probabilities using algorithms that perform their functions using pseudo-absence data, not background data (see Sillero, Barbosa, 2021). In order to build distinguishable pseudo-absences from true absences and avoid biases that rise with randomness, we randomly selected 10 sets of 209 pseudo-absences outside an environmental envelope generated with all occurrence records and selected predictor variables at these locations (Nix, 1986; Busby, 1991). This procedure guarantees that pseudo-absences are geographically and environmentally distinct from presences (see Lobo et al.,2006). Thus, a binary matrix of presence (1) and pseudo-absence (0) was created to serve as input for the niche models.

Species distribution modeling. Binary matrices representing the presence and pseudo-absence of M. obtusidens, and environmental layers corresponding to the set of non-collinear variables based on VIF results for the species were used to calibrate models. The different algorithms provide distinct predictions of the species distribution area, generating uncertainty about which model best represents the geographic distribution of the species (Diniz-Filho et al., 2009). To overcome this uncertainty and minimize errors, the ensemble forecasting approach was used since it provides a consensus projection among multiple algorithms (Araújo, New, 2007). By obtaining a consensus model, errors that affect each algorithm differently tend to cancel each other out, resulting in a reliable and moderate solution (Terribile et al., 2010). In this context, we used seven algorithms, as follows: Support Vector Machine with Radial Kernel (svmRadial), Random Forest (RF), General Linear Models (GLM), Multiple Discriminant Analysis (MDA), Neural Networks (NNET), K-Nearest Neighbors (KNN), and Naive Bayes (Naive_Bayes) to predict the environmental suitability and potential distribution of M. obtusidens in Paraná-Paraguay basin.

For each algorithm used, the M. obtusidens occurrence data (presences and pseudo-absences) were randomly divided into two datasets, one comprising 75% of the data for model calibration and the other with 25% for model evaluation. This process was repeated 10 times using a cross-validation system of subsampling K-folds, with K = 4 (totalizing 40 repetitions). The K-fold validation divides the data into K subsets of approximately equal size and adjusts the models K times. Each time a subset is used as test data, the remaining K-1 subsets are used as training data (Naimi, Araújo, 2016). Iterations of the cross-validation were held to each set of pseudo-absences. In each repetition, each algorithm was also submitted to an automated fine-tuning with a grid search pattern of size 10, and optimizing the Area Under the Receiver Operating Characteristic Curve (AUC) values. A total of 40 climatic-environmental suitability projections were generated for each algorithm. Each projection was then binarized into presence and absence data for every grid cell using the threshold that maximizes the sum of sensitivity and specificity (Liu et al., 2016). We summed the binary outputs, generating frequency outputs that represent comparable suitability among different models. Thus, for each cell, the comparable suitability (i.e., the frequency, referred to as climatic-environment suitability) was calculated, ranging between 0 and 1 (1 represents the most suitable conditions and 0 the least suitable). Climatic-environmental suitability was then converted in presence and absence to obtain the species distribution, where values higher than 0.5 represented presences, and values lower than or equal to 0.5 represented absences.

The predictive performance, for each algorithm, was evaluated using the Receiver Operating Characteristic (ROC) method, which generates a curve in a bivariate space by plotting the true positive rate (sensitivity) against the false positive rate (1 – true negative rate or 1 – specificity). The AUC was calculated as a measure of the predictive performance of models, independent of the decision threshold (Manel et al., 2001; Liu et al., 2005). AUC values of 0.5 indicate models that perform no better than random selection, while values close to 1 indicate good performance with higher true-positive rates and lower false-positive rates. Models with AUC > 0.9 were combined to obtain a consensus prediction (Araújo, New, 2007). To do that, we used the majority consensus rule (adapted from Diniz-Filho et al., 2009) to obtain the consensus models, considering species presence only in cells where more than 50% of the ENMs retained in the ensemble indicated the species as being present. The climatic-environmental suitability of the consensus model was obtained by averaging the climatic-environmental suitability of the models retained in the consensus. The modeling protocol produced a total of 28,000 projections for the current time (7 algorithms x 40 repetitions x 10 fine-tuning iterations x 10 pseudoabsence datasets) and a total of 224,000 projections for the future time (7 algorithms x 40 repetitions x 2 climate models x 2 SSPs x 2 future times x 10 fine-tuning iterations x 10 pseudoabsence datasets).

The importance of variables was assessed through a “filter” method, where the models are built with and without a given variable. The change in AUC is used as a metric of variable importance: if the value does not change, the variable has minimum influence on the model. Calibration, testing, fine-tuning and ensembling were performed in caretSDM R package (https://github.com/luizesser/caretSDM). Maps were produced using QGIS v. 3.40.1.

To identify potential areas within the Paraná-Paraguay basin where M. obtusidens may gain, lose, or maintain its potential distribution in the future, we used the results of the consensus model of presence-absence. The current distribution of the species was then compared with projections for 2050 and 2090 under moderate and pessimistic climate scenarios. By overlaying these maps, the areas were classified into four categories: (1) stable, where the species remains present across projections; (2) susceptible to loss, where the species is currently present but is predicted to contract its potential range in the future; (3) susceptible to gain, where the species may expand its distribution to currently unoccupied areas; and (4) unsuitable areas, where conditions remain unsuitable in both the present and future.

Results​

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The models retained for the consensus (AUC > 0.9), included MDA, Naive Bayes, RF, and svmRadial, demonstrated high predictive performance for the occurrence of M. obtusidens in the Paraná-Paraguay basin (mean AUC of 0.96 ± 0.03). The environmental-climatic suitability gradients, generated by the consensus model, indicated that nearly half of the area of the Paraná-Paraguay basin offers favorable conditions for the occurrence of M. obtusidens currently. Extensive and contiguous regions of the Paraná River basin were predicted as suitable for the species, favoring its wide distribution throughout the basin. The main channel of the Paraná River, across nearly its entire length, along with the tributaries of its upper and lower stretches showed the highest environmental-climatic suitability. In contrast, in the Paraguay River basin, high environmental suitability was restricted to the large tributaries of the upper region, mainly in the Pantanal floodplain, and in the tributaries on the left bank of the lower Paraguay River, configuring a fragmented distribution pattern amidst predominantly unfavorable conditions (Figs. 2A–B).

FIGURE 2| Environmental-climatic suitability (A) and presence (red) / absence (gray) (B) estimated for Megaleporinus obtusidens in the Paraná-Paraguay basin for the present. Estimates are based on the results of the consensus models. Suitability values equal to 1 correspond to ideal environmental conditions and values equal to 0 correspond to suboptimum environmental conditions.

The environmental variables that most contributed to explaining the distribution of M. obtusidens in the Paraná-Paraguay basin were the mean diurnal temperature range (BIO2) and stream order (ORD_STRA) (Fig. 3). The analysis of partial dependence curves revealed that the probability of species occurrence increases in areas with a daily temperature range between approximately 9.8°C and 12.2°C, and in rivers of 4th order or higher (Fig. 4).

FIGURE 3| Relative importance of bioclimatic and hydrological variables for the current distribution of Megaleporinus obtusidens.

FIGURE 4| Response curves of variables used in the ecological niche modeling of Megaleporinus obtusidens in the Paraná-Paraguay basin. Values in parentheses indicate the relative importance of each variable.

Overall, future projections indicated a reduction in climatically suitable areas for M. obtusidens in the Paraná-Paraguay basin. By 2050, under a moderate scenario, a decrease in climatic suitability is expected, especially in the tributaries of the Upper Paraguay River, while suitable areas are projected to persist in the Lower Paraguay River and in most tributaries of the upper and lower stretches of the Paraná River (Fig. 5A). However, under the pessimistic scenario, the extent of these suitable areas is expected to decline, particularly in the tributaries located on the right bank of the upper Paraná River (Fig. 5B). For 2090, the moderate scenario follows the same trend for 2050, with a progressive decline in suitable areas but persistence of relatively favorable conditions along major tributaries of the Paraná River (Fig. 5C). In contrast, under the pessimistic scenario, a considerable reduction in climatically suitable areas is projected, limiting the favorable regions for M. obtusidens to a few segments of left-bank tributaries of the upper Paraná River and to small isolated patches in the southern portion of the basin (Fig. 5D).

FIGURE 5| Environmental-climatic suitability estimated for Megaleporinus obtusidens in the Paraná-Paraguay basin under future scenarios: A–B for 2050, and C–D for 2090, under moderate (SSP2–4.5) and pessimistic (SSP5–8.5) emission scenarios, respectively. Estimates are based on the results of the consensus models. Suitability values equal to 1 correspond to ideal environmental conditions and values equal to 0 correspond to suboptimum environmental conditions.

The potential distribution of M. obtusidens in the Paraná-Paraguay basin projected for 2050 under the moderate scenario indicates a loss of 38.1% of the currently suitable areas. Nevertheless, the lower stretches of the Paraguay River and extensive regions of the Paraná River basin are expected to serve as an important climatic refuge for the species (Fig. 6A). In the pessimistic scenario, a reduction of 46.9% of these areas is projected, especially in the tributaries of the upper Paraná River (Fig. 6B). The decrease in suitable areas becomes even more pronounced by 2090, both in the moderate (63.6%) (Fig. 6C) and, more intensively, in the pessimistic scenario (88.0%) (Fig. 6D) resulting in a greater contraction in the potential distribution of M. obtusidens.

In the pessimistic scenario for 2090, climate refugia are restricted to reduced stretches of the upper reaches of the left-bank tributaries of the upper Paraná River (Piquiri, Ivaí, Paranapanema, Tietê, Grande, and Paranaíba rivers), and to segments of the main channel of the Paraná river in its lower reach (Fig. 6D). Overall, the losses in suitable cells due to climate change greatly outweigh the gains, which are mainly limited to the upper stretches of tributaries of the upper Paraná River (Figs. 6A–D).

FIGURE 6| Predicted stable (blue), gain (green), loss (red) and unsuitable (grey) areas for Megaleporinus obtusidens in the Paraná-Paraguay: A–B for 2050, and C–D for 2090, under moderate (SSP2–4.5) and pessimistic (SSP5–8.5) emission scenarios, respectively. Estimates are based on the results of the consensus models.

Discussion​

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In this study, we highlight that the eastern portion of the Paraná-Paraguay basin along the main river axis exhibits a broad gradient of environmental climatic suitability, favoring a wide potential distribution of M. obtusidens in the present day. This species is recognized as a long-distance migratory fish, a characteristic that allows for a wider home range (Griffiths, 2010). Tagging studies in the Uruguay River basin have shown that the species can swim more than 500 km in a few days (Espinach Ros, 1999). In the Paraná-Paraguay basin, similar movements along the main rivers channel promote the dispersal of early life stages and the maintenance of adults, which supports the wide distribution observed in this study. Similar results were observed for other long-distance migratory fish in the region, such as the “curimba” (Prochilodus lineatus) (Agostinho et al., 1993) and the “dourado” (Salminus brasiliensis) (Ruaro et al., 2019). These movement patterns indicate that hydrological connectivity and the preservation of the integrity of these habitats are essential for the maintenance of M. obtusidens in the basin.

The distribution for M. obtusidens in the Paraná-Paraguay basin was largely explained by river order and thermal amplitude. Larger rivers (7th to 9th order), which provided greater water volume, habitat heterogeneity, and hydrological stability (Vannote et al., 1980; Ward, 1998; Zeiringer et al., 2018), showed the highest probabilities of species occurrence. These conditions favor feeding, shelter, and reproduction, as corroborated by the predominance of “piava” in the main channels of medium- to large-sized rivers channels (Palmuti et al., 2021). Consequently, maintaining longitudinal connectivity is critical for the maintenance of M. obtusidens populations, given their reproductive migratory behavior. Disruptions caused by dams and other anthropogenic barriers may fragment populations, reduce gene flow, and compromise the long-term viability (Carvajal-Quintero et al., 2019; Valenzuela-Aguayo et al., 2020). Nonetheless, it is important to mention that the importance of stream order may become even more prominent if projections that consider the influence of future climate and land use scenarios on this variable are available.

As ectothermic organisms, fish are sensitive to temperature variations (Vliet et al., 2013; Jonsson, 2023) that directly influence physiological processes such as reproduction, feeding, growth, and sensory sensitivity (Ficke et al., 2007; Wysocki et al., 2009; Li et al., 2022). In the case of M. obtusidens, experiments with juveniles showed that growth is optimized at temperatures between 26 °C and 30 °C, while lower temperatures reduce metabolic activity and higher temperatures, although they increase food consumption, do not promote significant growth (Piana et al., 2003). In our study, the most suitable areas for the species exhibited daily thermal amplitudes between 9.8°C and 12.2°C, suggesting that this range provides favorable conditions for development. Beyond its direct physiological implications, daily thermal amplitude may also serve as an indicator of environmental stability. Large fluctuations impose additional metabolic costs on ectothermic organisms, reducing the energy available for growth and reproduction (Ficke et al., 2007; Pörtner, Farrell, 2008), whereas intermediate ranges favor more stable habitats that are particularly important for migratory species such as M. obtusidens (Comte, Olden, 2017). As a result, these thermal conditions represent an essential component for the persistence of the species in the basin, especially under future climate change scenarios, which could alter the temperature ranges in areas currently suitable for its occurrence.

It is important to recognize that climatically suitable areas are not the only factor that supports the presence of M. obtusidens, as hydrology plays a decisive role in shaping its distribution. In this context, the restricted occurrence of the species in portions of the Paraná-Paraguay basin, particularly in the Chaco region (including northern Argentina and western Paraguay), likely reflects the structure of local drainage networks rather than climatic limitations. These regions, characterized by high thermal amplitude and more arid conditions, are dominated by intermittent or poorly connected river systems (Drago et al., 2008) that function as hydrological barriers and restrict the occurrence of the species even where climatic conditions remain favorable. For long-distance migratory fishes that depend on high-order rivers and prolonged flood pulses for reproduction (Agostinho et al., 2004), such landscapes become unsuitable, reinforcing the role of hydrological connectivity in determining species persistence and movement across the basin. In addition, future climate change may further alter hydrological regimes in the basin, potentially intensifying these constraints.

Despite this strong hydrological component, it is also important to consider that, in other areas of the basin, the absence of records may be related to sampling gaps rather than true absence. Regions of central and northern Argentina, particularly the Pilcomayo, Bermejo, and Salado rivers, as well as western Paraguay and the Bolivian portion of the Paraguay River, are widely recognized as under-sampled for freshwater fishes due to low population density, limited accessibility, and the lack of long-term monitoring programs in the Gran Chaco (Hablützel, Huanto, 2020). Historical ichthyological surveys from central Argentina provide additional support for this interpretation (Casciotta et al., 1989). Thus, the spatial distribution of available records may reflect this uneven sampling effort, which represents an inherent limitation of regional biodiversity databases including that of the present study.

Future projections indicate a concerning scenario for M. obtusidens across the basin, with losses of climatically suitable areas in nearly all regions that currently provide favorable conditions for the species. This trend has already been observed in previous studies, which warned about the impacts of these changes on M. obtusidens populations in the Paraná-Paraguay basin (Bailly et al., 2021; Peluso et al., 2022). These projected losses are particularly alarming because M. obtusidens as an omnivorous species, positioned at an intermediate trophic level, plays an important role in tropical freshwater ecosystems, influencing trophic interactions and contributing to nutrient cycling (Andrian et al., 1994; Vanni, 2002; Hahn et al., 2004). In addition, omnivorous fish contribute to the balance of zooplankton and phytoplankton communities, as well as in the biological control of invasive bivalves (Vadeboncoeur et al., 2005; Rosa et al., 2014; Salazar-Torres et al., 2015). These multiple ecological interactions illustrate not only the functional importance of M. obtusidens in the environment, but also highlight that biotic interactions contribute to shaping species distributions, influencing patterns of occurrence and local persistence.

While abiotic factors are traditionally considered the dominant drivers of species distribution at macroecological scales, considering biotic interactions can refine predictions of species responses to environmental changes, and may explain potential differences between modeled and observed distributions. Thus, the loss of suitable areas may, therefore, compromise the trophic dynamics and functionality of aquatic ecosystems in the Paraná-Paraguay basin, reinforcing the need for the conservation of M. obtusidens to ensure the maintenance of the basin’s ecological integrity.

Considering the importance of M. obtusidens for artisanal and recreational fishing (Barletta et al., 2010, 2015), the reduction of climatically suitable areas under future scenarios represents a significant loss of ecosystem services (e.g., provisioning and cultural), with potential economic impacts across various regions of the Paraná-Paraguay basin. One such region is the Paraguay River basin, which encompasses the “Pantanal”, a globally significant floodplain where fishing plays a crucial socio-economic role. In 2018, the average catch per unit of effort (CPUE) in this basin was estimated at 8,601 Kg per fisherman per day (6,606 Kg per fisherman per day in Mato Grosso and 14,685 Kg per fisherman per day in Mato Grosso do Sul) (ANA, 2020). Additionally, the total income of artisanal professional fishermen from the value of the first sale in the Paraguay River basin was estimated at R$ 69,820,920.29, with R$ 38,014,094.90 in Mato Grosso and R$ 31,788,825.39 in Mato Grosso do Sul (ANA, 2020).

Climate refugia can be defined as geographically stable areas where projected future climate conditions overlap with current or historical conditions, providing suitable habitats for the persistence of species in a climate change scenario (Keppel et al., 2012; Graham et al., 2019). The identification of these areas has become a key strategy for the management and conservation of species (Gavin et al., 2014; Sobral-Souza et al., 2018; Graham et al., 2019). In this context, our study showed that by mid-century, the areas of climate stability for M. obtusidens are expected to concentrate in the main channels of the Paraná and Paraguay Rivers, as well as in the tributaries of the Paraná River. However, by the end of the century, an expressive contraction of these areas is projected, resulting in the spatial fragmentation of refugia into small isolated segments of the Paraná-Paraguay basin, compromising the connectivity between essential habitats for the species.

The loss of climatic-environmental suitable connectivity between refugia regions may lead to the local extirpation of M. obtusidens across extensive portions of the basin, as the species undertakes long-distance migratory routes to complete its life cycle. Habitat fragmentation, intensified by the presence of numerous dams in the basin (Agostinho et al., 2008), further exacerbates this scenario in areas recognized as potential refugia, such as the Piquiri, Ivaí, Tietê, Paranapanema, Grande and Paranaíba rivers, which are left-bank tributaries of the Paraná-Paraguai basin draining the Serra do Mar and Serra da Mantiqueira. These barriers block migratory routes, restrict dispersal, and interrupt connectivity between spawning and recruitment areas (Mounic-Silva et al., 2019). Although the Ivaí and Piquiri rivers are currently dam-free climatic refuges, both have planned and inventoried hydroelectric plants (Affonso et al., 2015; ANEEL, 2019). The implementation of these projects represents an additional threat to the species’ survival, reinforcing the urgency of adopting effective conservation measures aimed at maintaining these climate refugia. It is further emphasized that the upper stretch of the Tietê River sub-basin is highly eutrophicated due to the discharge of domestic and industrial effluents (CETESB, 2023), a condition that exacerbates the threats to the species survival and further compromises the functionality of these refuges.

Paradoxically, climate change may also transform previously unsuitable areas into environmentally favorable habitats (see Williams, Jackson, 2007; Parmesan, Yohe, 2003). The ability of species to track these changes will depend on their ability to colonize new environments and establish viable populations. The speed of these processes will be decisive for the occupation of newly suitable environmental areas (Angert et al., 2011). In the case of M. obtusidens, although there is potential for a range expansion in the upper stretches of the left bank tributaries of the upper Paraná River, this process may be severely limited by habitat fragmentation, the absence of climate-environmental corridors (as discussed earlier), and by specific characteristics of the species’ life history.

In our study, climate projections indicated that the distribution of M. obtusidens in the Paraná-Paraguay basin will be severely affected by the end of this century, with potential negative consequences for the ecosystem services provided by this species. Mitigating these impacts requires long-term strategic conservation planning (Groves et al., 2012; Stein et al., 2014; Wang et al., 2024). However, studies show that the currently existing protected areas in the basin do not provide adequate protection for migratory species like M. obtusidens, a gap that is likely to worsen with the projected climate changes (Bailly et al., 2021). In light of this scenario, it becomes imperative to implement preventive measures, such as the preservation of free-flowing rivers, which maintain longitudinal connectivity, and protecting floodplains and wetlands, which safeguards lateral connectivity. These environments provide environmental stability, act as natural climate refugia, and serve as nurseries for the reproduction and juvenile development of M. obtusidens (Nakatani et al.,2004; Thomaz et al., 2007). Their inclusion in protected area systems is essential to ensure the integrity of their ecological characteristics, thereby promoting the resilience of aquatic ecosystems and the conservation of fish in the face of ongoing climate change.

Acknowledgments​

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The authors thank the Universidade Estadual de Mato Grosso do Sul (UEMS) for the physical and institutional infrastructure provided.

References​

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Authors

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Beatriz Cristina de Paula de Souza¹, Luana Caroliny Possamai², Katia Yasuko Yofukuji³, Taise Miranda Lopes^2,4, Luiz Fernando Esser², José Hilário Delconte Ferreira⁵, Reginaldo Ré⁵, Weferson Júnio da Graça^2,6, Ana Francisca Gomes da Silva¹, Jefferson Matheus Barros Ozório⁷, Dayani Bailly^2,6 and Valéria Flávia Batista-Silva¹

^[1]    Universidade Estadual de Mato Grosso do Sul (UEMS), Programa de Pós-Graduação em Biodiversidade e Sustentabilidade Ambiental (PGBSA), Grupo de Estudo em Ciências Ambientais e Educação (GEAMBE), BR-163, 235, 79980-000, Mundo Novo, MS, Brazil. (BCPS) beatrizarnhorn@gmail.com, (AFGS) ana.francisca@uems.br, (VFBS) vfb_silva@uems.br.

^[2]    Universidade Estadual de Maringá (UEM), Programa de Pós-Graduação em Ecologia de Ambientes Aquáticos Continentais (PEA), Av. Colombo, 5790, 87020-900, Maringá, PR, Brazil. (LCP) luanacarolinypossamai@gmail.com, (TML) taisemlopes@gmail.com, (LFE) luizesser@gmail.com, (WJG) weferson@nupelia.uem.br, (DB) dayanibailly@nupelia.uem.br (corresponding author).

^[3]    CIMO, LA SusTEC, Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253, Bragança, Portugal. (KYY) kayofukuji96@gmail.com.

^[4]    Universidade Estadual do Oeste do Paraná (UNIOESTE), Campus Cascavel, Programa de Pós-Graduação em Conservação e Manejo de Recursos Naturais, Rua Universitária, 1619, 85819-110, Cascavel, PR, Brazil.

^[5]    Universidade Tecnológica Federal do Paraná (UTFPR), Via Rosalina Maria dos Santos, 1233, 87301-899, Campo Mourão, PR, Brazil. (JHDF) jhdferreira@gmail.com, (RR) reginaldo@utfpr.edu.br.

^[6]    Universidade Estadual de Maringá (UEM), Núcleo de Pesquisas em Limnologia, Ictiologia e Aquicultura (Nupélia), Av. Colombo, 5790, 87020-900, Maringá, PR, Brazil.

^[7]    Universidade Estadual de Mato Grosso do Sul (UEMS), Cidade Universitária de Dourados, 79804-970, Dourados, MS, Brazil. (JMBO) ozorio.jmb@outlook.com.

Authors’ Contribution

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Beatriz Cristina de Paula de Souza: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing-original draft, Writing-review and editing.

Luana Caroliny Possamai: Formal analysis, Visualization, Writing-review and editing.

Katia Yasuko Yofukuji: Data curation, Visualization, Writing-review and editing.

Taise Miranda Lopes: Formal analysis, Writing-review and editing.

Luiz Fernando Esser: Methodology, Software, Writing-review and editing.

José Hilário Delconte Ferreira: Software, Writing-review and editing.

Reginaldo Ré: Software, Writing-review and editing.

Weferson Júnio da Graça: Data curation, Validation, Writing-review and editing.

Ana Francisca Gomes da Silva: Visualization, Writing-review and editing.

Jefferson Matheus Barros Ozório: Formal analysis, Writing-review and editing.

Dayani Bailly: Conceptualization, Data curation, Formal analysis, Methodology, Writing-review and editing.

Valéria Flávia Batista-Silva: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Supervision, Writing-original draft, Writing-review and editing.

Ethical Statement​

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This manuscript does not require approval from the Ethical Committee for Animal Use in Experiments, since the data were obtained from publicly available online databases.

Competing Interests

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The author declares no competing interests.

Data availability statement

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

AI statement

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ChatGPT (OpenAI) was used for English language editing. All outputs were reviewed and approved by the authors.

Funding

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This study was financed in part by the “Programa Institucional de Bolsas aos Alunos de Pós-Graduação” (PIBAP/UEMS – proc. 86891363000180/2024-1) which granted a master’s scholarship to BCPS, by the “Coordenação de Aperfeiçoamento de Pessoal de Nível Superior” (CAPES – proc. 88887.968266/2024-00) which granted a master’s scholarship to LCP, by the “Fundação de Ciência e Tecnologia” (FCT – MCTES/PIDDAC: CIMO, UIDB/00690/2020 and SusTEC – LA/P/0007/2020) which supported the postdoctoral fellowship of KYY, and by the “Fundação Araucária/SETI” which granted postdoctoral fellowships to LEF (proc. 683/2022) and TML (proc. 154/2021). WJG received funding from the “Conselho Nacional de Desenvolvimento Científico e Tecnológico” (CNPq – proc. 303571/2024-1) through the research productivity fellowship.

How to cite this article

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Souza BCP, Possamai LC, Yofukuji KY, Lopes TM, Esser LF, Ferreira JHD, Ré R, Graça WJ, Silva AFG, Ozório JMB, Bailly D, Batista-Silva VF. Climate change affects the potential distribution of a Neotropical freshwater migratory fish. Neotrop Ichthyol. 2026; 24(1):e250091. https://doi.org/10.1590/1982-0224-2025-0091

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 January 23, 2026

Submitted May 16, 2025

Epub April 27. 2026