Population genetics of three threatened catfish species in heterogeneous environments of the Cauca River, Colombia

Natalia Restrepo-Escobar^[1] , Anny Johanna Yepes-Acevedo^[1]  and Edna Judith Márquez^[1] 

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Abstract​

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Introduction​

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The Siluriformes order comprises 38 families, 15 of which are exclusively in Central and South America (Ferraris, 2007; Fricke et al., 2020). Six of these families encompass the 86% of the 2347 catfish valid species of Neotropical distribution (Ferraris, 2007; Fricke et al., 2020): Auchenipteridae (125), Callichthyidae (221), Heptapteridae (226), Loricariidae (1000), Pimelodidae (114), and Trichomycteridae (327). These species, known as catfishes, have commercial importance in different regions as nourish source, ornamental fishes or even sport fishing (Usma-Oviedo et al., 2009; Nelson et al., 2016).

Population genetic studies in Neotropical catfishes are centered in members of commercial interest of Pimelodidae (17) family, and in lower proportion, of Loricariidae (6), Trichomycteridae (1), and Heptateridae (2) families. To the date, evidences for gene flow have been found in species that perform medium and large distance migrations during their lifecycle, such as Brachyplatystoma flavicans (Coronel et al., 2004), Brachyplatystoma rousseauxii (Batista, Alves-Gomes, 2006), Pimelodus maculatus (Almeida et al., 2001, 2003; Ramella et al., 2006; Ribolli et al., 2012), Pseudoplatystoma fasciatum (Coronel et al., 2004), Pseudoplatystoma magdalenatium (Gallo, Díaz-Sarmiento, 2003), Pseudoplatystoma corruscans (Dantas et al., 2013; Vaini et al., 2016; Prado et al., 2018),and Pseudoplatystoma reticulatum (Vaini et al., 2016; Prado et al., 2018).

Nevertheless, genetic structure of populations of some species has been found and it seems to be explained by various types of behaviors: (1) sedentarism and short-distance migration range in Steindachneridion parahybae (Fonseca et al., 2017), Trichogenes longipinnis (Zamudio et al., 2009), Iheringichthys labrosus, and Pimelodus cf. absconditus (Almeida et al., 2001); (2) fidelity to breeding or spawning sites (homing) in P. corruscans (Pereira et al.,2009), P. reticulatum (Abreu et al., 2009), and Rhamdia quelen (Ríos et al., 2019), and (3) presence of natural or artificial geographical barriers in P. maculatus in Paranapanema River (Almeida et al., 2003), P. corruscans in Paraná River (Sekine et al., 2002), and between Paraná and São Francisco rivers (Carvalho et al., 2012), and P. corruscans and P. reticulatum in Paraná and Paraguay rivers (Prado et al., 2018).

Contrary to the majority of population genetics studies in Amazonas and Paraná basins, very few have been performed in Colombian basins, most of which are found in grey literature (see Mancera-Rodríguez et al., 2013; Márquez et al., 2020). For the remaining freshwater catfishes in northwestern South America, there is still unawareness of genetic diversity, demography and population structure which limits the implementation of effective rules for their management and protection.

The latter is important since populations of these species have been affected by overfishing and other indirect effects of anthropogenic activities like mining, dam construction, gravel sand extraction, basins contamination and continuous water extraction for agricultural and livestock purposes, which have led to the decay and decrease of the populations of said species in all Colombian basins (Galvis, Mojica, 2007; Usma-Oviedo et al., 2009; Barletta et al., 2010; Jiménez-Segura et al., 2016).

To contrast the hypothesis that threatened fish populations show genetic vulnerability signs in Cauca River sections exposed to anthropic activities, three catfish species were chosen, with differences in their standard length, migration range and reproductive strategies. Ageneiosus pardalis Lütken, 1874, is a medium size species (standard length between 12.83–42.98 cm; Ribeiro et al., 2017), with short-distance migration range (< 100 km), marked sexual dimorphism (Dahl, 1971; Mojica et al., 2012a), elaborated courtship and copulation (Galvis et al., 1997) and distribution from south Panamá to north Venezuela; Pimelodus grosskopfii Steindachner, 1879, is a small size species (standard length between 10.17–32.12 cm; Villa-Navarro et al., 2017), with medium migration range (100–500 km), external reproduction, endemic of the Magdalena-Cauca Colombian basin (Mojica et al., 2006; Ortega-Lara et al., 2006), and Sorubim cuspicaudus Littmann, Burr & Nass, 2000, a medium size species (can reach lengths greater than 80 cm; Littmann et al., 2000), with medium-distance migration range (100-500 km), external reproduction and distribution in the rivers Catatumbo (Ortega-Lara et al., 2012), Magdalena (Mojica et al., 2006; Villa-Navarro et al., 2006), Sinú and Cauca (Littmann et al., 2000) in northwestern South America.

The appointed species are a good model for population genetics analysis since they are exposed to anthropic interventions such as loss of habitats, deforestation, river-course fragmentation, introduction of exotic fish species, contamination and overfishing (Barletta et al., 2010; FAO, 2015; Jiménez-Segura et al., 2016; AUNAP, 2020). The decreasing population density of the three species led to their classification as vulnerable in the Colombian red list of freshwater fishes (Mojica et al., 2012b). Additionally, due to this decline in populations, P. grosskopfii was included as a critically endangered threatened species in the red list of threatened species of the International Union for Conservation of Nature – IUCN (Villa-Navarro et al., 2016). Thus, the a priori expectation was that the species showed high values of inbreeding and recent bottlenecks, as they are exposed to different anthropic interventions that might affect the density of their populations.

Moreover, the studied area comprises the middle and lower sections of the Cauca River, which includes near 500 km of the main channel of the river, 110 km of torrents and 40.000 ha of swamps. This area also includes the Cauca River canyon, the steepest margin of the Antioqueño Plateau in the northern portion of the Central Cordillera (Restrepo-Moreno et al., 2009), which has been considered a geographic barrier for many fish species (Dahl, 1971). Additionally, this area presents differences in habitats, water speeds, temperatures and it constitutes the influence zone of the Ituango hydroelectric project. In this context, this study also tested the hypothesis that populations of these species, collected before the beginning of the construction of the hydroelectric, were genetically structured. The a priori expectation was that the environmental heterogeneity of the zone caused genetic structuration. The answer to these queries generates information of interest to propose rules of management and conservation, suitable for the preservation of natural populations of these fish species.

Material and methods

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A total of 492 preserved in alcohol muscle tissues of A. pardalis (193), P. grosskopfii (170), and S. cuspicaudus (129) were analyzed. Said tissues were provided by Integral S.A through the scientific cooperation agreement CT–2013–002443, framed in the environmental license of Ministerio de Ambiente, Vivienda y Desarrollo Territorial # 0155 of January 30^th, 2009. Samples were collected between 2011–2014 in the middle (sections S1–S4) and lower (sections S5–S8) sections of the Cauca River, located upstream (S1) and downstream (S2–S8) of the construction zone of Ituango hydroelectric project (Fig. 1; Tab. 1). The middle section of the Cauca River encompasses the Cauca River canyon, characterized by a steep topography with the presence of rapid zones (S1–S3) followed by a vast alluvial plain surrounded by mountains, with swamp ecosystems connected with the main river channel (S4). The section S5 includes the mouth of the Nechí River, a hydrologically monomodal river prone to flooding and scouring, and the remaining lower section (S6–S8) shows soft topography with flat and wavy surfaces wherein several swamps connected to rivers through canals are formed, conforming complex swampy systems (Mejía-Rivera et al., 2007; Betancur-Vargas et al., 2009).

DNA extraction was performed with the commercial kit PureLink® Genomic DNA (ThermoFisher Scientific), following the instructions of the manufacturer. PCR conditions previously described by Landínez-García, Marquez (2016, 2018) were employed to amplify between 13 and 20 microsatellite loci for A. pardalis (Apar03, Apar04, Apar05, Apar11, Apar12, Apar14, Apar18, Apar19, Apar20, Apar21, Apar22, Apar23, Apar25, Apar27, Apar28, Apar30, Apar32, Apar34, Apar35, Apar36); P. grosskopfii (Pgrk01, Pgrk02, Pgrk03, Pgrk08, Pgrk10, Pgrk14, Pgrk15, Pgrk19, Pgrk24, Pgrk27, Pgrk28, Pgrk31, Pgrk40), and S. cuspicaudus (Scus03, Scus10, Scus12, Scus15, Scus16, Scus17, Scus18, Scus20, Scus21, Scus22, Scus23, Scus24, Scus25, Scus28, Scus32, Scus35, Scus39, Scus40, Scus41; Restrepo-Escobar, Marquez, 2020). PCR products were separated in an automatic sequencer ABI 3130 (Applied Biosystems, USA) using GeneScan-500 LIZ dye size standard (Applied Biosystems, USA) as internal marker and the allelic fragments were denoted according to their molecular size and scored using GeneMapper (Applied Biosystems, USA). Before the statistical analysis, the Micro-Checker v2.2.1 software (Van Oosterhout et al., 2004) was used to detect possible genotyping errors.

FIGURE 1 | Location of sampling sites of Pimelodus grosskopfii, Sorubim cuspicaudus,and Ageneiosus pardalis in the middle and lower sections of the Cauca River.

TABLE 1 | Number of individuals of Pimelodus grosskopfii, Sorubim cuspicaudus,and Ageneiosus pardalis analyzed in the middle and lower basin of the Cauca River. S1–S4: Middle section of the Cauca River, S1 and S2–S4 are located upstream and downstream of the construction zone of the dam, respectively. S5–S8: Lower section of the Cauca River.

Sections	P. grosskopfii	S. cuspicaudus	A. pardalis
S1	44	–	–
S2/S3	25	19	–
S4	18	22	–
S5	26	43	45
S6	35	25	84
S7/S8	22	20	64
Total	170	129	193

 

For samples of each studied section and genetic group, it was determined the genetic diversity calculating the expected and observed heterozygosities and the average number of alleles per locus with GenAlex v6.502 software (Peakall, Smouse, 2012). Additionally, the Arlequin v3.5.2.2 software (Excoffier, Lischer, 2010) was employed to test departures of the Hardy-Weinberg equilibrium, linkage equilibrium and calculate the inbreeding coefficient (F_IS) by population. In multiple comparisons, the statistical significance was adjusted by the Bonferroni sequential correction (Rice, 1989). Finally, two tests were used to determine whether the populations of these species have suffered a recent genetic bottleneck, the one-tailed test of Wilcoxon (Luikart, Cornuet, 1998), and M ratio of Garza, Williamson (2001) calculated respectively in Bottleneck v1.2.02 software (Piry et al., 1999) and the Arlequin v3.5.2.2. program (Excoffier, Lischer, 2010).

To determine the number of possible genetic groups for A. pardalis, P. grosskopfii,and S. cuspicaudus in the middle and lower basins of the Cauca River, it was used different complementary approaches. The Bayesian clustering method with STRUCTURE v2.3.4 software (Pritchard et al., 2000) used the following conditions: 100000 MCM, 10000 burn-in, admixture model, correlated allele frequency, and LOCPRIOR option. Simulations were repeated 20 times per each number of evaluated probable populations: 1–6 for A. pardalis, 1–8 for S. cuspicaudus, and 1–9 for P. grosskopfii. The most probable number of population was calculated using the ∆K method (Evanno et al., 2005) and the estimators MedMedK, MedMeaK, MaxMedK, and MaxMeaK (Puechmaille, 2016) with the web-based software STRUCTURESELECTOR (Li, Liu, 2018). The STRUCTURE results were summarized using the integrated software CLUMPAK (Kopelman et al., 2015) to generate a graphical representation of the results. Wherein STRUCTURE detected different genetic groups, the allocation of each individual to each group was determined by the coancestry coefficient from the Q-matrix generated by CLUMPAK (Kopelman et al., 2015) from the 20 simulations produced by STRUCTURE. Moreover, the genetic differentiation of each of the species among sectors of the Cauca River was calculated with the Analysis of Molecular Variance AMOVA and the standardized estimators F’_ST (Meirmans, 2006) and Jost’s Dest (Meirmans, Hedrick, 2011) using the GenAlex v6.502 software (Peakall, Smouse, 2012), and a Discriminant Analysis of Principal Components (DAPC) was performed using the package adegenet (Jombart, 2008) for R v3.4.0 program (R Development Core Team, 2017).

Results​

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The sampling performed by Integral S.A. between 2011–2014 revealed that A. pardalis, P. grosskopfii, and S. cuspicaudus were differentially distributed in the middle and lower sections of the Cauca River. Namely, and despite having the same migration range, P. grosskopfii was found in all sampled sites, including upstream of the Cauca River canyon, whereas S. cuspicaudus was found in the downstream area of Cauca River canyon and the construction zone of the dam (S3–S8). In contrast, short-distance migration range A. pardalis was only captured in the lower basin of the river (S5–S8; Tab. 1).

Genetic diversity and population demographics. Pimelodus grosskopfii showed similar or nearly similar genetic diversity values in all evaluated sections (Na=10.308–13.308; He=0.849–0.866; Ho=0.607–0.682) and in the genetic groups proposed by the genetic structure analysis described below (Na=12.846–16.615; He=0.858–0.866; Ho=0.614–0.664; Tab. 2), further to statistical significance in heterozygosity deficit and inbreeding coefficients (F_IS=0.108–0.218; P<0.000; Tab. 2).

Likewise, S. cuspicaudus exhibited similar values of genetic diversity within the analyzed sections (Na=8.105–9.368; He=0.771–0.785; Ho=0.745–0.795; Tab. 2); however, in this case the genotypic frequencies behaved according to Hardy-Weinberg equilibrium except from S5 wherein the heterozygosity deficit was significant. Moreover, the inbreeding coefficient was significant in S5 (F_IS=0.045; P=0.026) and S8 (F_IS=0.058; P=0.032; Tab. 2).

In accordance with the other two species, A. pardalis showed similar genetic diversity values (Na=10.850–12.550; He=0.832–0.839; Ho=0.791–0.822; Tab. 2); statistical significance in heterozygosity deficits and coefficients of inbreeding in all the evaluated samples (F_IS=0.026–0.086; P<0.007) although in lesser magnitude than in P. grosskopfii (Tab. 2).

TABLE 2 | Genetic diversity, M-ratio estimator and bottleneck for populations and genetic groups of Pimelodus grosskopfii, Sorubim cuspicaudus,and Ageneiosus pardalis in the middle and lower sections of the Cauca River. N: Number of analyzed individuals, Na: Average number of alleles/locus, Ho: Observed heterozygosity, He: Expected heterozygosity, P: statistical significance of Hardy-Weinberg equilibrium; F_IS: inbreeding coefficient, M-ratio: M estimator of Garza, Williamson (2001), IAM: infinite alleles model, TPM: two phase model, SMM: stepwise model. Values in bold denote statistical significance.

	N	Na	Ho	He	P	FIS	M-ratio	IAM	TPM	SMM
Pimelodus grosskopfii
S1	44	13.308±1.184	0.682±0.020	0.863±0.015	0.000	0.147	0.217±0.049	0.000	0.003	0.342
S2/S3	25	11.615±0.675	0.679±0.062	0.860±0.012	0.000	0.157	0.224±0.057	0.000	0.000	0.317
S4	18	10.308±0.728	0.660±0.068	0.852±0.013	0.000	0.178	0.197±0.054	0.000	0.000	0.064
S5	26	12.462±0.991	0.618±0.061	0.866±0.011	0.000	0.177	0.201±0.058	0.000	0.001	0.527
S6	35	12.385±0.984	0.607±0.051	0.855±0.014	0.000	0.186	0.215±0.045	0.000	0.000	0.847
S7/S8	22	11.538±1.029	0.666±0.055	0.849±0.017	0.000	0.109	0.227±0.048	0.000	0.040	0.526
Genetic group 1	64	12.846±1.061	0.614±0.050	0.858±0.017	0.000	0.218	0.225±0.061	0.000	0.000	0.987
Genetic group 2	106	16.615±1.583	0.664±0.050	0.866±0.011	0.000	0.108	0.212±0.046	0.000	0.000	0.936
Sorubim cuspicaudus
S3	19	8.105±0.501	0.767±0.029	0.774±0.020	0.814	0.018	0.229±0.053	0.000	0.040	0.928
S4	22	8.316±0.536	0.788±0.023	0.771±0.024	0.352	-0.065	0.248±0.068	0.000	0.176	0.922
S5	43	9.368±0.613	0.745±0.028	0.783±0.020	0.000	0.045	0.258±0.049	0.000	0.020	0.973
S6	25	8.684±0.484	0.795±0.024	0.783±0.019	0.412	-0.045	0.254±0.063	0.000	0.129	0.916
S7/S8	20	8.263±0.561	0.745±0.028	0.785±0.017	0.124	0.058	0.257±0.055	0.001	0.078	0.675
Ageneiosus pardalis
S5	45	10.850±0.559	0.772±0.039	0.832±0.017	0.000	0.086	0.242±0.046	0.000	0.007	0.249
S6	84	12.550±0.755	0.791±0.027	0.839±0.015	0.000	0.060	0.240±0.042	0.000	0.002	0.607
S7/S8	64	11.950±0.630	0.822±0.021	0.839±0.014	0.000	0.026	0.245±0.043	0.000	0.000	0.892

 

The analysis for detecting bottleneck showed significant values for all the species in the evaluated sections under the IAM, while no significance was found under the SMM and the TPM showed significance in all or almost all of the evaluated sections in A. pardalis, P. grosskopfii (except S8), and S. cuspicaudus (except S4, S6, and S7/8). Additionally, the three species showed values of the M ratio of Garza, Williamson, (2001) lower than 0.680 (P. grosskopfii: 0.197–0.227; S. cuspicaudus: 0.229–0.258; A. pardalis: 0.242–0.245; Tab. 2), which has been proposed as limit value for inferring that the population has suffered a recent decline in population (Garza, Williamson, 2001).

Genetic structure analysis. In the distribution range of the evaluated samples in middle and lower sections of the Cauca River, the Bayesian analysis of STRUCTURE showed the homogeneous distribution of two coexisting genetic groups in P. grosskopfii (K=2; MedMedK=2; MedMeanK=2; MaxMedK=2; MaxMeanK=2; Fig. 2A), one genetic group in S. cuspicaudus, wherein each individual exhibits a similar genetic admixture of two biological groups (K=2; MedMedK=1; MedMeanK=1; MaxMedK=2; MaxMeanK=2; Fig. 2B), and one main genetic group with some genetic admixture in A. pardalis (∆K=2; MedMedK=1; MedMeanK=1; MaxMedK=1; MaxMeanK=1; Fig. 2C).

The homogeneous distribution of the genetic groups of P. grosskopfii (F_ST: 0.004, P: 0.075), S. cuspicaudus (F_ST: 0.003, P: 0.084) and A. pardalis (F_ST: 0.001, P: 0.066) in the middle and lower sections of the Cauca River was corroborated by AMOVA, the pairwise comparisons with standardized estimators F´_ST and Dest (Tab. 3), and DAPC (Figs. 2D-F).

FIGURE 2 | Population structure suggested by STRUCTURE (A–C) and the Discriminant Analysis of the Principal Components (D–F) for Pimelodus grosskopfii (A, D), Sorubim cuspicaudus (B, E),and Ageneiosus pardalis (C, F).

TABLE 3 | Statistical values F’_ST and Dest by pairs of the Pimelodus grosskopfii, Sorubim cuspicaudus,and Ageneiosus pardalis populations in middle and lower sections of the Cauca River.

	F’ST (P)	DST (P)
Pimelodus grosskopfii
S1–S2/S3	0.010 (0.502)	-0.004 (0.543)
S1–S4	0.013 (0.432)	-0.002 (0.504)
S1–S5	0.012 (0.095)	0.027 (0.098)
S1–S6	0.009 (0.276)	0.008 (0.284)
S1–S7/S8	0.013 (0.123)	0.027 (0.123)
S2/S3–S4	0.018 (0.332)	0.010 (0.332)
S2/S3–S5	0.012 (0.831)	-0.028 (0.829)
S2/S3–S6	0.013 (0.215)	0.019 (0.219)
S2/S3–S7/S8	0.018 (0.041)	0.055 (0.014)
S4–S5	0.015 (0.649)	-0.018 (0.666)
S4–S6	0.014 (0.635)	-0.013 (0.656)
S4–S7/S8	0.019 (0.169)	0.033 (0.177)
S5–S6	0.012 (0.361)	0.007 (0.352)
S5–S7/S8	0.017 (0.037)	0.052 (0.037)
S6–S7/S8	0.016 (0.037)	0.050 (0.036)
Sorubim cuspicaudus
S3–S4	0.015 (0.180)	0.014 (0.186)
S3–S5	0.010 (0.531)	-0.003 (0.555)
S3–S6	0.014 (0.208)	0.010 (0.217)
S3–S7/S8	0.012 (0.837)	-0.017 (0.838)
S4–S5	0.009 (0.562)	-0.002 (0.546)
S4–S6	0.012 (0.298)	0.007 (0.298)
S4–S7/S8	0.015 (0.146)	0.017 (0.150)
S5–S6	0.010 (0.159)	0.010 (0.159)
S5–S7/S8	0.009 (0.665)	-0.006 (0.679)
S6–S7/S8	0.011 (0.774)	-0.011 (0.785)
Ageneiosus pardalis
S5–S6	0.005 (0.615)	-0.003 (0.624)
S5–S7/S8	0.007 (0.120)	0.008 (0.127)
S6–S7/S8	0.005 (0.029)	0.011 (0.029)

 

Discussion​

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This study employed species-specific microsatellite loci to acknowledge the level of genetic diversity, demographic status and genetic structure degree of three species of Colombian endemic Neotropical catfishes that coexist in the middle and lower sections of the Cauca River basin. The a priori expectation was that the species showed high values of inbreeding and recent bottlenecks as they are subject of different anthropic interventions that might affect the density of their populations. Furthermore, it was expected a population genetic structure concordant with some heterogeneous features of the basin.

Genetic diversity and population demography. The three studied species showed higher levels of genetic diversity than the average values reported for Neotropical catfishes (Na=7.470, He=0.609; revision of Hilsdorf, Hallerman, 2017) although S. cuspicaudus showed lower diversity (Na=8.547, He=0.779) than A. pardalis (Na=11.783, He=0.835) and P. grosskopfii (Na=11.143, He=0.847).

The average expected heterozygosity values in the three species were higher than in other Neotropical catfishes such as T. longipinnis (He=0.393, Zamudio et al., 2009), S. parahybae (He=0.470, Fonseca et al., 2017), P. reticulatum (He=0.498–0.751, Abreu et al., 2009; Vaini et al., 2016; Prado et al., 2017), and P. corruscans (He=0.709–0.760, Pereira et al., 2009; Dantas et al., 2013; Vaini et al., 2016). Nonetheless, the genetic diversity observed in this study was lower than those found in R. quelen (He=0.614–0.909, Ríos et al., 2017; 2019), P. punctifer (He=0.783, Telles et al., 2014), P. corruscans (He=0.862, Prado et al., 2017), and P. maculatus (He=0.871, Ribolli et al., 2012).

In S. cuspicaudus, genotypic frequencies were distributed according to Hardy-Weinberg equilibrium and the inbreeding values were not significant save for sections S5 and S8 in which values lower than 10% suggest a careful management to prevent adverse effects regarding fitness (Frankham et al., 2014). On the contrary, and despite their high genetic diversity, A. pardalis and P. grosskopfii exhibited a heterozygosity deficit that cannot be explained by the Wahlund effect in the only genetic group formed by A. pardalis nor in each of the two genetic groups of P. grosskopfii that co-migrate in the studied area, wherein the heterozygosity deficit stayed significant.

Unlike P. grosskopfii, which has external reproduction (Loir et al., 1989), the assortative mating can explain the heterozygosity deficit in A. pardalis since it has internal insemination and elaborated courtships (Galvis et al., 1997) and the females store spermatozoa inside their ovaries (Contreras et al., 2012). However, to verify this hypothesis, it remains necessary to further research the reproductive behavior of these species.

Alternatively, the heterozygosity deficit could be explained by inbreeding as A. pardalis (2.600–8.600%) and P. grosskopfii (10.800–21.800%) showed significant F_IS values. This effect may result from different anthropic activities like overfishing due to diminishments in captures since 1994 (Jiménez-Segura,Villa-Navarro, 2011) and their presence in the first 10 species captured for the Magdalena-Cauca basin (AUNAP, 2020). Other factor that could negatively contribute to the studied catfish species is the contamination in basins caused by mining as in the studied zone there is gold, silver, and platinum extraction (UPME, 2019), and there is evidence of mercury bioaccumulation, a residual contaminant of this activity, in several species that cohabit in the zone (Marrugo-Negrete et al., 2008; Álvarez et al., 2012).

All those factors above mentioned may explain the recent decline in populations suggested by bottlenecks in the three studied species, supporting the hypothesis of genetic vulnerability of fishes due to anthropic interventions. A non-excluding alternative considers the climate factor as an additional influence of the demographic aspects of the populations of these species. Extreme changes in the Cauca River flow as consequences of the climatic phenomenon El niño–Southern Oscillation (ENSO) presented in the region in the prior years, wherein since 2007 there has been extreme NIÑA (2007–2008 and 2010–2011) and NIÑO (2009–2010, Hoyos et al., 2013) phenomena, could have caused bottlenecks as described in the same region for Curimata mivartii (Landínez-García, Marquez, 2018). This climate factor could contribute to bottlenecks phenomena associated to overfishing, which has been described for other Neotropical catfishes as P. corruscans, P. reticulatum,and B. flavicans (Coronel et al., 2004; Prado et al., 2018).

Genetic structure analysis. This study did not find significant differences among individuals of middle and lower sections of the Cauca River, which indicates that the environmental heterogeneity of the basin and, in particular, the steep slope of the Cauca River canyon is not a barrier for the gene flow of P. grosskopfii. However, such slope seems to limit of dispersion of S. cuspicaudus and A. pardalis in the middle section of the Cauca River since no individuals of these species were captured in the higher sections of the studied area in the sampled period (2011–2014). This result is not surprising for a short migrator like A. pardalis; nonetheless, the spatial distribution differed in the middle range migrators S. cuspicaudus and P. grosskopfii, suggesting that besides from their migration range, other factors as body conformation, habitat preferences and behavior, can play an important role in the observed spatial distribution, which is an important approach for future researches. A strong limitation to spatial distribution by the Cauca River canyon is also observed in Pseudopimelodus atricaudus, a new species described in the lower section of the Cauca River that diverged about 16 mya from its congener P. magnus distributed upstream the Cauca River canyon (Rangel-Medrano et al., 2020; Restrepo-Gómez et al., 2020).

In the spatial distribution analyzed for each species, the Bayesian analysis of STRUCTURE, the DAPC, the AMOVA and the pairwise distances showed absence of geographic population structure in the studied species. These results concord with the ones described for other Neotropical catfishes that perform medium and large distance migrations as P. maculatus (Almeida et al., 2001, 2003; Ribolli et al., 2012), B. flavicans (Coronel et al., 2004), B. rousseauxii (Batista, Alves-Gomes, 2006), P. corruscans and P. reticulatum (Vaini et al., 2016; Prado et al., 2018). Nevertheless, our results with A. pardalis and S. cuspicaudus contrast with the results for P. corruscans in the basin of rivers Paraguay and Paraná wherein the authors hypothesize a possible homing behavior for the species (Pereira et al., 2009; Dantas et al., 2013).

Distinct from A. pardalis and S. cuspicaudus, each formed by one genetic group, P. grosskopfii represented two coexisting genetic groups in the evaluated sections of the Cauca River. This result in P. grosskopfii could reflect a possible spatial reproductive isolation, considering the preference for reproductive sites (homing) described for other species of Pimelodidae family as B. rousseauxii (Batista, Alves-Gomes, 2006), P. corruscans (Pereira et al., 2009; Dantas et al., 2013), and P. reticulatum (Abreu et al., 2009). Another non-excluding alternative is that P. grosskopfii experiences temporary reproductive isolation as the Cauca River presents two hydrological periods of shallow and deep waters that could benefit two reproductive periods of the fish species that habit this basin (Jiménez-Segura et al., 2010; López-Casas et al., 2016). This explanation is supported in the observation of a greater number of individuals of P. grosskopfii participating in the migration during the first period compared to the second hydrological period of the Magdalena River (López-Casas et al., 2016). Despite the latter, to the date, there is no detailed information as per the reproductive periods and behaviors of P. grosskopfii that allows to elucidate the origin of the genetic groups.

Under this context, it is recommended that the information obtained in this study regarding the structure and diversity of three coexisting species of catfishes in the middle and lower sections of the Cauca River is considered within the expansion proposals of the hydroelectric development for Colombia (Angarita et al., 2018) and of other anthropic activities. The higher values of the inbreeding coefficient were found for P. grosskopfii, included in 2016 as a critical danger species in the red list of the International Union for Conservation of Nature – IUCN (Villa-Navarro et al., 2016), for which it is necessary to enforce the proposed measures for the recovery and conservation of natural populations of the species. Despite the inbreeding values found for S. cuspicaudus and A. pardalis are lower than 10%, which is the suggested limit to avoid substantial losses in the reproductive features (Soulé, 1980), it is advisable to continue monitoring these populations to evaluate the changes of the species over time since it has been indicated that inbreeding values higher than cero (F_IS>0) can cause negative effects in the fitness of natural populations (Frankham et al., 2014).

In conclusion, employing species-specific microsatellite loci, this study determined the diversity and possible genetic structure in the middle and lower sections of the Cauca River for the Neotropical catfishes A. pardalis, P. grosskopfii and S. cuspicaudus. The genetic diversity levels of the three species (expected heterozygosity and number of alleles/locus) are high; however, all the studied species seem to have suffered recent bottlenecks and exhibit significant inbreeding values, which are greater for P. grosskopfii, currently in a higher risk category. Furthermore, P. grosskopfii shows the coexistence of two genetic groups while A. pardalis and S. cuspicaudus are mainly represented by a genetic group. Contrary to the expectations, none of the evaluated species showed population structure related to some heterogeneous features of the basin. It was also evidenced that the cannon of the Cauca River in this zone does not represent a barrier to the gene flow of P. grosskopfii but it seems to limit the dispersion of A. pardalis and S. cuspicaudus.

Acknowledgments​

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This work was funded by the Universidad Nacional de Colombia, Sede Medellín and Empresas Públicas de Medellín, Grant CT–2013–002443–R1 “Variación genotípica y fenotípica de poblaciones de especies reófilas presentes en el área de influencia del proyecto hidroeléctrico Ituango”, Grant Convenio CT–2019–000661 “Variabilidad genética de un banco de peces de los sectores medio y bajo del Río Cauca”.

References​

---

Abreu MM, Pereira LHG, Vila VB, Foresti F, Oliveira C. Genetic variability of two populations of Pseudoplatystoma reticulatum from the Upper Paraguay River Basin. Genet Mol Biol. 2009; 32(4):868–73. https://doi.org/10.1590/S1415-47572009005000075

Almeida FS, Sodré LMK, Contel EPB. Population structure analysis of Pimelodus maculatus (Pisces, Siluriformes) from the Tietê and Paranapanema Rivers (Brazil). Genet Mol Biol. 2003; 26(3):301–05. https://doi.org/10.1590/S1415-47572003000300014

Almeida FS, Fungaro MHP, Sodré LMK. RAPD and isoenzyme analysis of genetic variability in three allied species of catfish (Siluriformes: Pimelodidae) from the Tibagi River, Brazil. J Zool. 2001; 253(1):113–20. https://doi.org/10.1017/S0952836901000103

Álvarez S, Jessick AM, Palacio JA, Kolok AS. Methylmercury concentrations in six fish species from two Colombian rivers. Bull Environ Contam Toxicol. 2012; 88:65–68. https://doi.org/10.1007/s00128-011-0458-x

Angarita H, Wickel AJ, Sieber J, Chavarro J, Maldonado-Ocampo JA, Herrera-R GA et al. Basin-scale impacts of hydropower development on the Mompós Depression wetlands, Colombia. Hydrol Earth Syst Sci. 2018; 22(5):2839–65. https://doi.org/10.5194/hess-22-2839-2018

Autoridad Nacional de Acuacultura y Pesca (AUNAP). SEPEC-Servicio Estadístico Pesquero Colombiano [Internet]. Bogotá; 2020. Available from: http://sepec.aunap.gov.co/

Barletta M, Jaureguizar AJ, Baigun C, Fontoura NF, Agostinho AA, Almeida-Val VMF et al. Fish and aquatic habitat conservation in South America: A continental overview with emphasis on Neotropical systems. J Fish Biol. 2010; 76(9):2118–76. https://doi.org/10.1111/j.1095-8649.2010.02684.x

Batista JDS, Alves-Gomes JA. Phylogeography of Brachyplatystoma rousseauxii (Siluriformes – Pimelodidae) in the Amazon Basin offers preliminary evidence for the first case of “homing” for an Amazonian migratory catfish. Genet Mol Res. 2006; 5(4):723–40. Available from: http://www.funpecrp.com.br/gmr/year2006/vol4-5/pdf/gmr0231.pdf

Betancur T, Mejía O, Palacio C. Conceptual hydrogeology model to Bajo Cauca antioqueño: a tropical aquifer system. Rev Fac Ing Univ Antioquia. 2009; 48(1):107–18.

Carvalho DC, Oliveira DAA, Beheregaray LB, Torres RA. Hidden genetic diversity and distinct evolutionarily significant units in an commercially important Neotropical apex predator, the catfish Pseudoplatystoma corruscans. Conserv Genet. 2012; 13:1671–75. https://doi.org/10.1007/s10592-012-0402-6

Contreras-C P, Zapata-B B, Rosado-P R. Aspectos preliminares del manejo reproductivo en cautiverio de la doncella (Ageneiosus pardalis Lütken, 1874). Rev MVZ Cordoba. 2012; 17(3):3147–53. Available from: http://www.scielo.org.co/pdf/mvz/v17n3/v17n3a08.pdf

Coronel JS, Maes GE, Claus S, Van Damme PA, Volckaert FAM. Differential population history in the migratory catfishes Brachyplatystoma flavicans and Pseudoplatystoma fasciatum (Pimelodidae) from the Bolivian Amazon assessed with nuclear and mitochondrial DNA markers. J Fish Biol. 2004; 65(3):859–68. https://doi.org/10.1111/j.0022-1112.2004.00498.x

Dahl G. Los peces del Norte de Colombia. Bogotá (D.C.): Ministerio de Agricultura, Instituto de desarrollo de los recursos naturales renovables (INDRENA); 1971.

Dantas HL, Santos Neto MA, Oliveira KKC, Severi W, Diniz FM, Coimbra MRM. Genetic diversity of captive and wild threatened catfish Pseudoplatystoma corruscans in the São Francisco River. Rev Fish Sci. 2013; 21(3-4):237–46. https://doi.org/10.1080/10641262.2013.800787

Evanno G, Regnaut S, Goudet J. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol. 2005; 14(8):2611–20. https://doi.org/10.1111/j.1365-294X.2005.02553.x

Excoffier L, Lischer HEL. Arlequin suite ver 3.5: A new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Resour. 2010; 10(3):564–67. https://doi.org/10.1111/j.1755-0998.2010.02847.x

FAO. Colombia: pesca en cifras/2014. Bogotá (D.C.): Ministerio de Agricultura y desarrollo rural, Organización de las naciones unidas para la alimentación y la agricultura (FAO); 2015. Available from: https://www.aunap.gov.co/wp-content/uploads/2016/05/Pesca_en_cifras.pdf

Ferraris CJ Jr. Checklist of catfishes, recent and fossil (Osteichthyes, Siluriformes), and catalogue of siluriform primary types. Zootaxa. 2007; 1418(1):1–128. https://doi.org/10.11646/zootaxa.1418.1.1

Fonseca FS, Domingues RR, Hallerman EM, Hilsdorf AWS. Genetic diversity of an imperiled Neotropical catfish and recommendations for its restoration. Front Genet. 2017; 8:196. https://doi.org/10.3389/fgene.2017.00196

Frankham R, Bradshaw CJA, Brook BW. Genetics in conservation management: Revised recommendations for the 50/500 rules, Red List criteria and population viability analyses. Biol Conserv. 2014; 170:56–63. https://doi.org/10.1016/j.biocon.2013.12.036

Fricke R, Eschmeyer WN, Van der Laan R. Eschmeyer’s catalog of fishes: genera, species, references [Internet]. San Francisco: California Academy of Science; 2020. Available from: http://researcharchive.calacademy.org/research/ichthyology/catalog/fishcatmain.asp

Gallo H, Díaz-Sarmiento J. Variabilidad genética del bagre rayado Pseudoplatystoma fasciatum (Pisces: Pimelodidae) en el río Magdalena (Colombia). Rev Acad Colomb Cien Exactas, Fis Nat. 2003; 27(105):559–606.

Galvis G, Mojica JI. The Magdalena River fresh water fishes and fisheries. Aquat Ecosyst Health Manag. 2007; 10(2):127–39. https://doi.org/10.1080/14634980701357640

Galvis G, Mojica JI, Camargo M. Peces del Catatumbo. Bogotá (D.C.): ECOPETROL; 1997.

Garza JC, Williamson EG. Detection of reduction in population size using data from microsatellite loci. Mol Ecol. 2001; 10(2):305–18. https://doi.org/10.1046/j.1365-294x.2001.01190.x

Hilsdorf AWS, Hallerman EM. Genetic resources of Neotropical fishes. New York: Springer International Publishing; 2017. https://doi.org/10.1007/978-3-319-55838-7

Hoyos N, Escobar J, Restrepo JC, Arango AM, Ortiz JC. Impact of the 2010-2011 La Niña phenomenon in Colombia, South America: the human toll of an extreme weather event. Appl Geogr. 2013; 39:16–25. https://doi.org/10.1016/j.apgeog.2012.11.018

Jiménez-Segura LF, Galvis-Vergara G, Cala-Cala P, García-Alzate CA, López-Casas S, Ríos-Pulgarín MI et al. Freshwater fish faunas, habitats and conservation challenges in the Caribbean river basins of north-western South America. J Fish Biol. 2016; 89(1):65–101. https://doi.org/10.1111/jfb.13018

Jiménez-Segura LF, Palacio J, Leite R. River flooding and reproduction of migratory fish species in the Magdalena River basin, Colombia. Ecol Freshw Fish. 2010; 19(2):178–86. https://doi.org/10.1111/j.1600-0633.2009.00402.x

Jiménez-Segura LF, Villa-Navarro FA. Pimelodus grosskopfii Steindachner 1879. In: Lasso CA, Agudelo Córdoba E, Jiménez-Segura LF, Ramírez-Gil H, Morales-Betancourt M, Ajiaco-Martínez RE et al., editors. I. Catálogo de recursos pesqueros continentales de Colombia. Serie Editorial Recursos Hidrobiológicos y Pesqueros Continentales de Colombia. Bogotá (D.C.): Instituto de investigaciones de Recursos Biológicos Alexander von Humboldt; 2011, p.466–71.

Jombart T. adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics. 2008; 24(11):1403–05. https://doi.org/10.1093/bioinformatics/btn129

Kopelman NM, Mayzel J, Jakobsson M, Rosenberg NA, Mayrose I. Clumpak: a program for identifying clustering modes and packaging population structure inferences across K. Mol Ecol Resour. 2015; 15(5):1179–91. https://doi.org/10.1111/1755-0998.12387

Landínez-García RM, Márquez EJ. Microsatellite loci development and population genetics in Neotropical fish Curimata mivartii (Characiformes: Curimatidae). PeerJ. 2018; 6:e5959. https://doi.org/10.7717/peerj.5959

Landínez-García RM, Márquez EJ. Development and characterization of 24 polymorphic microsatellite loci for the freshwater fish Ichthyoelephas longirostris (Characiformes: Prochilodontidae). PeerJ. 2016; 4:e2419. https://doi.org/10.7717/peerj.2419

Li YL, Liu JX. StructureSelector: a web-based software to select and visualize the optimal number of clusters using multiple methods. Mol Ecol Resour. 2018; 18(1):176–77. https://doi.org/10.1111/1755-0998.12719

Littmann MW, Burr BM, Nass P. Sorubim cuspicaudus, a new long-whiskered catfish from northwestern South America (Siluriformes: Pimelodidae). Proc Biol Soc Wash. 2000; 113(4):900–17.

Loir M, Cauty C, Planquette P, Le Bail PY. Comparative study of the male reproductive tract in seven families of South-Arnerican catfishes. Aquat Living Resour. 1989; 2(1):45–56. https://doi.org/10.1051/alr:1989005

López-Casas S, Jiménez-Segura LF, Agostinho AA, Pérez CM. Potamodromous migrations in the Magdalena River basin: Bimodal reproductive patterns in Neotropical rivers. J Fish Biol. 2016; 89(1):157–71. https://doi.org/10.1111/jfb.12941

Luikart G, Cornuet J. Empirical evaluation of a test for identifying allele recently data bottlenecked populations from frequency. Conserv Biol. 1998; 12(1):228–37. https://doi.org/10.1111/j.1523-1739.1998.96388.x

Mancera-Rodríguez NJ, Márquez EJ, Hurtado-Alarcón JC. Uso de citogenética y técnicas moleculares en estudios de diversidad genética en peces colombianos. In: López-H A, editor. Biología Molecular aplicada a la producción animal y la conservación de especies silvestres., Medellín: Universidad Nacional de Colombia; 2013. p.237–312.

Márquez E., Restrepo-Escobar N, Yepes-Acevedo AJ, Narváez JC. Diversidad y estructura genética de los peces de la cuenca del Magdalena, Colombia. In: Jiménez-Segura LF, Lasso CA, editors. XIX. Peces de la cuenca del río Magdalena, Colombia: diversidad, conservación y uso sostenible. Serie Editorial Recursos Hidrobiológicos y Pesqueros Continentales de Colombia. Bogotá, (D.C): Instituto de Investigación de Recursos Biológicos Alexander von Humboldt; 2020. p.115–57.

Marrugo-Negrete J, Verbel JO, Ceballos EL, Benítez LN. Total mercury and methylmercury concentrations in fish from the Mojana region of Colombia. Environ Geochem Health. 2008; 30:21–30. https://doi.org/10.1007/s10653-007-9104-2

Meirmans PG. Using the AMOVA framework to estimate a standardized genetic differentiation measure. Evolution (N Y). 2006; 60(11):2399–402. https://doi.org/10.1111/j.0014-3820.2006.tb01874.x

Meirmans PG, Hedrick PW. Assessing population structure: FST and related measures. Mol Ecol Resour. 2011; 11(1):5–18. https://doi.org/10.1111/j.1755-0998.2010.02927.x

MejíaRivera O, Betancur-Vargas T, Londoño-Ciro L. Aplicación de técnicas geoestadisticas en la hidrogeología del bajo Cauca antioqueño. Dyna. 2007; 74(152):137–49. Available from: http://www.scielo.org.co/pdf/dyna/v74n152/a12v74n152.pdf

Mojica JI, Castellanos C, Álvarez -León R, Villa-Navarro FA. Ageneiosus pardalis Lütken 1874. In: Mojica JI, Usma-Oviedo JS, Álvarez-León R, Lasso CA, editors. Libro rojo peces dulceacuícolas de Colombia 2012. Bogotá (D.C.): Investigación de Recursos Biológicos Alexander von Humboldt, Instituto de Ciencias Naturales de la Universidad Nacional de Colombia, WWF Colombia y Universidad de Manizales; 2012a. p.71–73.

Mojica JI, Galvis G, Sánchez-Duarte P, Castellanos C, Villa-Navarro FA. Peces del valle medio del río Magdalena, Colombia. Biota Colomb. 2006; 7(1):23–37.

Mojica JI, Usma-Oviedo JS, Álvarez-León R, Lasso CA. Libro Rojo de peces dulceacuicolas de Colombia 2012. Bogotá (D.C.): Instituto de Investigación de los Recursos Biológicos Alexander von Humboldt, Instituto de Ciencias Naturales de la Universidad Nacional de Colombia, WWF Colombia, Universidad de Manizales; 2012b. https://doi.org/10.1007/s13398-014-0173-7.2

Nelson JS, Grande TC, Wilson MVH. Fishes of the world. Hoboken, New Jersey: John Wiley & Sons; 2016. https://doi.org/10.1007/bf00005935

Oosterhout C Van, Hutchinson WF, Wills DPM, Shipley P. MICRO-CHECKER: Software for identifying and correcting genotyping errors in microsatellite data. Mol Ecol Notes. 2004; 4(3):535–38. https://doi.org/10.1111/j.1471-8286.2004.00684.x

Ortega-Lara A, Lasso-Alcalá OM, Lasso CA, Pasquier GA, Bogotá-Gregory JD. Peces de la subcuenca del río Catatumbo, cuenca del Lago de Maracaibo, Colombia y Venezuela. Biota Colomb. 2012; 13(1):71–99. Available from: http://revistas.humboldt.org.co/index.php/biota/article/view/258

Ortega-Lara A, Usma JS, Bonilla PA, Santos NL. Peces de la cuenca alta del río Cauca, Colombia. Biota Colomb. 2006; 7(1):39–54.

Peakall R, Smouse PE. GenALEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics. 2012; 28(19):2537–39. https://doi.org/10.1093/bioinformatics/bts460

Pereira LHG, Foresti F, Oliveira C. Genetic structure of the migratory catfish Pseudoplatystoma corruscans (Siluriformes: Pimelodidae) suggests homing behaviour. Ecol Freshw Fish. 2009; 18(2):215–25. https://doi.org/10.1111/j.1600-0633.2008.00338.x

Piry S, Luikart G, Cornuet JM. BOTTLENECK: a computer program for detecting recent reduction in the effective population size using allele frequency data. J Hered. 1999; 90(4):502–03. https://doi.org/10.1093/jhered/90.4.502

Prado FD, Fernández-Cebrián R, Foresti F, Oliveira C, Martínez P, Porto-Foresti F. Genetic structure and evidence of anthropogenic effects on wild populations of two Neotropical catfishes: baselines for conservation. J Fish Biol. 2018; 92(1):55–72. https://doi.org/10.1111/jfb.13486

Prado FD, Fernández-Cebrián R, Hashimoto DT, Senhorini JA, Foresti F, Martínez P, Porto-Foresti F. Hybridization and genetic introgression patterns between two South American catfish along their sympatric distribution range. Hydrobiologia. 2017; 788:319–43. https://doi.org/10.1007/s10750-016-3010-5

Pritchard JK, Stephens M, Donnelly P. Inference of population structure using multilocus genotype data. Genetics. 2000; 155(2):945–59. Available from: https://www.genetics.org/content/genetics/155/2/945.full.pdf

Puechmaille SJ. The program structure does not reliably recover the correct population structure when sampling is uneven: subsampling and new estimators alleviate the problem. Mol Ecol Resour. 2016; 16(3):608–27. https://doi.org/10.1111/1755-0998.12512

Ramella MS, Kroth MA, Meurer S, Nuñer APDO, Zaniboni Filho E, Arisi ACM. Genetic variability in four fish species (Pimelodus maculatus, Prochilodus lineatus, Salminus brasiliensis and Steindachneridion scripta) from Uruguay River Basin. Braz Arch Biol Technol. 2006; 49(4):589–98. https://doi.org/10.1590/S1516-89132006000500008

R Development Core Team. R: A Language and Environment for Statistical Computing; 2017. Available from: https://www.R-project.org/

Rangel-Medrano JD, Ortega-Lara A, Márquez EJ. Ancient genetic divergence in bumblebee catfish of the genus Pseudopimelodus (Pseudopimelodidae: Siluriformes) from northwestern South America. PeerJ. 2020; 8:e9028. https://doi.org/10.7717/peerj.9028

Restrepo-Escobar N, Márquez EJ. Microsatellite loci development for three catfish species from northwestern South America. Neotrop Ichthyol. 2020; 18(1):e190079. https://doi.org/10.1590/1982-0224-2019-0079

Restrepo-Gómez AM, Rangel-Medrano JD, Márquez EJ, Ortega-Lara A. Two new species of Pseudopimelodus Bleeker, 1858 (Siluriformes: Pseudopimelodidae) from the Magdalena Basin, Colombia. PeerJ. 2020; 8:e9723. https://doi.org/10.7717/peerj.9723

Restrepo-Moreno SA, Foster DA, Stockli DF, Parra-Sánchez LN. Long-term erosion and exhumation of the Altiplano Antioqueño, Northern Andes (Colombia) from apatite (U-Th)/He thermochronology. Earth Planet Sci Lett. 2009; 278(1-2):1–12. https://doi.org/10.1016/j.epsl.2008.09.037

Ribeiro FRV, Rapp Py-Daniel LH, Walsh SJ. Taxonomic revision of the South American catfish genus Ageneiosus (Siluriformes: Auchenipteridae) with the description of four new species. J Fish Biol. 2017; 90(4):1388–478. https://doi.org/10.1111/jfb.13246

Ribolli J, Melo CMR, Zaniboni-Filho E. Genetic characterization of the Neotropical catfish Pimelodus maculatus (Pimelodidae, Siluriformes) in the Upper Uruguay River. Genet Mol Biol. 2012; 35(4):761–69. https://doi.org/10.1590/S1415-47572012005000060

Rice WR. Analyzing Tables of Statistical Tests. Evolution (N Y). 1989; 43(1):223–25. https://doi.org/10.2307/2409177

Ríos N, Bouza C, García G. Past hybridisation and introgression erased traces of mitochondrial lineages evolution in the Neotropical silver catfish Rhamdia quelen (Siluriformes: Heptapteridae). Hydrobiologia. 2019; 830:161–77. https://doi.org/10.1007/s10750-018-3861-z

Ríos N, Bouza C, Gutiérrez V, García G. Species complex delimitation and patterns of population structure at different geographic scales in Neotropical silver catfish (Rhamdia: Heptapteridae). Environ Biol Fishes. 2017; 100:1047–67. https://doi.org/10.1007/s10641-017-0622-1

Sekine ES, Prioli AJ, Prioli SMAP, Júlio Júnior HF. Genetic differentiation among populations of Pseudoplatystoma corruscans (Agassiz, 1829) (Osteichthyes, Pimelodidae) isolated by the Guaíra Falls in the Paraná River. Acta Sci. 2002; 24(2):507–12. Available from: http://repositorio.uem.br:8080/jspui/bitstream/1/5222/1/375.pdf

Soulé ME. Thresholds for survival: maintaining fitness and evolutionary potential. In: Soulé ME, Wilcox B, editors. Conservation biology: an evolutionary-ecological Perspective. Sunderland: Sinauer Associates Inc; 1980. p.151–69.

Telles MP, Collevatti RG, Braga RS, Guedes LBS, Castro TG, Costa MC et al. Geographical genetics of Pseudoplatystoma punctifer (Castelnau, 1855) (Siluriformes, Pimelodidae) in the Amazon basin. Genet Mol Res. 2014; 13(2):3656–66. https://doi.org/10.4238/2014.May.9.8

Unidad de planeación minero energética (UPME). Producción, regalías y comercio exterior [Internet]. Bogotá (D.C.): Sistema de información minero colombiano (SIMCO).; 2019. Available from: http://www1.upme.gov.co/simco/Cifras-Sectoriales/Paginas/Informacion-estadistica-minera.aspx

Usma-Oviedo JS, Valderrama M, Escobar MD, Ajiaco-Martínez RE, Villa-Navarro FA, Castro F et al. Peces dulceacuícolas migratorios en Colombia. In: Naranjo LG, Amaya Espinel JD, editors. Plan nacional de las especies migratorias. Ministro de ambiente, Vivienda y Desarrollo Territorial, WWF Colombia; 2009. p.103–32. Available from: http://d2ouvy59p0dg6k.cloudfront.net/downloads/plan_migratorias_version_web.pdf

Vaini JO, Crispim BA, Silva DBS, Benites C, Russo MR, Grisolia AB. Genetic variability of pure Pseudoplatystoma corruscans and Pseudoplatystoma reticulatum individuals in the Paraná and Paraguay River basins. Fish Sci. 2016; 82:605–11. https://doi.org/10.1007/s12562-016-0999-3

Villa-Navarro FA, Acero P A, Cala-Cala P. Taxonmic review of Trans-Andean species of Pimelodus (Siluriformes: Pimelodidae), with the description of two new species. Zootaxa. 2017; 4299(3):337–60. https://doi.org/10.11646/zootaxa.4299.3.2

Villa-Navarro FA, Usma-Oviedo JS, Mesa-Salazar L, Sanchez-Duarte P. Pimelodus grosskopfii. The IUCN red list of threatened species 2016:eT49829828A61473588 [Internet]. http://dx.doi.org/10.2305/IUCN.UK.2016-1.RLTS.T49829828A61473588.en

Villa-Navarro FA, Zúñiga-Upegui PT, Castro-Roa D, García-Melo JE, García-Melo LJ, Herrada-Yara ME. Peces del alto Magdalena, cuenca del río Magdalena, Colombia. Biota Colomb. 2006; 7(1):3–22.

Zamudio KR, Robertson JM, Chan LM, Sazima I. Population structure in the catfish Trichogenes longipinnis: Drift offset by asymmetrical migration in a tiny geographic range. Biol J Linn Soc. 2009; 97(2):259–74. https://doi.org/10.1111/j.1095-8312.2009.01209.x

Authors

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Natalia Restrepo-Escobar^[1] , Anny Johanna Yepes-Acevedo^[1]  and Edna Judith Márquez^[1] 

^[1]    Facultad de Ciencias, Escuela de Biociencias, Laboratorio de Biología Molecular y Celular, Universidad Nacional de Colombia, Sede Medellín, Carrera 65 No 59A, 110 Bloque 19A Laboratorio 310, Medellín 050034, Colombia. (NRE) nrestree@unal.edu.co; (AJYA) ajyepesa@unal.edu.co; (EJM) ejmarque@unal.edu.co, ejmarque@gmail.com (corresponding author).

Authors Contribution

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Natalia Restrepo-Escobar: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing-original draft, Writing-review and editing.

Anny Johanna Yepes-Acevedo: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing-original draft, Writing-review and editing.

Edna Judith Márquez: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing-original draft, Writing-review and editing.

Ethical Statement​

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Environmental license of Ministerio de Ambiente, Vivienda y Desarrollo Territorial # 0155 of January 30th, 2009.

Competing Interests

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The authors declare no competing interests.

How to cite this article

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Restrepo-Escobar N, Yepes-Acevedo AJ, Márquez EJ. Population genetics of three threatened catfish species in heterogeneous environments of the Cauca River, Colombia. Neotrop Ichthyol. 2021; 19(1):e200040. https://doi.org/10.1590/1982-0224-2020-0040

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

© 2021 The Authors.

Diversity and Distributions Published by SBI

Submitted May 22, 2020

Accepted December 29, 2020
by Guillermo Ortí

Epub 08 March, 2021