The Neotropical region’s freshwaters are highly diverse, representing approximately one-fifth of the more than 35.000 known extant fish species (Nelson et al., 2016; Birindelli, Sidlauskas, 2018; Fricke et al., 2021). The coastal rivers of eastern Brazil stand out by their high proportion of endemic species (Bizerril, 1994; Schaefer, 1997; Mittermeier et al., 2005; Albert et al., 2011). This high proportion of endemics is thought to be related to the isolation of these drainages from larger continental basins (Ribeiro, 2006; Thomaz, Knowles, 2018; Wendt et al., 2019).
Among the geographic processes associated with geographic distribution and genetic structuring of populations within the coastal rivers of southeastern Brazil, the two more often cited are headwater stream capture and isolation/connection due to marine transgressions and regressions (Ribeiro, 2006; Roxo et al., 2014; Thomaz, Knowles, 2018; Thomaz et al., 2019). Stream capture, when part of a river drainage basin is diverted into an adjacent basin, is an important geographic event affecting the distribution of freshwater organisms (Albert et al., 2011, 2018; Souza et al., 2020). From a biogeographic perspective, stream capture involves first geodispersal (e.g., erosion of barriers) and latter vicariance (e.g., emergence of new geographic barriers to dispersal and gene flow) (Albert, Crampton, 2010). Another contrasting geographic event is the connection and disruption of basins caused by marine transgressions and regressions that may profoundly affect the population dynamics on the coastal drainages (Thomaz et al., 2015; Shelley et al., 2020). During the Pleistocene glacial periods, the Brazilian coast was impacted by lower sea levels, and the exposed paleodrainages connected currently isolated riverine basins and may have served as dispersal corridors (Dias et al., 2014; Thomaz et al., 2015, 2017).
The south and southeastern coastal drainages of Brazil encompass three Freshwater Ecoregions of the World (FEOW): Tramandaí-Mampituba, Southeastern Mata Atlântica, and Ribeira de Iguape (Abell et al., 2008; Thomaz, Knowles, 2018). Ecoregions are widely recognized and applied geospatial units for conservation planning, developed to represent patterns of environmental and ecological variables known to influence the distribution of biodiversity at broad scales (Abell et al., 2008). Rivers of southeastern Brazil flow within the Atlantic Rain forest, a major biodiversity hotspot. This biome has been reduced to less than 8% of its original range. Currently, its fragments harbor one of the largest percentages of endemic species in the world (Morellato, Haddad, 2000; Rodrigues, 2005; Carnaval et al., 2009). Freshwater ecosystems and their diverse communities of species may be the most endangered (Abell et al., 2008). Species of freshwater fish are often unable to cross barriers and represent an evolutionarily conserved system most susceptible to climate change (Dias et al., 2014). Knowledge of genetic diversity patterns on isolated freshwater systems within the Atlantic Rainforest is still limited, and conservation planning is hindered.
To evaluate phylogeographic patterns in this region, we accessed the genetic diversity of Hisonotus leucofrenatus (Miranda Ribeiro, 1908), which belongs to the Hypoptopomatinae, a group of small-sized loricariids including 252 species (Fricke et al., 2021). Hisonotus Eigenmann & Eigenmann, 1889,is the most species-rich genus of Hypoptopomatinae and recent contentious taxonomic circumscription suggests that this group encompasses about 50 species (Roxo et al., 2019; Reis et al., 2019). Hisonotus leucofrenatus occurs in coastal drainages of southern and southeastern Brazil, between Tramandaí (southern boundary) and Ribeira de Iguape (northern boundary) (Fig. 1; Carvalho, Reis, 2011), in which inhabits lowland portions of rivers within slow to medium flowing waters (Malabarba et al., 2013), characteristics that are associated to species of large distribution (Carvajal-Quintero et al., 2019). Habitat and other ecological specificities are often associated with phylogeographic structure (Papadopoulou, Knowles, 2016). In this sense, the lowlander H. leucofrenatus contrasts with other fish species in this region that were studied in a phylogeographic framework (e.g., Hollandichthys Eigenmann, 1910, a forest specialist in Thomaz et al., 2015; Diapoma itaimbe (Malabarba & Weitzman, 2003)and Bryconamericus lethostigmus (Gomes, 1947)rapid dwellers in Hirschmann et al., 2015, 2017; and Thomaz, Knowles, 2020) that often show a per basin genetic structure.
Thus, this study main objective is to evaluate how Pleistocene sea-level changes may have affected the genetic diversification of Hisonotus leucofrenatus. If paleodrainage connections during marine regressions served as an opportunity for dispersal among currently isolated rivers, they might have left a signature in the genetic diversity of this species, otherwise, if proposed paleodrainages fail to describe past connections correctly, it can be suggested that processes such as river capture may have a more significant role (e.g., Lima et al., 2017). We also evaluate how physical characteristics of these paleodrainages (e.g., area, number of tributaries) may correlate with populations’ genetic diversity in this region (Thomaz et al., 2017).
Material and methods
Samples. We included 80 specimens of H. leucofrenatus in the analyses distributed throughout its area of occurrence, in a total of 14 currently isolated drainages, from Tramandaí River system in Rio Grande do Sul State to Ribeira de Iguape River basin in São Paulo State (Fig. 1) corresponding to the known species distribution (Carvalho, Reis, 2011). The number of samples per each drainage vary between 3 and 12 specimens and are often from distant collecting localities, trying to maximize the genetic diversity observed at each drainage (Tab. 1; S1). Samples came from museum historical collections, but three recent collection expeditions were conducted to obtain genetic data in regions that there were no tissue samples. Fish expeditions were done with permits (SISBIO/ICMBio #9318–1, 9220–1, 8796–1). All fishes were euthanized using clove oil – eugenol (following Lucena et al., 2013), and tissues were collected from fin clips or muscle. All samples are deposited in the fish collection of the Departamento de Zoologia, Universidade Federal do Rio Grande do Sul (UFRGS) (S1).
Molecular data. DNA extractions were made using a CTAB protocol (Doyle, Doyle, 1987). PCR was used to amplify the mitochondrial gene Cytochrome Oxidase I (cox1) (primers LCO1490 and HCO 21908 primers in Folmer et al., 1994) and nuclear gene rpS7 ribosomal protein gene intron 1 (rpS7; S7RPEX1F and S7RPEX2R primers in Chow, Hazama, 1998). Heterozygous sites in the rpS7 nuclear gene were coded with IUPAC ambiguity codes. For the nuclear gene rpS7 intron 1 only a subset of 27 specimens was sequenced due to difficulties in amplification, this datasets represents most drainages and all paleodrainages. PCRs were carried out in 20 µL reactions containing 10–50 ng DNA, 0.2 µM of each primer, 0.2 mM of each dNTP, 1X Buffer, 1.5 µM MgCl2 and 1U Platinum Taq DNA polymerase (Invitrogen, São Paulo, Brazil). PCR conditions followed recommendations reported for the respective primers. PCR products were checked by electrophoresis in agarose gel, purified using ExoSap (Exonuclease I and Shrimp Alkaline Phosphatase, GE Healthcare, Piscataway, NJ, USA) and sequenced cox1 and rpS7 genes in both directions by MACROGEN Inc., Seul, Korea, and ACTGENE Ltda., Porto Alegre, Brazil. Sequences were edited and aligned in Geneious 126.96.36.199, that uses the Muscle algorithm (Edgar, 2004). All sequences were uploaded in the GenBank (S1).
Phylogeographic and phylogenetic reconstruction methods. The haplotype diversity, nucleotide diversity, neutrality tests Fu’s FS (Fu, 1997) and Tajima’s D (Tajima, 1989) were calculated on DNASP v.5 (Librado, Rozas, 2009) for the cox 1 gene. The haplotype network was constructed with the cox1 gene using the Median-Joining method in PopArt (Bandelt et al., 1999). PartitionFinder 2.1.1 (Lanfear et al., 2016) was used to find the best nucleotide substitution models. The cox1 gene was partitioned by codon positions and rpS7 considered as a single partition and the Bayesian Information Criterion (BIC) was used to model selection in PartitionFinder. Phylogenetic relationships between populations were inferred using Bayesian Inference in BEAST 2.3 (Bouckaert et al., 2019) and both genes (cox1 and rpS7) separately. A strict molecular clock was used to estimate the divergence time between lineages, appropriate for analysis within species or among closely related species (Li, Drummond, 2011). We use cox1 evolutionary rates proposed by Bermingham et al. (1997) of 0.01/site/million years, followed by other phylogeographic studies in the region (Thomaz et al., 2015; Hirschmann et al., 2015, 2017). The haplotype trees were based on 40 million MCMC steps. The trees were sampled every 1000 steps; chain efficiency was observed in TRACER 1.5 (Rambaut et al., 2018), and after that, trees were summarized using Maximum Clade Credibility tree criterion in treeAnnotator with 10% burn-in.
TABLE 1 | Number of samples sequenced for Cytochrome Oxidase subunit 1 (cox1) and rpS7 ribosomal protein gene intron 1(rpS7) genes by drainage (populations) and its respective paleodrainage.
Ribeira de Iguape
ribeira de iguape
Calculation of Fstatistic (Φst) and analysis of molecular variance (AMOVA) were done in ARLEQUIN 3.5 (Excoffier et al., 2005) using the cox1 gene. Groups on AMOVA, were made considering paleodrainages following (Thomaz, Knowles, 2018), and each population was equal to the currently isolated drainages by the sea (Tab. 1; S1). We also follow the same nomenclature of paleodrainages as in Thomaz, Knowles (2018, tab. 1). Since some paleodrainages, have the same names as current drainages, here we used the first word capitalized for drainages and lower case for paleodrainages. Samples on rivers draining to the Paranaguá bay area were grouped into two populations in order to have more than one specimen per population in the AMOVA analysis: one population with samples from nearest rivers (draining the west portion) and another population corresponding to the northern tributaries (Fig. 1), similar to phylogeographic structure proposed for other groups in the region (Tschá et al., 2017). These two populations compose the paleodrainage of paranaguá for the AMOVA configuration. Samples from Ribeira de Iguape river drainage were excluded from AMOVA analysis because there is a single population (drainage) to a single paleodrainage. To evaluate whether there was a correspondence between genetic variation and paleodrainages features, we examined the correlation between genetic diversity (mean number of pairwise differences – π) and paleodrainage physical characteristics such as number of tributaries, contemporary area and exposed area (Papadopoulou et al., 2011; Thomaz et al., 2017; Thomaz, Knowles, 2018; S2) using the linear regression function in Microsoft Excel.
A total 80 specimens from the entire distribution of H. leucofrenatus (Fig. 1) were sequenced (678 base pairs) for the mitochondrial cox1 gene. For the nuclear gene rpS7 intron 1 a subset of 27 specimens (608 base pairs) was sequenced (Tab. 1; S1). Best fit nucleotide substitution models were TrNef (TrN equal base frequencies, Tamura, Nei, 1993) for first codon position and HKY (Hasegawa et al., 1985) for second and third codon positions of the mitochondrial cox1 and HKY+G for the nuclear rpS7. Details on the number of sequenced specimens, number of observed mitochondrial haplotypes, haplotype diversity (h), nucleotide diversity (π), Tajima’s D, Fu’s FS and theta values are in Tab. 2. Only cox1 values are listed, as the sampling of nuclear rpS7 is relatively low – this later gene was used only for phylogenetic reconstructions.Phylogenetic history and divergence time estimates. Our phylogenetic estimates support two highly diverged clades in both molecular markers (Fig. 2A – cox1; Fig. 2B – rpS7), herein named north and south. According to molecular calibration only using the mitochondrial marker, this divergence occurred at about 2.6 Ma (95% confidence intervals of 1.9 – 3.5 Ma). In the north group, a clade representing individuals from Ribeira de Iguape River drainage in the cox1 tree form a monophyletic unit sister to a large group containing several populations from other southern basins (Fig. 2A; S3), this relationship is not supported by the rpS7 gene (Fig. 2B; S4). The group formed by Ribeira de Iguape River specimens diverged at about 1.3 Ma (95% confidence intervals of 0.8 – 2.8 Ma) from other southward populations in the north group (S3). Most paleodrainages form well supported monophyletic units with some degree of lineage sharing between paranaguá and itajaí and also between itajaí and florianópolis paleodrainages in both rpS7 and cox1 genes. Divergence age estimates of these less inclusive monophyletic units vary between 0.6 Ma (tramandaí) and 0.3 Ma (florianópolis). Similar patterns of geographic structure by paleodrainage are observed in the haplotype network for mtDNA data that shows two consistent and genetically distinct groups: north (including paleodrainages: ribeira de iguape, paranaguá, itajaí and florianópolis) and south (limited to a single paleodrainage, tramandaí – see Fig. 3A). Only two among 32 haplotypes (Tab. 1) are shared between paleodrainages. Extensive haplotype sharing between drainages (populations) is observed throughout H. leucofrenatus distribution, except the Ribeira de Iguape River drainage with its haplotypes (Fig. 3B).
TABLE 2 | Genetic diversity of cox 1: sample size (N), haplotype number (H), haplotype diversity (Hd), mean number of pairwise differences (π), D of Tajima statistic (D) and FS test (FS). *Value of P <0.001; **Population not considered for the AMOVA analyses.
0.8775 ± 0.0386
2.427350 ± 1.357928
0.6667 ± 0.0910
0.787879 ± 0.613118
0.8933 ± 0.0354
2.166667 ± 1.242691
0.8000 ± 0.1721
1.333333 ± 0.954521
0.7143 ± 0.1809
1.61904 ± 1.082592
Source of variation
% of variation
FIGURE 1 | Map of geographic distribution and included samples of Hisonotus leucofrenatus from coastal drainages of southeastern Brazil. Colors of the circles represent groups sampled according limits of paleodrainage systems for the region and sample photo of Hisonotus leucofrenatus from Tramandaí River system, UFRGS 16528 (photo by L. R. Malabarba).
FIGURE 2 | Phylogeny of Hisonotus leucofrenatus samples. A. Cytochrome Oxidase subunit 1; and B. rpS7 ribosomal protein gene intron 1 sequences. Numbers represent posterior probabilities of the respective node. Terminals collapsed into large and well supported group and colors represent paleodrainages according to Fig. 1. In (A) X axis represents time (Ma).
Paleodrainage genetic structure and diversity. Paleodrainage structure is strongly evidenced by both network and phylogenetic analyses (Figs. 2–3A). AMOVAs suggests a greater partitioning of genetic variation among paleodrainage (90.6%) than among populations (current drainages) within paleodrainages (4.3%) and within populations (5%) (Tab. 2). The linear regressions pointed to a positive correlation and high r-square values between paleodrainage contemporary land area and continental shelf area exposed when compared with index of genetic diversity (mean number of pairwise differences – π) but not a strong correlation with the number of isolated drainages in each paleodrainage (Figs. 4A-C). Other descriptive values of genetic diversity in paleodrainages are found in Tab. 1.
FIGURE 3 | Haplotype network using Median-Joining for only cox1 sequences of Hisonotus leucofrenatus samples. A. Colors represent groups by paleodrainage; and B. Colors represent populations by current drainages. We use upper case in the first word of the noun for drainages (e.g., Tramandaí River system) to differentiate from the homonymous paleodrainages (e.g., tramandaí).
FIGURE 4 | Linear regression plots of the relationship between genetic diversity (mean number of pairwise differences π) and physical characteristics of paleodrainage (contemporary land area, continental shelf area exposed and number of contemporary basins) as described by Thomaz, Knowles, 2018 (S2). A. Contemporary land area (R2 = 0.90); B. Continental shelf area exposed (R2 0.77); C. Number of contemporary basin (R2 = 0.21).
The freshwater fishes in the coastal region of Brazil were strongly influenced by marine regressions and transgressions (Weitzman et al., 1988; Thomaz et al., 2015), which alternately connected and disconnected populations through Pleistocene glacial cycles. The phylogeographic structure of H. leucofrenatus corroborates proposed paleodrainage configurations on the southeastern coast of Brazil during periods of marine regression (Dias et al., 2014; Thomaz et al., 2015, 2017; Thomaz, Knowles, 2018). This shows that freshwater fishes in this region used these paleoconnections during sea regression periods, and interchanges among adjacent drainages were rare. Our data evidenced that paleodrainages, promoted by marine regressions, shaped the genetic profile of these populations (Thomaz et al., 2015, 2017; Tschá et al., 2017). The influence on patterns of genetic diversity seems to be associate with paleodrainage physical features as well (Figs. 4a–b; Thomaz et al., 2017). The species-area relationship is a robust biogeographic predictor for richness and endemism (Albert et al., 2011), and as seems to be the case for genetic diversity (Fan et al., 2019). In our estimates, we found that both the current area and past geographic area (area submerged in the continental platform) strongly correlates with genetic diversity, but not the number of drainages (Fig. 4C), suggesting that the current isolation of coastal basins has less impact on the genetic structure of the populations (Thomaz et al., 2017).
Factors intrinsic to species can result in specific distribution patterns (Whiteley et al., 2004; Burridge et al., 2008). For example, fish faunas from high latitudinal regions are dominated by large-bodied species, while the fish assemblages from river basin of the neotropical realms harbor smaller mean body sizes (Blanchet et al., 2010). This biological trait is associated with the dispersal capacity of freshwater fishes, where small-bodied species have less dispersal capacity (Tedesco et al., 2012; Radinger, Wolter, 2014). Hisonotus leucofrenatus as a small-bodied species seems to contrast this general rule, at least when we consider dispersal among drainages in the same paleodrainage. Studies in this region have shown that the corridors among drainages facilitate dispersal depending on species specific ecological restrictions (Hirschmann et al., 2015, 2017; Thomaz et al., 2015, Thomaz, Knowles, 2020). In terms of habitat specificity, H. leucofrenatus populations are mostly found in the lowlands (Malabarba et al., 2013), an area that has higher connectivity during lower sea levels (Carvajal-Quintero et al., 2019). These characteristics contrasts with some other investigated taxa in a phylogeographic context such as Hollandichthys, a forest specialist (Thomaz et al., 2015; Thomaz, Knowles, 2020), and Diapoma itaimbe, Bryconamericus lethostigmus, and Epactionotus Reis & Schaefer, 1998,found almost exclusively in fast-flowing waters towards headwaters of river drainages (Hirschmann et al., 2015, 2017; Delapieve et al., 2020; Thomaz, Knowles, 2020). Within coastal drainages, some species show patterns of genetic structuring also by current drainage and not just preterit drainage (Lima et al., 2017; Delapieve et al., 2020), a feature not observed in Hisonotus (e.g., AMOVA, Fig. 3B). In terms of macroevolution, hypoptopomatines inhabiting fast-flowing, rocky riverine habitats exhibited increased body size and higher lineage diversification rates (Roxo et al., 2017), which can be associated with the geographical discontinuity and diminished connectivity of these types of habitats. Higher species richness and limited distributions are seen in the region for other loricariids as for Epactionotus (Delapieve et al., 2020) and Pareiorhaphis Miranda Ribeiro, 1918 (Pereira, Reis, 2002; Cramer et al., 2007), which contrasts with H. leucofrenatus, a single widespread species in these coastal basins.
Hisonotus leucofrenatus has a genetic diversity pattern that strongly correlates with paleodrainage configuration, evidencing its dispersal during the last glacial maximum. Dispersal between neighboring paleodrainages seem to be rare and its limits may compose strong barriers to gene flow within populations of fishes in this region, which is a potential factor for lineage diversification. One of the strong and oldest barriers affecting H. leucofrenatus populations is the one located between the paleodrainage tramandaí and florianópolis that is supported by strong genetic divergence between north and south groups (Figs. 2–3). In this area lies the Serra do Tabuleiro, a high promontory of the Serra do Mar that may act as a barrier for dispersal of fishes within the coastal basins of South Brazil. The role of this geographic feature as a barrier is also supported by species distributional limits (Carvalho, 2007) and genetic based evidence of other fish species (south barrier of Thomaz, Knowles, 2020). Furthermore, the genetic structure between populations of H. leucofrenatus support an additional previously proposed populational break (central break in Thomaz, Knowles, 2020 similar but southward in Tschá et al., 2017) observed in the genetic structure of other species between Paranaguá Bay and Ribeira de Iguape River basin (Fig. 1). As discussed by these authors, no obvious geological structures would support this break, other than its paleodrainage discontinuity. This spatial break are not temporarily concomitant, which may also be supported by our age estimates (Fig. 2A), in general older within the Pleistocene than previously proposed to other species (Thomaz, Knowles, 2020).
The southeastern coastal drainages of Brazil encompass three Freshwater Ecoregions of the World: (Tramandaí-Mampituba, Southeastern Mata Atlântica and Ribeira de Iguape) that are widely applied geospatial units for conservation planning and biogeographical studies and represent environmental and ecological variables known to influence the distribution of biodiversity at broad scales (Abell et al., 2008; Albert, Carvalho, 2011). In terms of genetic variation within these Freshwater Ecoregion patterns are, to some extension, discordant with limits proposed for these areas (e.g., limits between Tramandaí-Mampituba and the Southeastern Mata Atlântica ecoregions), which is true for other freshwater groups in this region (Thomaz, Knowles, 2020). For freshwater fish taxa in this region, it is more interesting, from a conservation standpoint, to look at the genetic structuring of paleodrainages, than the current proposed ecoregion configuration. Further studies on the coastal basin of southeastern Brazil should contrast these observed genetic patterns with proposed areas of species endemism and bioregionalization (e.g., Menezes, 1988; Bizerril, 1994; Abell et al., 2008).
We would like to thank to J. Wingert and L. R. Malabarba for support with the scientific collection of fishes at the Universidade Federal Rio Grande do Sul. Thanks to J. Ferrer, P. Madoka, L. Donin, and J. Wingert for help collecting specimens in field trips. We also thank J. Ferrer, A. Hirschmann, A. Thomaz, V. Valiati for comments and suggestions on the manuscript. NLP was supported with a master’s scholarship by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). TPC was supported during the development of this work by a PNPD (CAPES) postdoctoral scholarship. Specimens for this study were collected with support of a CNPq universal (#401204/2016–2) fellowship in which TPC was a collaborator.
Abell R, Thieme ML, Revenga C, Bryer M, Kottelat M, Bogutskaya N et al. Freshwater ecoregions of the world: a new map of biogeographic units for freshwater biodiversity conservation. BioScience. 2008; 58(5):403–14. https://doi.org/10.1641/B580507
Albert JS, Carvalho TP. Neogene assembly of modern faunas. In: Albert JS, Reis RE, editors. Historical Biogeography of Neotropical Freshwater Fishes. Berkeley: University of California Press; 2011. p.119–36.
Albert JS, Craig JM, Tagliacollo VA, Petry P. Upland and lowland fishes: a test of the river capture hypothesis. In: Hoorn CM, Perrigo A, Antonelli A, editors. Mountains, Climate and Biodiversity. Crambridge: Wiley Press; 2018. p.273–94.
Albert JS, Crampton WG. The geography and ecology of diversification in Neotropical freshwaters. Nature Education Knowledge. 2010; 3(10):13–19.
Albert JS, Petry P, Reis RE. Major biogeographic and phylogenetic patterns. In: Albert JS, Reis RE, editors. Historical Biogeography of Neotropical Freshwater Fishes. Berkeley: University of California Press; 2011. p.21–57.
Bandelt H, Forster P, Röhl A. Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol. 1999; 16(1):37–48. https://doi.org/10.1093/oxfordjournals.molbev.a026036
Bermingham E, McCafferty SS, Martin AP. Fish biogeography and molecular clocks: perspectives from the Panamanian Isthmus. In: Kocher TD, Stepien CA, editors. Molecular systematics of fishes. New York: Academic Press; 1997. p.113–28.
Birindelli JLO, Sidlauskas BL. Preface: How far has Neotropical Ichthyology progressed in twenty years? Neotrop Ichthyol. 2018, 16(3):e180128. https://doi.org/10.1590/1982-0224-20180128
Bizerril CRSF. Análise taxonômica e biogeográfica da ictiofauna de água doce do leste brasileiro. Acta Biol Leopoldensia. 1994; 16(1):51–80.
Blanchet S, Grenouillet G, Beauchard O, Tedesco PA, Leprieur F, Dürr HH et al. Non- native species disrupt the worldwide patterns of freshwater fish body size: implications for Bergmann’s rule. Ecol Lett. 2010; 13(4):421–31. https://doi.org/10.1111/j.1461-0248.2009.01432.x
Bouckaert R, Vaughan TG, Barido-Sottani J, Duchêne S, Fourment M, Gavryushkina A, Heled J et al. BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis. PLoS Comput Biol. 2019; 15(4):e1006650. https://doi.org/10.1371/journal.pcbi.1006650
Burridge CP, Craw D, Jack DC, King TM, Waters JM. Does fish ecology predict dispersal across a river drainage divide? Evolution. 2008; 62(6):1484–99. https://doi.org/10.1111/j.1558-5646.2008.00377.x
Carnaval AC, Hickerson MJ, Haddad CFB, Rodrigues MT, Moritz C. Stability predicts genetic diversity in the Brazilian Atlantic forest hotspot. Science. 2009; 323(5915):785–89. https://doi.org/10.1126/science.1166955
Carvajal-Quintero J, Villalobos F, Oberdorff T, Grenouillet G, Brosse S, Hugueny B et al. Drainage network position and historical connectivity explain global patterns in freshwater fishes’ range size. Proc Natl Acad Sci U S A. 2019; 116(27):13434–39. https://doi.org/10.1073/pnas.1902484116
Carvalho TP. Distributional patterns of freshwater fishes in coastal Atlantic drainages of eastern Brazil: a preliminary study applying parsimony analysis of endemism. Darwiniana. 2007; 45:65–67.
Carvalho TP, Reis RE. Taxonomic review of Hisonotus Eigenmann & Eigenmann (Siluriformes: Loricariidae: Hypoptopomatinae) from the laguna dos Patos system, southern Brazil. Neotrop Ichthyol. 2011; 9(1):1–48. https://doi.org/10.1590/S1679-62252011000100001
Chow S, Hazama K. Universal PCR primers for S7 ribosomal protein gene introns in fish. Mol Ecol. 1998; 7(9):1255–56.
Cramer CA, Liedke AMR, Bonatto SL, Reis RE. The phylogenetic relationships of the Hypoptopomatinae and Neoplecostominae (Siluriformes: Loricariidae) as inferred from mitochondrial cytochrome c oxidase I sequences. Bull Fish Biol. 2007; 9(1/2):51–59.
Delapieve MLS, Carvalho TP, Reis RE. Species delimitation in a range‐restricted group of cascudinhos (Loricariidae: Epactionotus) supports morphological and genetic differentiation across coastal rivers of southern Brazil. J Fish Biol. 2020; 97(6):1748–69. https://doi.org/10.1111/jfb.14538
Dias MS, Oberdorff T, Hugueny B, Leprieur F, Jézéquel C, Cornu JF et al. Global imprint of historical connectivity on freshwater fish biodiversity. Ecol Lett. 2014; 17(9):1130–40. https://doi.org/10.1111/ele.12319
Doyle JJ, Doyle JL. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem Bull. 1987; 19(1):11–15.
Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004; 32(5):1792–97. https://doi.org/10.1093/nar/gkh340
Excoffier L, Laval G, Schneider S. Arlequin (version 3.0): an integrated software package for population genetics data analysis. Evol Bioinform Online. 2005; 1:47–50. https://doi.org/10.1177%2F117693430500100003
Fan H, Zhang Q, Rao J, Cao J, Lu X. Genetic Diversity–Area relationships across bird species. Am Nat. 2019; 194(5):736–40. https://doi.org/10.1086/705346
Folmer O, Black M, Hoeh W, Lutz R, Vrijenhoek R. DNA primers for the amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol Mar Biol Biotechnol. 1994; 3:294–99.
Fricke R, Eschmeyer WN, van der Laan R. Eschmeyer’s catalog of fishes: genera, species, references [Internet]. San Francisco: California Academy of Science; 2021. Available from: http://researcharchive.calacademy.org/research/ichthyology/catalog/fishcatmain.asp
Fu YX. Statistical tests of neutrality of mutations against population growth, hitchhiking and background selection. Genetics. 1997; 147(2):915–25. https://doi.org/10.1093/genetics/147.2.915
Hasegawa M, Kishino H, Yano T. Dating the human-ape splitting by a molecular clock of mitochondrial DNA. J Mol Evol. 1985; 22:160–74. https://doi.org/10.1007/BF02101694
Hirschmann A, Fagundes NJR, Malabarba LR. Ontogenetic changes in mouth morphology triggers conflicting hypotheses of relationships in characid fishes (Ostariophysi: Characiformes). Neotrop Ichthyol. 2017; 15(1):e160073. http://dx.doi.org/10.1590/1982-0224-20160073
Hirschmann A, Malabarba LR, Thomaz AT, Fagundes NJR. Riverine habitat specificity constrains dispersion in a Neotropical fish (Characidae) along Southern Brazilian drainages. Zool Scr. 2015; 44(4):374–82. https://doi.org/10.1111/zsc.12106
Lanfear R, Frandsen PB, Wright AM, Senfeld T, Calcott B. PartitionFinder 2: new methods for selecting partitioned models of evolution for molecular and morphological phylogenetic analyses. Mol Biol Evol. 2016; 34(3):772–73. https://doi.org/10.1093/molbev/msw260
Li WLS, Drummond AJ. Model averaging and Bayes factor calculation of relaxed molecular clocks in Bayesian phylogenetics. Mol Biol Evol. 2011; 29(2):751–61. https://doi.org/10.1093/molbev/msr232
Librado P, Rozas J. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics. 2009; 25(11):1451–52. https://doi.org/10.1093/bioinformatics/btp187
Lima SMQ, Berbel-Filho WM, Araújo TFP, Lazzarotto H, Tatarenkov A, Avise JC. Headwater capture evidenced by paleo-rivers reconstruction and population genetic structure of the armored catfish (Pareiorhaphis garbei) in the Serra do Mar mountains of southeastern Brazil. Front Genet. 2017; 8(199):1–8. https://doi.org/10.3389/fgene.2017.00199
Lucena CA, Calegari B, Pereira E, Dallegrave E. O uso de óleo de cravo na eutanásia de peixes. Bol Soc Bras Ictiol. 2013; 105:20–24.
Malabarba LR, Carvalho-Neto P, Bertaco VA, Carvalho TP, Santos JF, Artioli LGS. Guia de identificação dos peixes da bacia do rio Tramandaí. Porto Alegre: Via Sapiens; 2013.
Menezes NA. Implications of the distribution patterns of the species of Oligosarcus (Teleostei, Characidae) from central and southern South America. In: Vanzolini PE, Heyer WR, editors. Proceedings of a Workshop on Neotropical Distribution Patterns. Rio de Janeiro: Academia Brasileira de Ciências; 1988. p.295–304.
Mittermeier RA, Fonseca GAB, Rylands AB, Brandon K. A brief history of biodiversity conservation in Brazil. Conserv Biol. 2005; 19(3):601–07. https://doi.org/10.1111/j.1523-1739.2005.00709.x
Morellato LPC, Haddad CFB. Introduction: The Brazilian Atlantic Forest. Biotropica. 2000; 32(4b):786–92. http://dx.doi.org/10.1111/j.1744-7429.2000.tb00618.x
Nelson JS, Grande TC, Wilson MVH. Fishes of the World. Hoboken: John Wiley & Sons; 2016.
Papadopoulou A, Anastasiou I, Spagopoulou F, Stalimerou M, Terzopoulou S, Legakis A, Vogler AP. Testing the species–genetic diversity correlation in the Aegean archipelago: toward a haplotype-based macroecology? Am Nat. 2011; 178(2):241–55. https://doi.org/10.1086/660828
Papadopoulou A, Knowles LL. Toward a paradigm shift in comparative phylogeography driven by trait-based hypotheses. Proc Natl Acad Sci U S A. 2016; 113(29):8018–24. https://doi.org/10.1073/pnas.1601069113
Pereira EHL, Reis RE. Revision of the loricariid genera Hemipsilichthys and Isbrueckerichthys (Teleostei: Siluriformes), with descriptions of five new species of Hemipsilichthys. Ichthyol Explorat Freshw. 2002; 13(2):97–146.
Radinger J, Wolter C. Patterns and predictors of fish dispersal in rivers. Fish Fish. 2014; 15(3):456–73. https://doi.org/10.1111/faf.12028
Rambaut A, Drummond AJ, Xie D, Baele G, Suchard MA. Posterior summarization in Bayesian phylogenetics using Tracer 1.7. Syst Biol. 2018; 67(5):901–04. https://doi.org/10.1093/sysbio/syy032
Reis RE, Britski HA, Britto MR, Buckup PA, Calegari BB, Camelier P et al. Poor taxonomic sampling undermines nomenclatural stability: A reply to Roxo et al. (2019). Zootaxa. 2019; 4701(5):497–500. http://dx.doi.org/10.11646/zootaxa.4701.5.10
Ribeiro AC. Tectonic history and the biogeography of the freshwater fishes from the coastal drainages of eastern Brazil: an example of faunal evolution associated with a divergent continental margin. Neotrop Ichthyol. 2006; 4(2):225–46. https://doi.org/10.1590/S1679-62252006000200009
Rodrigues MT. The conservation of Brazilian reptiles: challenges for a megadiverse country. Conserv Biol. 2005; 19(3):659–64. https://doi.org/10.1111/j.1523-1739.2005.00690.x
Roxo FF, Albert JS, Silva GSC, Zawadzki CH, Foresti F, Oliveira C. Molecular phylogeny and biogeographic history of the armored Neotropical catfish subfamilies Hypoptopomatinae, Neoplecostominae and Otothyrinae (Siluriformes: Loricariidae). PLoS One. 2014; 9(8):e105564. https://doi.org/10.1371/journal.pone.0105564
Roxo FF, Lujan NK, Tagliacollo VA, Waltz BT, Silva GSC, Oliveira C, Albert JS. Shift from slow-to fast-water habitats accelerates lineage and phenotype evolution in a clade of Neotropical suckermouth catfishes (Loricariidae: Hypoptopomatinae). PLoS One. 2017; 12(6):e0178240. https://doi.org/10.1371/journal.pone.0178240
Roxo FF, Ochoa LE, Sabaj MH, Lujan NK, Covain R, Silva GSC et al. Phylogenomic reappraisal of the Neotropical catfish family Loricariidae (Teleostei: Siluriformes) using ultraconserved elements. Mol Phylogen Evol. 2019; 135:148–65. https://doi.org/10.1016/j.ympev.2019.02.017
Schaefer SA. The Neotropical cascudinhos: systematics and biogeography of the Otocinclus catfishes (Siluriformes: Loricariidae). Proc Acad Nat Sci Phila. 1997; 148:1–120.
Shelley JJ, Swearer SE, Dempster T, Adams M, Le Feuvre MC, Hammer MP, Unmack PJ. Plio‐Pleistocene sea‐level changes drive speciation of freshwater fishes in north‐western Australia. J Biogeogr. 2020; 47(8):1727–38. https://doi.org/10.1111/jbi.13856
Souza MS, Thomaz AT, Fagundes NJ. River capture or ancestral polymorphism: an empirical genetic test in a freshwater fish using approximate Bayesian computation. Biol J Linn Soc Lond. 2020; 131(3):575–84. https://doi.org/10.1093/biolinnean/blaa140
Tajima F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics. 1989; 123(3):585–95.
Tamura K, Nei M. Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. Mol Biol Evol. 1993. 10(3):512–26. https://doi.org/10.1093/oxfordjournals.molbev.a040023
Tedesco PA, Leprieur F, Hugueny B, Brosse S, Dürr HH, Beauchard O et al. Patterns and processes of global riverine fish endemism. Glob Ecol Biogeogr. 2012; 21(10):977–87. https://doi.org/10.1111/j.1466-8238.2011.00749.x
Thomaz AT, Carvalho TP, Malabarba LR, Knowles LL. Geographic distributions, phenotypes, and phylogenetic relationships of Phalloceros (Cyprinodontiformes: Poeciliidae): Insights about diversification among sympatric species pools. Mol Phylogenet Evol. 2019; 132:265–74. https://doi.org/10.1016/j.ympev.2018.12.008
Thomaz AT, Knowles LL. Flowing into the unknown: inferred paleodrainages for studying the ichthyofauna of Brazilian coastal rivers. Neotrop Ichthyol. 2018; 16(3):e180019. https://doi.org/10.1590/1982-0224-20180019
Thomaz AT, Knowles LL. Common barriers, but temporal dissonance: Genomic tests suggest ecological and paleo‐landscape sieves structure a coastal riverine fish community. Mol Ecol. 2020; 29(4):783–96. https://doi.org/10.1111/mec.15357
Thomaz AT, Malabarba LR, Bonatto SL, Knowles LL. Testing the effect of palaeodrainages versus habitat stability on genetic divergence in riverine systems: study of a Neotropical fish of the Brazilian coastal Atlantic Forest. J Biogeogr. 2015; 42(12):2389–401. https://doi.org/10.1111/jbi.12597
Thomaz AT, Malabarba LR, Knowles LL. Genomic signatures of paleodrainages in a freshwater fish along the southeastern coast of Brazil: genetic structure reflects past riverine properties. Heredity. 2017; 119(4):287–94. https://doi.org/10.1038/hdy.2017.46
Tschá MK, Bachmann L, Abilhoa V, Boeger WA. Past connection and isolation of catchments: The sea-level changes affect the distribution and genetic variability of coastal freshwater fishes. Estuar Coast Shelf Sci. 2017; 190:31–39. https://doi.org/10.1016/j.ecss.2017.02.030
Weitzman SH, Menezes NA, Weitzman MJ. Phylogenetic biogeography of the Glandulocaudini (Teleostei: Characiformes, Characidae) with comments on the distributions of other freshwater fishes in eastern and southeastern Brazil. In: Vanzolini PE, Heyer WR, editors. Proceedings of workshop on Neotropical distribution patterns. Rio de Janeiro: Academia Brasileira de Ciências; 1988. p.379–427.
Wendt EW, Silva PC, Malabarba LR, Carvalho TP. Phylogenetic relationships and historical biogeography of Oligosarcus (Teleostei: Characidae): Examining riverine landscape evolution in southeastern South America. Mol Phylogenet Evol. 2019; 140:106604. https://doi.org/10.1016/j.ympev.2019.106604
Whiteley AR, Spruell P, Allendorf FW. Ecological and life history characteristics predict population genetic divergence of two salmonids in the same landscape. Mol Ecol. 2004; 13(12):3675–88. https://doi.org/10.1111/j.1365-294X.2004.02365.x
 Laboratório de Ictiologia, Departamento de Zoologia, Universidade Federal do Rio Grande do Sul, Avenida Bento Gonçalves, 9500, 91501-970 Porto Alegre, RS, Brazil. (NLP) firstname.lastname@example.org (corresponding author).
 Laboratorio de Ictiología, Unidad de Ecología y Sistemática (UNESIS), Departamento de Biología, Facultad de Ciencias, Pontificia Universidad Javeriana, Carrera 7 N° 43-82, Bogotá D.C., Colombia (TPC current address). (TPC) email@example.com.
Nathália Luiz Pio: Investigation, Methodology, Resources, Writing-original draft, Writing-review and editing.
Tiago P. Carvalho: Investigation, Methodology, Project administration, Resources, Writing-original draft, Writing-review and editing.
Fish expeditions were done with permits (SISBIO/ICMBio #9318–1, 9220–1, 8796–1). All fishes were euthanized using clove oil – eugenol (following Lucena et al., 2013).
The authors declare no competing interests.
How to cite this article
Pio NL, Carvalho TP. Evidence on the paleodrainage connectivity during Pleistocene: Phylogeography of a hypoptopomatine endemic to southeastern Brazilian coastal drainages.Neotrop Ichthyol. 2021; 19(2):e200128. https://doi.org/10.1590/1982-0224-2020-0128
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© 2021 The Authors.
Diversity and Distributions Published by SBI
Submitted November 16, 2020
Accepted February 26, 2021 by Marcelo Britto
Epub Jun 21, 2021