Received: 17 May 2019 Revised: 12 June 2020 Accepted: 16 June 2020 DOI: 10.1002/aqc.3425

RESEARCH ARTICLE

Dammed river: Short- and long-term consequences for fish species inhabiting a river in a Mediterranean climate in central Chile

Caren Vega-Retter1,2 | Pablo Muñoz-Rojas1,3 | Noemi Rojas-Hernández1,2 | Sylvia Copaja4 | Luis Flores-Prado5 | David Véliz1,2

1Departamento de Ciencias Ecológicas and Instituto de Ecología y Biodiversidad (IEB), Abstract Universidad de Chile, Santiago, 7800003, Chile 1. The presence of a dam disturbs river flow, which in turn directly affects the com- 2 Núcleo Milenio de Ecología y Manejo munities and evolutionary potential of riverine species. To detect the ecological Sustentable de Islas Oceánicas (ESMOI), Departamento de Biología Marina, Universidad effects of a dam on genetic diversity, genetic structure, and their progress in time, Católica del Norte, Coquimbo, Chile two riverine fishes living upstream and downstream of an irrigation reservoir were 3GHD Ingenieros Consultores, Santiago, Chile studied at two periods after its construction in 2004 in central Chile. 4Departamento de Química, Universidad de Chile, Santiago, Chile 2. Samples of the Neotropical silverside Basilichthys microlepidotus and the pencil 5Instituto de Entomología, Universidad catfish Trichomycterus areolatus were obtained 2 and 7 years after the Corrales Metropolitana de Ciencias de la Educación, Dam was built. The microsatellite DNA variability of both species upstream and Santiago, Chile downstream of the dam was analysed. 3. Fish analysed 2 years after dam construction did not show genetic differences Correspondence David Véliz, Departamento de Ciencias between upstream and downstream populations; however, fish obtained 7 years Ecológicas, Facultad de Ciencias, Universidad after dam construction showed differences between populations above and de Chile, Las Palmeras 3425, Ñuñoa, Santiago, 7800003, Chile. below the dam and differences from individuals collected 5 years earlier. Email: [email protected] 4. The current effective population sizes of both species were smaller in samples Funding information obtained upstream than in samples obtained downstream. Simulations showed a Basal Grant, Grant/Award Number: PFB 023; migration equal to zero as most probable after reservoir construction, suggesting Chilean Millennium Initiative, Grant/Award Number: ESMOI; CONICYT-FONDEQUIP, that the dam is an impermeable barrier to the movement of individuals of these Grant/Award Number: EQM150077; Fondo species. These results showed that population fragmentation in time could be Nacional de Desarrollo Científico y Tecnológico, Grant/Award Number: 11150213 related to the barrier imposed by the dam. 5. In a scenario of no new contact between populations located upstream and downstream of the dam, the simulation predicts a reduction of genetic diversity ranging from 3.98 to 8.09% over the next 60 years. 6. Analyses suggest that the Corrales Reservoir may be affecting the evolutionary potential of the populations upstream and downstream from the dam.

KEYWORDS Basilichthys microlepidotus, effective population size, genetic diversity, irrigation reservoir, population genetic structure, Trichomycetrus areolatus

Aquatic Conserv: Mar Freshw Ecosyst. 2020;1–15. wileyonlinelibrary.com/journal/aqc © 2020 John Wiley & Sons, Ltd. 1 2 VEGA-RETTER ET AL.

1 | INTRODUCTION Two native resident fish species with wide distribution in Chile inhabit this drainage, but with different habitat use. The limnetic Freshwater systems represent a significant part of the biological riverine Neotropical silverside Basilichthys microlepidotus diversity in the world (Dudgeon et al., 2006), but they are among the (Atheriniformes: Atherinopsidae) is an atherinid endemic to Chile that most affected systems on the planet (Sala et al., 2000): already in the inhabits lakes and rivers from the Copiapó River (27220S) to Chiloé year 2001, 20% of freshwater fish species worldwide were reported Island (41520S) (Véliz et al., 2012). Basilichthys microlepidotus is micro- to be threatened or extinct (Jackson et al., 2001). Human threats such phagous, feeding on insect larvae, small invertebrates, filamentous as over-exploitation, the invasion of alien species, and habitat algae, and detritus (Bahamondes, Soto, & Vila, 1979; Duarte, Feito, fragmentation and degradation adversely affect the conditions of Jara, Moreno, & Orellana, 1971), and its reproductive period ranges populations that live in rivers (Mora, Metzger, Rollo, & Myers, 2007; from August to January (Comte & Vila, 1992). The benthic pencil cat- Myers, 1995) and their conservation status (Clavero, Blanco-Garrido, & fish Trichomycterus areolatus (Siluriformes: Trichomycteridae) inhabits Prenda, 2004). river and stream bottoms (Arratia, 1983) from the Huasco River Habitat fragmentation in freshwater systems is mainly caused by (28150S) to Chiloé Island (Dyer, 2000), feeding mainly on aquatic the construction of dams, which has been one of the largest human insects (Habit, Victoriano, & Campos, 2005), and spawning from interventions in freshwater systems (Dynesius & Nilsson, 1994). September to December (Manriquez, Huaquin, Arellano, & Diverse effects of dams have been documented, including changes in Arratia, 1988). Both species have a generational time of 1 year and the chemical composition of downstream habitats (Copaja are considered ‘vulnerable’ to extinction (Ministerio de Medio et al., 2016; Morais, 2008), changes in downstream temperature Ambiente Chile, 2018). Quezada-Romegialli, Fuentes, and Véliz (2010) affecting the phenology of organisms (McCully, 1996), reduction of suggested that B. microlepidotus migrated after river isolation, the macroinvertebrate condition index (Santucci, Gephard, & probably using coastal water, whereas T. areolatus has probably never Pescitelli, 2005), blockage of the migratory movements of fish migrated among the four rivers studied: it has low genetic differentia- populations (Morita & Yamamoto, 2002), reduction of the physical tion within the Choapa River, suggesting high rates of dispersal of the space inhabited by individuals of natural populations (Apodaca, individuals within this basin when no barriers existed in the river. Both Rissler, & Godwin, 2012; Hall, Jordan, & Frisk, 2011; Leclerc, Mailhot, species inhabited the Camisas River, but after the construction of the Mingelbier, & Bernatchez, 2008), the loss of populations (Morita & Corrales Dam populations were separated upstream and downstream Yamamoto, 2002), genetic differentiation between individuals from the dam. Several years after the Corrales Dam was built, upstream and downstream from dams (Neraas & Spruell, 2001; Rosso physicochemical analysis showed differences in total phosphorus, et al., 2018), and the loss of genetic variability (Nielsen, Carpanzano, iron, copper, and manganese between upstream and downstream Fountain, & Gan, 1997). In particular, the loss of genetic variability sections of the river (Copaja, Muñoz, et al., 2016), and fish showed directly influences the evolutionary potential of the populations higher mercury accumulation upstream compared with downstream (Stockwell, Hendry, & Kinnison, 2003) because it affects their ability from the dam (Copaja, Nuñez, & Veliz, 2016). to adapt to future environmental challenges (van Straalen & The objective of this study was to determine the population Timmermans, 2002). The main consequence for fish populations is the genetic effects of a physical disruption resulting from the presence of change in connectivity between the populations upstream and a dam, and the progression and consequences of these effects over downstream from the dam; however, relatively few studies have time. To do this, the variability of microsatellite loci was analysed in explored the effects of loss of connectivity on genetic diversity and B. microlepidotus and T. areolatus at two different periods – 2006 and population genetic structure, especially how they progress through 2011 – after dam construction, in 2004, in areas upstream and down- time (Balkenhol et al., 2009; Davis, Epps, Flitcroft, & Banks, 2017). stream from the Corrales Dam. The following analyses were con- This information is crucial so that management and conservation plans ducted for each species: (i) changes in population structure during this can be designed and executed according to the current state of the period; (ii) differences in genetic diversity and effective population affected populations. size over time, and between upstream and downstream areas; (iii) the Large dams have been built in central Chile for use in agricultural genetically effective migration rate after the construction of the dam; irrigation because in the Mediterranean climate regime of this area, and (iv) the predicted effect of the barrier on genetic diversity over river flow depends on the yearly snowmelt. One example is the time (changes in allelic richness of these species were simulated Corrales Dam, recently built in the Choapa River basin in 2004, with 30 and 60 generations after dam construction, considering the current a capacity of 50 × 106 m3 and a maximum height of 75 m. This dam migration rate of the system as estimated in point iii). Given that is a concrete-faced rock fill and was built in the middle of a tributary genetic drift could generate changes in the allele frequencies of the (the Camisas River) of the Choapa basin to provide water to the populations over time unrelated to the presence of the reservoir, a agricultural industry of the Choapa Valley during the 10-month dry control system consisting of samples collected in a river basin that season. The dam does not contain a fish passage facility: larvae, does not contain a dam reservoir was included. Fish of the same spe- juveniles, and adults cannot pass over or through the dam, making cies were sampled from this control river over the same period from connectivity between fish populations located upstream and down- three independent locations. This control allowed an assessment of stream almost impossible. whether the changes occurring upstream and downstream from the VEGA-RETTER ET AL. 3 reservoir could result from its presence instead of the effect of drift Wasko, Martins, Oliveira, and Foresti (2003), and tissue samples were over time. obtained by the removal of a small piece of the caudal fin, which was stored in 99% ethanol. To reduce the effect of anaesthesia, fish were maintained for 20 min in clean, oxygenated water before being 2 | MATERIALS AND METHODS released back into the river. The protocols of this study were approved by the ethics committee of the Universidad de Chile and 2.1 | Sampling sites and fish sampling complied with existing laws in Chile (Resolución Exenta no. 2887 Sub- secretaria de Pesca). Table 1 shows the sample sizes per site and date. Fish samples were obtained in 2006 and 2011 upstream and down- stream from the Corrales Dam (Figure 1a,b) and from three sites in the control Maipo River basin: Angostura (ANG), Estero Cancho (EC), 2.2 | Genetic analysis and Puangue (PU) (Figure 1b). Two native Chilean species were collected using a low-impact electrofishing unit, the silverside DNA was obtained using the protocol described by Aljanabi and B. microlepidotus and the catfish T. areolatus. Individuals were Martinez (1997). A total of 10 microsatellite loci were screened for anaesthetized with a 12-mg L−1 dose of M222, as described by the silverside B. microlepidotus: five loci (OD02, OD07, OD09, OD38

FIGURE 1 (a) Corrales Dam. (b) Sampling sites in the Choapa and Maipo river basins. Samples in the Choapa River were obtained above and below the Corrales Reservoir (arrow). Samples from the control Maipo River basin were as follows: ANG, Angostura Stream; EC, Cancho Stream; PU, Puangue Stream 4 VEGA-RETTER ET AL.

TABLE 1 Sample sizes obtained for each fish species, sampling site, and year of sampling

Trichomycterus areolatus Basilichthys microlepidotus

River basin Sampling site 2006 2011 2006 2011 Corrales Reservoir (Choapa River basin) Upstream 24 33 24 33 Downstream 24 37 24 48 Control sites (Maipo River basin) Puangue 12 11 24 24 Estero Cancho 22 6 24 21 Angostura 18 23 14 19 and OD39) described by Beheregaray and Sunnucks (2000) and five between the populations upstream and downstream from the dam loci (OB01, OB19, OB44, 0B59 and OB71) described by Koshimizu and between sampling years were assessed for the Choapa River et al. (2009). These microsatellites were amplified following the basin, whereas in the control basin comparisons were performed protocol described by Muñoz, Quezada-Romegialli, and Véliz (2011). between years only owing to the absence of a dam separating

The 10 microsatellite loci (TR01, TR04, TR06, TR10, TR11, TR14, populations. A paired non-parametric Wilcoxon test implemented in R

TR17, TR21, TR22 and TR24) described by Muñoz-Rojas, Quezada- was used to quantify differences in AR (R Core Team, 2018). Romegialli, and Véliz (2012) were screened for the catfish T. areolatus. All loci were amplified in single reactions. The polymerase chain reaction (PCR) reaction mixture for all 2.4 | Population structure microsatellites had a final volume of 10 μl that included 1.3 μl of 10x PCR buffer (Invitrogen, now ThermoFisher Scientific, Waltham, MA), Two different methods were used to detect possible genetic

0.5 μl of MgCl2 (50 mM) (Invitrogen), 0.5 μl of forward and reverse differences between the upstream and downstream populations and primers (50 ng μl−1) (Applied Biosystems, Foster City, CA), 2.4 μlof possible changes from 2006 to 2011 in the Choapa Reservoir, and deoxyribonucleotide triphosphates (dNTPs) (2.5 mM) (Invitrogen), between years only in sites located in the control basin. Analyses

4.68 μlofH2O, and 0.12 μlofTaq polymerase (Invitrogen). To this included: (i) the genetic difference between pairs of sites or times, −1 mixture, 1.5 μl of DNA solution (50–80 ng μl ) was added. PCR prod- estimated using the fixation index (FST), with significance evaluated ucts were genotyped by Macrogen Inc. (Seoul, Korea); GENEMAKER from 5,000 permutations using GENETIX (Belkhir et al., 2004); and (ii) the

(SoftGenetics Inc., State College, PA) was used to build the matrix Bayesian clustering and assignment algorithm implemented in STRUC- with genotype data. MICRO-CHECKER (van Oosterhout, Hutchinson, TURE (Pritchard, Stephens, & Donnelly, 2000). Bayesian clustering and Wills, & Shipley, 2004) was used to identify possible genotyping mis- assignment was performed using the non-admixture model and the takes and detect the presence of null alleles in the microsatellite data. correlated allele frequencies model. The procedure was run five times Five per cent of the samples were re-amplified to test the microsatel- for each value of K (from K =1toK = 5) using 200,000 iterations with lite error rate per locus. a burn-in of 100,000 Markov chain Monte Carlo (MCMC) iterations. To ensure that the individuals were a random subset of the Ln P(D) values obtained for each K value were compared using population, relatedness was estimated with the rxy index (Queller & STRUCTURE HARVESTER (Earl & von Holdt, 2012). The method of Evanno,

Goodnight, 1989), implemented in IDENTIX (Belkhir, Castric, & Regnaut, and Goudet (2005) and the posterior probability of the

Bonhomme, 2002). Using multilocus genotypic data, IDENTIX estimates K values (Pritchard, Wen, & Falush, 2010) were used to select the relatedness between pairs of individuals within a sample set. The null K that best represents the number of genetic clusters. hypothesis for the random distribution of related individuals in a sample was also tested using 1,000 permutations of the alleles within the respective samples. 2.5 | Effective population size

Historical and contemporary effective population sizes (NE) were esti- 2.3 | Descriptive analysis mated for the populations upstream and downstream from the

Corrales Reservoir. Historical NE values were estimated for samples

The number of alleles per locus and the expected (HE) and observed collected in 2006 using the coalescence method implemented in

(HO) heterozygosity were estimated with GENETIX (Belkhir, Borsa, MIGRATE (Beerli & Felsenstein, 1999), which estimates mutation-scaled Chikhi, Raufaste, & Bonhomme, 2004). With this same software, migration rates (M) and the mutation-scaled population size (θ) for

5,000 genotype permutations were used to test for linkage disequilib- each population over the last 4NE generations. The default settings rium and departures from Hardy–Weinberg equilibrium (HWE). FSTAT were used, except for the following run options: (i) using the Bayesian

(Goudet, 1995) was used to estimate allelic richness (AR). Differences inference module with the Brownian motion mutation model; VEGA-RETTER ET AL. 5

(ii) varying the mutation rate for each locus in the data; (iii) using a observed for the years 2006 and 2011 in this analysis. The following single long chain for the static heating scheme with four temperatures, initial conditions were considered for all simulations: diploid organism, 1.0, 1.5, 3.0 and 100; (iv) sampling 10 replicates each 400,000 steps two sexes, random mating system, two sampling sites, equal number of recorded every 100 steps; and (v) using a burn-in of 100,000 females and males in each generation, island migration model, nine replicates. The uniform prior distributions ranging from 0 to 100 with polymorphic loci for B. microlepidotus and eight polymorphic loci for a Δ of 10 were used for θ and M. The θ value estimated by MIGRATE T. areolatus with free recombination, a microsatellite mutation rate of −3 −3 was used to estimate the NE (θ = xNEμ, where x = 4 for diploid data, 2 × 10 for B. microlepidotus and 3.38 × 10 for T. areolatus, a mixed

NE = effective population size, and μ = mutation rate). A mutation rate model SSM/KAM was used (SSM: this is the single step mutation model of 2 × 10−3 locus/generation was used for B. microlepidotus: this value limited to a finite number of allelic states; KAM: in this model, mutation is an average of the mutation rates estimated for Lepomis marginatus will generate a new allele of any possible allelic state at random). In this (Perciformes) (Mackiewicz, Fletcher, Wilkins, DeWoody, & mixed model, the probability that a mutation event follows a KAM pro- Avise, 2002) and Syngnathus typhle (Syngnathiformes) (Jones, cess must be stated. For each mutation, a random number is drawn and Rosenqvist, Berglund, & Avise, 1999), as both species are phylogeneti- tested against the proportion of KAM, then the mutation follows either cally close to B. microlepidotus (see phylogeny of Actinopterygii in a KAM or a SSM process. A proportion of KAM = 0.3, allele states = 5 Near et al., 2012). A mutation rate of 3.4 × 10−3 locus/generation was for B microlepidotus and 6 for T. areolatus (similar to the mean allele used for T. areolatus: this is an average of the mutation rates estimated numbers observed in this study in 2006), and maximum variability of for Oncorhynchus gorbuscha (Salmoniformes) (Steinberg et al., 2002) the initial population were considered. To obtain a distribution of simu- and Cyprinus carpio (Cypriniformes) (Yue, David, & Orban, 2007). lated FST, the simulations were performed using the following:

MIGRATE analyses were performed at the National Center for High Per- formance Computing (NHLPC) located at the Facultad de Ingeniería, i. The first 200 generations were simulated as if there were no

Universidad de Chile. The historical NE estimates were used to simu- dam, because one population with size = NE was simulated. NE late the genetic effect of the dam upon the fish populations affected. estimated for the samples in 2006 with MIGRATE were used and

The contemporary NE value was estimated with the temporal the migration rates used in this simulation step were estimated method implemented in MLNE (Wang & Whitlock, 2003), using the data with BA3 (Wilson & Rannala, 2003). The means of the migration for the fish collected in 2006 and 2011. MLNE uses the maximum rates estimated for both species for populations upstream and likelihood to estimate the actual NE, assuming a negligible effect of downstream in 2006 were used, i.e. m = 0.188 and m = 0.204 for mutation and selection, random sampling, and that sampling does not the silverside and the catfish, respectively. change the constitution of the population sampled. An estimation of ii. It is supposed that the dam was constructed at generation contemporary effective population sizes was also performed using a 200, splitting the population into two populations, one rep-

Bayesian approximate computation, implemented in ONESAMP 1.2 resenting the fish located upstream, and one representing the fish (Tallmon, Koyuk, Luikart, & Beaumont, 2008). located downstream. The permeability of the dam was tested using different migration rates (m = 0, 0.1, and 0.2). As the generation time of each species is 1 year, each generation repre- 2.6 | Bottlenecks sents 1 year: thus, in the simulation generation 202 represents the year 2006 and generation 207 represents the year 2011. The

The M ratio (Garza & Williamson, 2001) – the total number of alleles simulated FST values from generations 202 and 207 were

(K) divided by the overall range in allele size (R) – was calculated to extracted from each simulation and contrasted with the FST assess the possible occurrence of bottleneck events in the recent past observed for the data (R Core Team, 2018). for all the populations studied. To avoid division by zero when the microsatellite was fixed for a single allele, the modified Garza- Using the m inferred in the first simulation (m = 0), a second

Williamson (GW) index was computed using ARLEQUIN 3.5 (Excoffier & simulation was performed to determine the possible consequences

Lischer, 2010). The estimation of this index does not include a for AR over time. Simulations were run as in points (i) and (ii) above, statistical test; values of M < 0.68 are considered a sign of a recent but AR data were collected for generations 200 (year 2004), 230 (year population bottleneck (Garza & Williamson, 2001). 2034) and 260 (year 2064) after dam construction.

2.7 | Simulations to determine the migration rate 3 | RESULTS and predict genetic diversity loss over time 3.1 | Genetic and descriptive analysis To infer the migration rate after dam construction, a null model was constructed to simulate population structure scenarios for each Nine microsatellite loci were polymorphic for B. microlepidotus and species using EASYPOP (Balloux & Lugon-Moulin, 2002). The distribution eight microsatellite loci were polymorphic for T. areolatus; MICRO- of the simulated FST (1,000 iterations) was compared with the FST CHECKER did not detect the presence of null alleles for the loci analysed. 6 VEGA-RETTER ET AL.

The variability of these loci is shown in Appendix A. The number of found with FST. The analysis suggested K = 2 as the most likely alleles per locus for B. microlepidotus ranged from one (Obo59TUF number of genetic clusters for the silverside B. microlepidotus with the and Odon39) to seven (Obo19TUF, Obo44TUF and Odon09), method of Evanno et al. (2005) and K = 4 with the posterior whereas the number of alleles per locus for T. areolatus ranged from probability of K (Figure 2). No clear pattern could be found with K =2. one (TR01 and TR24) to 16 (TR14 and TR22). Departures from HWE The results showed two clusters when K = 3 and K = 4 were consid- were detected for both species, but deviations were not associated ered, however, with the 2011 upstream population being the only one with any specific locus, sampling period or location. Relatedness showing a difference. For the catfish T. areolatus, K = 2 was suggested values showed no evidence for a high aggregation of related by the method of Evanno et al. (2005) and K = 3 with the posterior individuals in the samples collected: some sites had negative values. probability of K as the most likely number of populations (Figure 3). Hence data for all loci were retained for the analysis. K = 2 showed a clear difference between years (2006 and 2011), and

The Wilcoxon test did not detect differences in the AR between K = 3 also suggested differences in the collection from upstream and upstream and downstream populations from the same sampling year downstream in 2011. The STRUCTURE analysis was performed per site in or comparing upstream or downstream populations between the two the control basin, comparing the two sampling years. The two sampling years for the Choapa River basin for both species, whereas analyses used showed different K values as the most likely number of for the Maipo River basin significant differences were detected only populations; however, the results suggested that for each sampling for the PU site (Table 2). site there was no differentiation between 2006 and 2011 (Appendix A, Figures A1 and A2).

3.2 | Population structure 3.3 | Effective population size and bottlenecks

The FST showed similar results for both species for the Choapa River basin: there were no significant differences between upstream and Historical effective population sizes estimated with MIGRATE showed downstream populations in 2006 (P > 0.05), but significant differences values of NE > 100 (Table 6). The values of contemporary NE obtained were detected in 2011 (P < 0.05) and between the upstream and with the temporal method were lower than the historical NE, and the downstream populations of both sampling times (P < 0.05) (Tables 3 populations inhabiting upstream areas showed lower values than and 4). In contrast, FST did not show significant differences among the those downstream for both species. The NE estimated with control sites comparing the years 2006 and 2011 (P > 0.05), except ONESAMP increased in the populations living downstream of the dam for the catfish, which showed a significant difference in the Angostura from the year 2006 to 2011 but decreased in the upstream Stream (P < 0.05) (Table 5). populations. Although some differences were observed in the mean

When all samples of the Choapa River basin were included (both NE of both fish species, these values were within the confidence sides of the dam and years), STRUCTURE showed results similar to those interval (Table 6).

TABLE 2 Results of the comparison of allelic richness for both species studied

Basilichthys microlepidotus Trichomycterus areolatus

River basin Mean SD P Mean SD P Corrales Reservoir Upstream 2006 3.59 1.81 0.447 4.39 3.02 0.195 (Choapa River) Downstream 2006 3.78 1.92 3.96 2.99 Upstream 2011 3.21 1.64 0.234 4.46 4.89 0.272 Downstream 2011 3.59 1.59 4.60 2.76 Upstream 2006 3.59 1.81 0.080 4.39 3.02 0.547 Upstream 2011 3.21 1.64 4.46 4.89 Downstream 2006 3.78 1.92 0.652 3.96 2.99 0.250 Downstream 2011 3.59 1.59 4.60 2.76 Control sites PU 2006 2.43 1.23 0.022* 2.62 0.9 0.933 (Maipo River) PU 2011 3.36 1.31 2.62 0.91 EC 2006 3.43 1.49 0.675 2.74 0.9 0.999 EC 2011 3.6 1.2 2.73 0.96 ANG 2006 3.13 1.86 0.622 7.72 3.59 0.219 ANG 2006 3.3 1.45 6.67 2.78

Abbreviations: ANG, Angostura; EC, Estero Cancho; PU, Puangue; SD, standard deviation. *P < 0.05. VEGA-RETTER ET AL. 7

TABLE 3 Basilichthys microlepidotus pairwise FST (above diagonal) and P (below diagonal) values for individuals collected upstream and downstream of the Corrales Reservoir in 2006 and 2011

Upstream 2006 Downstream 2006 Upstream 2011 Downstream 2011 Upstream 2006 – 0.007 0.031 0.0006 Downstream 2006 0.267 – 0.029 0.018 Upstream 2011 0.008 0.029 – 0.030 Downstream 2011 0.413 0.066 0.001 –

TABLE 4 Trichomycterus areolatus pairwise FST (above diagonal) and P (below diagonal) values for individuals collected upstream and downstream of the Corrales Reservoir in 2006 and 2011

Upstream 2006 Downstream 2006 Upstream 2011 Downstream 2011 Upstream 2006 – 0.002 0.073 0.037 Downstream 2006 0.339 – 0.080 0.041 Upstream 2011 <0.001 <0.001 – 0.028 Downstream 2011 0.001 <0.001 0.001 –

TABLE 5 Basilichthys microlepidotus and Trichomycterus areolatus Simulations performed to determine the expected allelic richness pairwise FST and P values comparing samples from 2006 and 2011 in after dam construction showed decreasing allelic richness over gener- the control basin (Maipo River) ations in both upstream and downstream populations of both species Basilichthys microlepidotus Trichomycterus areolatus (Figures 6 and 7). The silverside B. microlepidotus population upstream from the dam showed a more pronounced decline in allelic richness, Site FST PFST P however, declining 8.09% over 60 generations after dam construction, PU 0.008 0.205 0.003 0.402 whereas the population downstream lost 3.98% of its allelic richness EC 0.024 0.059 −0.009 0.623 in the 60 generations. The catfish T. areolatus did not show an appar- ANG 0.023 0.056 0.023 0.039* ent difference of allelic richness loss in either population through the Abbreviations: ANG, Angostura; EC, Estero Cancho; PU, Puangue. 60 generations simulated (upstream = 6.43%; downstream = 6.95%). *P < 0.05.

4 | DISCUSSION Significant bottleneck signatures were detected for populations on both sides of the dam and across time periods using the M-ratio The microsatellite data show genetic differentiation in fish test, as well as for the control sites and both time periods for both populations above and below the dam in 2011, 7 years after the species (Table 7). Average M values across all loci ranged from 0.278 Corrales Dam was established; the control basin did not show genetic to 0.637; all values fell well below the critical M value of 0.68, differences over the same period of the study (2006 and 2011). This indicating that both fish species are likely to have experienced recent suggests that the changes in the downstream and upstream population bottlenecks in both basins. populations could be related to the presence of the dam and reservoir. These results suggested that the construction of a dam is related to rapid changes in the fish populations, with changes in the population 3.4 | Simulations structure being detected in both species only a few years after the Corrales Dam was built. Fish population structure driven by the dis-

The observed FST values in the basin with the Corrales Reservoir were ruptive effect of dams has been described in other species worldwide. compared with those obtained from the simulations of the population Examples include Zingel streber in the Danube River (Germany) structure scenarios based on different migration models (m = 0 to 0.2). (Brinker et al., 2017), Salvelinus confluentus in the Clark Fork River

When migration was set to zero (m = 0), the observed FST values in (USA) (Neraas & Spruell, 2001), Percina caprodes in the Cuyahoga both species did not differ from the simulated data distribution, River (USA) (Haponski, Marth, & Stepien, 2007), Thymallus thymallus suggesting that migration between the tributary and downstream is in the Skjern River (Denmark) (Meldgaard, Nielsen, & zero or very close to zero (Figures 4 and 5). The observed FST was Loeschcke, 2003), Etheostoma blennioides in the Grand, Thames and not significantly different using m = 0.1, except for T. areolatus Sydenham rivers (Canada) (Beneteau, Mandrak, & Heath, 2009) ,and in 2006; the FST became highly significant 5 years later with m =0 Salmo trutta in the Nive River (France) (Horreo et al., 2011). Interest- (year 2011). ingly, Dehais, Eudeline, Berrebi, and Argillier (2010) found a pattern 8 VEGA-RETTER ET AL.

FIGURE 2 Genetic structure of the silverside Basilichthys microlepidotus. Clusters were estimated with STRUCTURE using K =1toK =5. STRUCTURE figure for K =2toK = 4 on the left, with the result of the ΔK estimated using the method of Evanno et al. (2005) in the centre, and with the posterior probability of the K presenting the most probable number of populations estimated with the procedure described in STRUCTURE documentation to the right

FIGURE 3 Genetic structure of the catfish Trichomycterus areolatus. Groups were estimated with STRUCTURE software using K =1toK = 5. This figure also shows the results of ΔK estimated using the method of Evanno et al. (2005) and the posterior probability of the K presenting the most probable number of populations estimated with the procedure described in STRUCTURE documentation

TABLE 6 Historical effective population size (NE) estimated with MIGRATE, and mean and 95% confidence interval (95% CI) for the contemporary effective population size estimated with the temporal method (MLNE software)

Basilicthys microlepidotus Trichomycterus areolatus

Historical NE Upstream 2006 155.45 149.00

(MIGRATE) Downstream 2006 182.35 134.56

Contemporary NE Upstream Mean 42.81 35.94 Temporal method 95% CI 22.77–101.75 23.83–61.16

(MLNE) Downstream Mean 101.85 59.38 95% CI 52.89–285.16 36.04–114.17 Bayesian approximation Upstream 2006 Mean 22.08 28.81

(ONESAMP) Downstream 2006 95% CI 15.18–58.88 17.39–87.07 Mean 36.47 18.33 95% CI 22.75–91.40 13.08–32.11 Upstream 2011 Mean 30.29 25.36 95% CI 17.68–82.94 16.43–60.44 Downstream 2011 Mean 61.29 37.56 95% CI 33.74–149.22 21.64–111.05 VEGA-RETTER ET AL. 9

TABLE 7 Migration rate (M) ratios (Garza & Williamson, 2001) for similar to that detected in this study: Squalis cephalus from the the fish species, sites and time periods studied Durance River in France also showed low but significant FST values. Basilicthys Trichomycterus As was described for the control populations of B. microlepidotus and Site microlepidotus areolatus T areolatus, Percina rex showed extensive gene flow in the absence of Corrales Dam Upstream 0.541 0.363 artificial barriers, but high population fragmentation in the presence of 2006 hydroelectric dams and tail waters in Virginia (USA) (Roberts, (Choapa Downstream 0.518 0.408 Angermeir, & Hallerman, 2013); however, other authors did not detect River 2006 any effect of dams on fish populations. For example, Reid, Wilson, basin) Mandrak, and Carl (2008) found little evidence of population structure Upstream 0.531 0.503 change in the black redhorse Moxostoma duquesnei caused by a dam 2011 in the Gran River (Canada). The authors presumed that the permeabil- Downstream 0.573 0.404 ity of that dam promoted an exchange of individuals from both sides 2011 of the dam. Zhao, Chenoweth, Liu, and Liu (2016) showed that Control PU 2006 0.637 0.349 different types of dams produce different levels of fragmentation: (Maipo River EC 2006 0.395 0.351 basin) high hydroelectric dams (with a large drop and larger impoundment capacity) affected population structure more than low dams (with a ANG 2006 0.562 0.289 small drop and low impoundment capacity). The results indicate PU 2011 0.370 0.453 that the Corrales Dam, which can be described as a medium-height EC 2011 0.370 0.278 dam, acts similarly to a high dam (sensu Zhao et al., 2016), ANG 2011 0.375 0.279 preventing the exchange of fish between the upstream and Abbreviations: ANG, Angostura; EC, Estero Cancho; PU, Puangue. downstream areas.

FIGURE 4 Distribution of FST simulated for different reciprocal migration rates (from m =0to m = 0.5) between sites upstream and downstream of the Corrales Reservoir for the silverside Basilichthys microlepidotus. Vertical black lines indicate the observed FST values obtained from empirical data

FIGURE 5 Distribution of FST simulated for different reciprocal migration rates (from m =0to m = 0.5) between sites upstream and downstream of the Corrales Reservoir for the catfish Trichomycterus areolatus. Vertical black lines represent the observed FST values obtained from empirical data 10 VEGA-RETTER ET AL.

FIGURE 6 Box plot of the allelic richness of Basilichthys microlepidotus retained over 60 generations: (a) upstream population; (b) downstream population. Generation 200 represents the date of Corrales Dam construction. The dot inside the box corresponds to the mean value

FIGURE 7 Box plot of the allelic richness of Trichomycterus areolatus retained over 60 generations: (a) upstream population; (b) downstream population. Generation 200 represents the date of Corrales Dam construction. The dot inside the box corresponds to the mean value VEGA-RETTER ET AL. 11

Most studies have been carried out in reservoirs built many years disturbance when the habitat is intact, and also that it is probable that ago, including studies that demonstrated the effect of mediaeval res- the adverse effects of natural events are strengthened by the exis- ervoirs on brown trout Salmo trutta population structure in northern tence of a dam. Europe (Hansen, Limborg, Ferchaud, & Pujolar, 2014). To our knowl- Another effect observed was the difference in effective popula- edge, this study is one of the first with samples obtained in two tion sizes between the populations upstream and downstream of periods only a few years after dam construction, showing a rapid the Corrales Dam. Both species showed lower NE values upstream effect on population genetic structure. Conversely, Cheng, Li, Wu, compared with downstream, suggesting a more pronounced reduc- Hallerman, and Xie (2013) did not detect genetic differentiation tion in the effective population size upstream of the dam. This among bronze gudgeon Coreius heterodon populations above and effect is probably caused by the small size of the river basin above below two dams on the Yangtze River (China); however, the data sug- the dam compared with the river basin below the dam, which con- gest emerging genetic differentiation among populations above and nects with the whole Choapa River basin. Coleman et al. (2018) also below the dams. The first dam, Gezhouba Dam, was constructed in found a lower NE value in the blackfish Gadopsis marmoratus above 1981, allowing unidirectional downstream dispersal, whereas the the barrier compared with below the barrier in the Yarra River Three Gorges Dam (impounded in 2003) blocks bidirectional dispersal (Australia), and a similar pattern was found for juveniles of the lake of Coreius heterodon, and thus is the most probable explanation for sturgeon Acipenser fulvescens on two sides of a dam in the the incipient differentiation of the individuals inhabiting upstream Winnipeg River (Canada) (McDougall, Welsh, Gosselin, Anderson, & reaches. The results of Cheng et al. (2013), as well as the results of Nelson, 2017). our simulations, suggest that the Corrales Reservoir is impermeable to Owing to the damaging effects of dams, restoration programmes migration in both directions, in contrast to other reservoirs where including dam removal have begun in different countries, which is downstream migration is possible (Neraas & Spruell, 2001). This points very important for the restoration of the normal course of rivers, to a need to develop conservation strategies in which the first step allowing the restoration of habitat connectivity (Bednarek, 2001; Hill, could be to identify potential reserves for the endemic fish species Trueman, Prévost, Arden, & Grant, 2019), free movement of fish among the tributaries of the river above the Corrales Dam, as was (Kanehl & Lyons, 1997), and for improving their conservation status, performed for the Three Gorges Dam (Park, Chang, Lek, Cao, & regardless of whether they are residents or migrants. The construction Brosse, 2003). of dams continues in areas with Mediterranean climates, however, The results of this study also revealed evidence of changes in mainly to retain water in dry periods in order to ensure water supply effective population size, with the current value lower than the histor- for the agricultural industry. The recent construction of dams in cen- ical estimate, together with evidence of a recent bottleneck event in tral Chile allowed the collection of samples soon after the construc- all populations. Although other studies have related habitat fragmen- tion of one of these dams. It was possible, therefore, to describe the tation to changes in population size (Alo & Turner, 2004) and to a bot- changes produced in populations of B. microlepidotus and T areolatus, tleneck (Keyghobadi, 2007) in natural populations, it is not possible to which occurred over a fairly short time, probably because of the relate these changes to the presence of the dam alone. In the same impermeability of the dam and the restriction of movement of individ- sense, bottleneck events were detected for both species in the three uals both upstream and downstream of the dam. The simulations per- separate sites of the control basin that do not contain a reservoir. formed predict that this restriction will lead to a reduction in the Rivers in areas of Chile with a Mediterranean climate depend upon genetic variability of both species over a relatively short period of the accumulation of snow during winter, with high flow occurring dur- time (60 years). This prediction is relevant because: (i) the low number ing winter and spring, and with low flow occurring during summer and of alleles detected for both species means that a loss of 3.98–8.09% autumn. This geographical area is directly affected by El Niño and in allelic richness could have adaptive consequences for these La Niña events, with drought occurring during a La Niña event. This populations, and (ii) possible impacts may already have been gener- variation might affect population sizes cyclically during periods of low ated by some older reservoirs built in the area (e.g. the Recoleta flow by reducing the number of individuals in the populations. Natural Reservoir built in 1934, the La Paloma Reservoir built in 1966, and the causes could lead to these results, but it is important to note that: Cogotí Reservoir built in 1939). Other studies also found similar (i) no differentiation was detected in the control basin; (ii) the control results when the future effects of dams or other barriers were simu- Maipo River basin is one of the most perturbed in the country, with lated. For example, Coleman et al. (2018) showed a loss of variability 40% of the Chilean population living nearby and a large number of in <25 generations above the barrier, and Mona, Ray, Arenas, and industries close to the river (Dirección General de Aguas, 2004), which Excoffier (2014) found a loss in only 10 generations. Barrier effects also could be associated with bottleneck events for fish populations over 100 generations could have an impact on local genetic diversity inhabiting the three independent sites studied; and (iii) simulations for and population structure, however. The quantitative assessment of the Choapa River basin confirm that the observed data could occur genetic diversity within and between populations is important for the under the scenario of a migration rate of zero. All of this suggests that elaboration of genetic conservation plans (Eding, Crooijmans, the presence of the dam is the most likely explanation for the changes Groenen, & Meuwissen, 2002); the results of this study predict impor- observed in the populations of both fish species. It is important to tant reductions in the genetic diversity of both species that would take into account that fish populations respond better to any kind of affect their persistence and conservation in the long term. Therefore, 12 VEGA-RETTER ET AL. the construction of fish passes or the active translocation of individ- Alo, D., & Turner, T. F. (2004). Effects of habitat fragmentation on uals upstream and downstream could address the increasing differen- effective population size in the endangered Rio Grande silvery minnow. Conservation Biology, 19, 1138–1148. https://doi.org/10. tiation of populations and the reduction of genetic diversity on both 1111/j.1523-1739.2005.00081.x sides of the Corrales Dam. This measure could have significant Apodaca, J. J., Rissler, L., & Godwin, J. (2012). Population structure and impacts, especially for the silverside population upstream of the gene flow in a heavily disturbed habitat: Implications for the manage- Corrales Dam, which has the greatest predicted reduction in genetic ment of the imperiled Red Hills salamander (Phaeognathus hubrichti). Conservation Genetics, 13, 913–923. https://doi.org/10.1007/s10592- diversity. Different types of fish-passage structures have been tested 012-0340-3 for species with different habitat use: for example, for Galaxias Arratia, G. (1983). Preferencias de hábitat de peces siluriformes de aguas maculatus in New Zealand (Baker & Boubee, 2006) and for Lampetra continentales de Chile (Fam. Diplomystidae y Trichomycteridae). Stud- tridentate in the Columbia River (USA) (Moser, Keefer, Pennington, ies on Neotropical Fauna and Environment, 18, 217–237. https://doi. org/10.1080/01650528309360637 Ogden, & Simonson, 2011). Pompeu, Agostinho, and Pelicice (2012) Bahamondes, I., Soto, D., & Vila, I. (1979). Hábitos alimentarios de las pointed out that most facilities have been considered ineffective for especies de Atherinidae del Embalse Rapel. Medio Ambiente, 4,3–18. conservation purposes and proposed a new way to estimate fish-pass (in Spanish) efficiency for South American rivers based on the capacity to maintain Baker, C. F., & Boubee, J. A. T. (2006). Upstream passage of inanga viable populations, meaning a positive trend in abundance. It has not Galaxias maculatus and redfin bullies Gobiomorphus huttoni over artificial ramps. Journal of Fish Biology, 69, 668–681. https://doi.org/ yet been ascertained whether this would be effective in maintaining 10.1111/j.1095-8649.2006.01138.x the genetic cohesion of populations, however. Therefore, if a fish pass Balkenhol, N., Gugerli, F., Cushman, S. A., Waits, L. P., Coulon, A., is constructed in the Corrales Dam it will be important not only to Arntzen, J. W., … Wagner, H. H. (2009). Identifying future research undertake a long-term study to determine its effectiveness in popula- needs in landscape genetics: Where to from here? Landscape Ecology, 24, 455–463. https://doi.org/10.1007/s10980-009-9334-z tion recovery, but also to estimate its ability to reduce the impact of Balloux, F., & Lugon-Moulin, N. (2002). The estimation of population the dam on the genetic diversity of upstream and downstream differentiation with microsatellite markers. Molecular Ecology, 11, populations. Reservoirs are necessary to facilitate many human activi- 155–165. https://doi.org/10.1046/j.0962-1083.2001.01436.x ties; however, measures that prevent the discontinuity of aquatic Bednarek, A. T. (2001). Undamming rivers: A review of ecological impacts of dam removal. Environmental Management, 27, 803–814. https://doi. populations must be considered to prevent these populations from org/10.1007/s002670010189 losing their genetic variability and evolutionary potential. Beerli, P., & Felsenstein, J. (1999). Maximum-likelihood estimation of migration rates and effective population numbers in two populations ACKNOWLEDGEMENTS using a coalescent approach. Genetics, 152, 763–773. Beheregaray, L., & Sunnucks, P. (2000). Microsatellite loci isolated The authors thank Basal Grant PFB 023, ICM P05–002 and the from Odontesthes argentinensis and the O. perugiae species group – Chilean Millennium Initiative, ESMOI. Authors also thank CONICYT and their use in other South American silverside fish. Molecular FONDEQUIP EQM150077 and the supercomputing Infrastructure of Ecology, 9, 629–644. https://doi.org/10.1046/j.1365-294x.2000. the NLHPC (ECM-02). CVR thanks Fondo Nacional de Desarrollo 00882.x Belkhir, K., Borsa, P., Chikhi, L., Raufaste, N., & Bonhomme, F. (2004). Científico y Tecnológico (Fondecyt) N11150213. We thank C. GENETIX 4.05. logiciel sous Windows TM pour la genétique des Quezada-Romegialli for catfish data, and R. Gauci, S. Scott, and M. populations. Laboratoire Génome, Populations, Interactions, CNRS Espinoza for their help during fieldwork. UPR 5000. Université de Montpellier II, Montpellier (France). Belkhir, K., Castric, V., & Bonhomme, F. (2002). Identix, a software to test CONFLICT OF INTEREST for relatedness in a population using permutation methods. Molecular Ecology Notes, 2, 611–614. https://doi.org/10.1046/j.1471-8286. None declared. 2002.00273.x Beneteau, C. L., Mandrak, N. E., & Heath, D. D. (2009). The effects of river AUTHOR CONTRIBUTIONS barriers and range expansion on the population genetic structure and PM-R and DV conceived and designed the experiments. Laboratory stability in greenside darter (Etheostoma blennioides) populations. Conservation Genetics, 10, 477–487. https://doi.org/10.1007/s10592- analysis was performed by CV-R, NR-H and PM-R. CV-R, NR-H, 008-9627-9 PM-R, and DV analysed the data. CV-R, DV, SVC, and LF-P contrib- Brinker, A., Chucholl, C., Behrmann-Godel, J., Matzinger, M., uted reagents, materials, or analysis. CV-R, PM-R, DV, SC, NR-H, and Basen, T., & Baer, J. (2017). River damming drives population LF-P wrote the article. CV-R and DV guided the experiments. fragmentation and habitat loss of the threatened Danube streber (Zingel streber): Implications for conservation. Aquatic Conservation: Marine and Freshwater Ecosystems, 28, 587–599. https://doi.org/10. 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