Calotriton asper) along its distribution range, with special emphasis on the distinct habitat types , and the altitudinal and geographical ranges, using a total set of 900 individuals from 44 different localities across the Pyrenean mountain range genotyped for 19 microsatellite loci. We found evidence for a negative longitudinal and positive altitudinal gradient of genetic diversity in C. asper populations. The fact that genetic diversity was markedly higher westwards is in accordance with other Pyrenean species. However, the impact of altitudinal gradient on the genetic diversity seems to differ from other species, and mostly from other amphibians. We found that lower altitudes can act as a barrier probably because the lowlands do not provide a suitable habitat for C. asper. Regarding the distinct habitat types, caves had significantly lower values of genetic diversity compared to streams or lakes. The mean FST value was relatively high (0.304) with maximum values as high as 0.771, suggesting a highly structured total population. Indeed, populations were grouped into five subclusters, the eastern populations (cluster 1) remained grouped into two subclusters and the central-western Pyrenees (cluster 2) into three subclusters. The increase of isolation with geographical distance is consistent with the population structure detected. In conclusion, C. asper seems to be adapted to high altitude mountain habitats, and its genetic diversity is higher in the western Pyrenees. In terms of conservation priority, we consider more relevant the populations that represent a reservoir of genetic diversity.The Pyrenees represent a natural laboratory for biogeographic, evolutionary and ecological research of mountain fauna as a result of the high variety of habitats and the profound effect of the glacial and interglacial periods. There is a paucity of studies providing a detailed insight into genetic processes and better knowledge on the patterns of genetic diversity and how they are maintained under high altitude conditions. This is of particular interest when considering the course of past climate conditions and glaciations in a species which is considered site tenacious, with long generation times. Here we analyzed the genetic patterns of diversity and structure of the endemic Pyrenean brook newt ( Past and contemporary climate conditions have been the main drivers shaping the genetic population structure of species –3. AcrosHarpactocrates ravastellus; [Erebia epiphron; [Rhododendron ferrugineum; [The Pyrenees have played an important role throughout the distinct climatic events acting as a barrier or as a bridge for the migration of species between Europe and the Iberian Peninsula. During glacial periods, the ice sheet rarely descended below 1000 m above sea level (asl) but did not cover the highlands completely , 8. Thesstellus; ), butterugineum; , 12. Theugineum; , 7. Contugineum; , 14. Lonugineum; –19.Epidalea calamita, [Rana temporaria and B. bufo, [R. arvalis, [Calotriton arnoldi) present highly structured and isolated populations [Amphibians are excellent models to explore patterns of gene flow and genetic structure due to their strong habitat-association which is correlated with water availability . Besidesalamita, ; Rana teB. bufo, ; R. arvaarvalis, ). Insteaulations .Calotriton asper as a case study to better understand the role of climatic events and habitat variability in shapping the genetic structure of a mountain species. The Pyrenean brook newt, C. asper, inhabits different habitat types such as streams, alpine lakes and caves at elevations ranging from 360 m asl to 3,000 m asl across the Pyrenees and the pre-Pyrenean mountain chain occupying a geographic distribution range of more than 20.000 km2 [Calotriton asper is classified as near threatened by the International Union for Conservation of Nature [C. asper. In these lakes, C. asper may sometimes be located in the vicinity of the entrance of small streams or in the areas of drainage, where the oxygen content of the water is high [C. asper, a 2-year-long terrestrial dispersal phase is described during its juvenile stage following metamorphosis [Here we use the endemic Pyrenean amphibian species .000 km2 , 28. Calf Nature , 28. Alt is high  distinguorphosis , but it orphosis  suggesteb gene revealed low levels of genetic variation and poorly structured haplotype networks (two main mt-haplotypes with a star-like shape)[et al. [C. asper populations include hypogean and epigean habitats, exhibiting different mating preferences [Previous studies on the Pyrenean brook newt examined its genetic population structure and phylogeography with different molecular markers. The mitochondrial sequence variation of the cytochrome ke shape), 32, 33.ke shape). Isolateke shape). It is eferences , life-hiferences  and metaferences . FurtherCalotriton asper along its entire distribution area covered by 44 sampling localities across the Pyrenean mountain chain and based on 19 species-specific microsatellite loci. Our study aims to (i) characterize the genetic diversity of each C. asper population, (ii) analyze the genetic structure among its populations, (iii) determine whether the genetic patterns are related to a longitudinal and altitudinal gradient or to distinct habitat types, and (iv) whether mountains constitute a natural barrier between French and Iberian C. asper populations.Given the limitation of AFLPs and contrasting patterns by marker type, here we analyze the current genetic patterns of diversity and structure of the Pyrenean brook newt The collection of all samples was conducted under the licenses required by the corresponding authorities. As for the Spanish samplings, permits were given by the following institutions: Departament d’Agricultura, Ramaderia, Pesca Alimentació i Medi Natural of the Catalan Government, with the permission numbers SF/90, SF/91 and SF/429; Servicio de Conservación de la Biodiversidad, Departamento de Desarrollo Rural y Medio Ambiente of the Navarra Government, with the permission number 2012/721; Instituto Aragonés de Gestión Ambiental, Area II-Biodiversidad of Aragon Government, with the permission numbers 24/2009/4323, 24/2010/901, 24/2012/661 and 24/2014/491. As for the French samplings, the present investigation was carried out according to the ethical principles of the French (Ministère de l'Agriculture) and European Convention for the Protection of Vertebrate Animals Used for Experimental and Scientific Purposes  at the Station of Experimental Ecology of Moulis, France (Arrêtés 2009–11 for Haut Garonne and 2009–19 for Ariège).All tissue samples were collected according to the requirements of the above administrative institutions: newts were captured manually and tissue samples were taken with a procedure which does not affect survival and body condition in newts . ImmediaC. asper were analyzed from 44 different localities covering most of its distribution range  correction method. The bootstrap 95% confidence intervals (CI) for the global FST values were calculated using 50,000 replicates over loci. Pairwise linkage disequilibrium between loci and deviations from Hardy–Weinberg equilibrium (HWE) in each population and for each locus were checked using the software GENEPOP version 4.2.1 [The MICRO-CHECKER software  was usedon 4.2.1 .O) and expected heterozygosity (HE) and allelic richness (Ar) using FSTAT version 2.9.3.2 [FIS) following Weir and Cockerham [Genetic diversity was measured for each sampling site as the mean number of alleles (Na), observed  with the universal kriging function and a spherical semivariogram model [In order to visualize spatial patterns of genetic diversity, Ar, Hhttp://www.worldclim.org/) at a scale of 30 arc seconds . Furthermore, to test the prediction that genetic diversity varied across the selected geographical and environmental gradients, univariate linear regressions were implemented between each of these genetic diversity measures  and longitude, altitude and mean temperature of wettest quarter (BIO8). As most of the caves are located in the central-eastern part of the Pyrenees, and in order to exclude a possible interaction between longitude and habitat type, the correlation among longitude and altitude vs the genetic diversities was also measured by testing only streams. An ANOVA with Tukey HSD posthoc tests was used to compare the effect of the three distinct habitat types  to the main genetic diversity measures . In the same way, as habitat types are unevenly distributed along the longitudinal axis, in order to avoid biased comparisons among habitat types due to their longitudinal localization, populations from the central Pyrenees  were considered and tested for effect of the three distinct habitat types as before.PCA was performed using XLSTAT to summarize and visualize the structure of data described by these nine  quantitative variables, using the genetic diversity variables of Ar, HFST as calculated in FSTAT and with Jost’s D [C. asper populations was estimated using a Bayesian approach implemented in STRUCTURE version 2.3.4 [K) ranged from one (complete panmixia) to 45 . STRUCTURE was run for each value of K 10 times, with one million Markov Chain Monte Carlo (MCMC) iterations, discarding the first 105 MCMC steps as burn-in phase. The optimal number of clusters was inferred using ΔK method by Evanno et al. [A, [C. asper, as well as for grouping the sampling localities as indicated by STRUCTURE.The pairwise population divergence between sampling localities was estimated with the Jost’s D  using thJost’s D . To asseJost’s D . The levon 2.3.4 . Settingo et al. , as implo et al. . The aveo et al.  and ploto et al. . In addio et al.  to const al. [A, ) with 10 al. [A, , by perfFST values (see [FST/(1 − FST), and the significance of matrix correlation coefficients was estimated in IBDWS . Genetiservice; ) with 10Ne) for each population was calculated using two single-sample Ne estimators to check for convergent results: COLONY version 2.0.4.4 [Ne. COLONY was run using the maximum likelihood approach for a dioceous/diploid species, with medium length runs and both random and non-random mating, assuming polygamy for both males and females  with no sibship prior. We did not use the option ‘update allelic frequencies’ and other parameters used as default. ONeSAMP employs approximate Bayesian computation and calculates eight summary statistics to estimate Ne from a sample of microsatellite loci genotypes. The analyses were submitted online to the ONeSAMP 1.2 server . A variety of input priors were tested, with minimum Ne as low as 2 and maximum Ne as high as 1,000.In addition, the effective populations size , which means that the impact of null alleles can be neglected. Classical measures of population differentiation are only slightly biased with a null allele frequency ranging between 5% and 8% on average across loci [FST did not vary after excluding null alleles, all loci were kept for further statistical analyses.The highest percentage of null alleles was found for locus Ca16 in the population Barranco de Batisielles , while the average percentage was found to be 7.2% across the 44 populations analyzed. In total, null allele frequency estimates ranged from 0.3% to 7.2% with 2.5% on average across all loci. Global oss loci . Given tp<0.0003).Significant departures from HWE across loci were detected in 8 out of 44 (or 18%) sampling locations. Seven loci showed significant departures from HWE in one to three populations: Ca22 (two populations), Ca16 and Ca20 (three populations each), and Ca3, Us7, Ca5 and Ca25 (one population). These instances likely reflect occasional departures from random mating rather than the presence of null alleles. As none of the loci showed Hardy–Weinberg equilibrium deviations at more than three populations, we retained all loci in the analyses. Linkage disequilibrium was found only in Vidrà (VID) between five pairs of loci  after applying a Bonferroni correction (C. asper (weighted average) were 0.521 and 0.523, respectively (E) and observed heterozygosity (HO) ranged from 0.18 to 0.78 and from 0.18 to 0.72 respectively for all sites . In general, the most diverse populations in terms of Ar and HE were MON and Sarvisé (SAR), both located at the south-eastern Pyrenees, while the least diverse populations were two cave populations, Betharram (BET) and Pas du Loup (PDL) (FIS was estimated to be 0.360 (p<0.005) but was not significantly different from zero for any population after applying Bonferroni’s correction  . Overalltion see . SignifiO and HE) and accounted for 79.7% of their variance. The interpolated values of PC1 mapped into the species’ distribution range revealed a decrease of genetic diversity from the western Pyrenees to the eastern part (The first axis of the PCA (PC1) correlated positively with the genetic diversity variables . Indeed, very high FST values were found in-between eastern and western populations of C. asper, reaching a maximum value of 0.771 for two separately located caves: Pas du Loup (PDL) and Betharram , and a minimum of 0.401 with the remaining localities and a mean of 0.556. The minimum FST value between PDL and the other populations was 0.318 and the mean was 0.509. Most FST values (99% comparisons) were significant at p < 0.05 , a clear peak of deltaK was detected at K = 2  and observed (HO) heterozygosity were also higher in western populations than central-eastern ones . Instead, within eastern Pyrenees  higher values of FST were found (0.262–0.277). The neighbor-joining tree recovered the five groups identified by STRUCTURE , positive relationship between geographical and genetic distances .Mantel tests of isolation by distance (IBD) over all populations revealed a moderated but significant (Ne) resulted, in general, in low values , which C. asper populations across the Pyrenees (weighted average Ar = 2.930 and HE = 0.523) compared to its sister species, the Montseny brook newt, C. arnoldi (weighted average Ar = 3.398 and HE = 0.441)[Euproctus platycephalus on Sardinia  [Microsatellite loci analysis revealed similar levels of genetic variability in  = 0.441). These vHE = 0.6 ) and areHE = 0.6  and refeC. asper . Moreovesturias) , 68.E = 0.609; Rana chensinensis [Euproctus platycephalus [Rana luteiventris [Ambystoma macrodactulym [C. asper seems to prefer cooler and wetter environments at high altitudes than warmer and drier valleys.The most striking result concerning genetic variability in our study was the positive correlation with altitude, i.e. genetic diversity  tended to be higher at high-altitude populations. In fact, maximum values can be observed at an altitudinal range around 1,200 m, but levels still remained high at high-altitude populations . In othiventris ; Ambystodactulym ). HoweveC. asper populations. Populations at the periphery of a species' distribution tend to have lower genetic diversity than the central populations probably attributable to suboptimal habitat, greater isolation, founder effects and/or genetic bottleneck [C. asper. Given that C. asper can be generally seen as a typical cold-adapted mountainous freshwater amphibian species with an optimal elevation range between 1,000–2,000 m asl [Mountains have repeatedly been shown to have strong effects on gene flow in amphibians . Considettleneck , 73. By ttleneck , environ00 m asl , habitat00 m asl ). Along C. asper are found around 1,200 m asl, and the lowest below 700–1,000 m asl. However, regarding genetic diversity levels at high elevations and the cluster structure assembling French and Iberian populations (clusters 1.2 and 2.1), we can assert that high altitude mountains may not be acting as a dispersal barrier in C. asper. There might be enough passages at high altitudes that are suitable for migration during the summer period where temperatures are not too low. Some of the migration, however, will likely occur horizontally in a stretch of a suitable mountain region. Thus, French and Iberian high altitude populations may be genetically connected, but lowlands at both sides of the Pyrenees may constitute a harsh habitat with peripheral and isolated populations.We therefore conclude that the highest levels of genetic diversity of stream populations of C. asper uses caves in the lowlands as a substitute habitat for cold-water streams and individuals became enclosed and isolated from nearby populations. It seems that newts from streams might be dispersing when they ‘fall into the caves’ or enter voluntarily when conditions outside are harsher. The low levels of genetic variability together with the almost absence of private alleles (only in one of the caves) suggested a secondary colonization of lowland caves from neighboring populations rather than being rear-edge remnant populations left from the lowland refugia [The environmental plasticity previously mentioned for this species matches with similar levels of genetic diversity found between lakes and streams. Streams are described as the ‘optimal’ habitat for this species, and high mountain lakes and caves have been seen as secondary habitats . Our res refugia , 76. In  refugia , 74.FST found within C. asper populations are the highest ever found in similar species, considering the revision of Chan and Zamudio [Euproctus platycephalus endemic to the island Sardinia  presents a maximum level of pairwise population differentiation considerably lower than C. asper . Lower  of 0.27 ).C. asper, a 2-year-long terrestrial juvenile dispersal phase was described [C. asper inhabits high-altitude lakes and streams in areas that were recently glaciated, has been also seen as evidence for a high dispersal capacity [C. asper. Accounting for the extremely high values of genetic differentiation found among their populations–similar to what was found with AFLPs [C. asper, as dispersal may be strongly influenced by the presence of surrounding suitable corridors  and Sierra de Guara (SGU), presenting high allelic richness and a high number of private alleles, should be considered as populations of interest for conservation, as they harbor a large proportion of the species’ genetic diversity.Caves as habitats for Ne < 100). An effective population size of 500 has been suggested as a minimum value for the long-term survival of a species, and values around 50 in isolated populations are considered of major concern [Ne around 50 are not unusual for amphibians [C. asper populations were similar or higher than those of the C. arnoldi populations or other urodele amphibians [C. asper populations analyzed had an Ne lower than 10. Populations with a very low Ne are needed to be considered of particular concern, as these populations have an increased probability of extinction resulting from genetic effects, such as inbreeding [Except from Barbarisa (BAR), Oto (OTO) and Ibón de Perramó (IPE), the remaining populations showed low effective population sizes Click here for additional data file.S2 Tablep<0.05. See text, for the codes of the variables.Pearson correlation matrix of environmental and geographical variables. In bold, significant levels of (XLSX)Click here for additional data file.S3 TableCalotriton asper populations. In bold significant levels of p<0.05.Univariate linear regression between genetic diversity and geographical and environmental selected variables of (XLSX)Click here for additional data file.S4 TableO) and expected heterozygosity (HE).ANOVA with Tukey HSD posthoc test among the three distinct habitat types to allelic richness (Ar) observed (H(XLSX)Click here for additional data file.S5 TableFST values among Calotriton asper populations. See p values were <0.05 for all pairs except for those in bold.Pairwise (XLSX)Click here for additional data file.S6 TableCalotriton asper clusters.Results of the isolation by distance analyses  of the five genetic (XLSX)Click here for additional data file.S7 TableNe) for each Calotriton asper population, calculated with two analytical approaches  and using different priors; estimates of the upper and lower 95% CI estimates for each method are indicated.Estimates of effective population size ((XLSX)Click here for additional data file.S8 Table(XLSX)Click here for additional data file.S1 FigCalotriton asper. A) First axis of a principal components analysis (PC1) summarizing the allelic richness, the rarified private allele richness and the observed and expected heterozygosities (positive PC1 scores indicate higher diversity). B) Expected heterozygosity, HE. C) Observed heterozygosity, HO. D) Allelic richness, Ar. E) Rarified private allele richness, Par.Spatial interpolation of the genetic diversity of (TIF)Click here for additional data file.S2 FigO and HE) across the longitude (A) and altitude (B) ranges when only stream Calotriton asper populations were analyzed.Linear regressions between the three genetic diversity indices Click here for additional data file.S3 FigK values calculated by Evanno’s method from the Structure analyses. A) Global dataset of the 44 Calotriton asper populations. B) Western Pyrenean populations, i.e. Cluster 1. C) Central-eastern Pyrenean populations, i.e. Cluster 2.Plot of delta(TIF)Click here for additional data file.S4 FigA distances among the Calotriton asper populations showing the relationships between the five genetic clusters defined by STRUCTURE analysis. As for the population codifications see Neighbor-joining tree using D(TIF)Click here for additional data file.


Schizothorax waltoni, an endemic and endangered tetraploid schizothoracine fish in the Yarlung Tsangpo River (YLTR) on southern margin of Qinghai-Tibet Plateau (QTP), was investigated using two mitochondrial DNA regions and eleven microsatellite loci. Analyses of concatenated sequences of cytochrome b (1141 bp) and the control region (712 bp) revealed high haplotype diversity and moderate nucleotide diversity. High genetic diversity was observed based on microsatellite variation. Both mtDNA and microsatellite analyses revealed significant genetic differentiation between the eastern population (Mainling) and the other four populations to the west, and non-significant genetic differentiation amongst the three central populations in the west. Significant genetic differentiation was observed between the western population (Shigatse) and the three central populations based on microsatellite analyses alone. Bayesian skyline plot analyses showed that S. waltoni experienced a pronounced population expansion 0.05 to 0.10 Ma. Hierarchical structure analyses of microsatellite data indicated that S. waltoni could be split into three groups . The results indicate that three management units should be considered for S. waltoni. Our findings highlight the need for the conservation and effective management of S. waltoni, which is a key member of the endemic and highly threatened fishes of the QTP.The phylogeography of  Most freshwater systems now face multiple threats, all linked to anthropogenic activity, such that freshwater fish populations in many regions are endangered4. Indeed, anthropogenic effects are well documented in terms of localised and global extinctions of freshwater fishes on all human-inhabited continents6, leading to the suggestion that the world has already entered a sixth mass extinction event7.Fishes are the most abundant group of vertebrates, and nearly half of their number are found in freshwater systems that constitute < 0.01% of the earth’s water8. Of these, ~76 species and subspecies belonging to 11 genera occur on the Qinghai-Tibet Plateau (QTP) and its adjacent area9. Karyotype and DNA content analyses indicate that these fishes may be tetraploid, hexaploid or octoploid12. The genus Schizothorax includes 63 valid species13, of which ~40 species and subspecies are found in China14.Schizothoracine fishes (snow trout or snow minnows) consist of 15 genera and >100 species that are mainly distributed in AsiaSchizothorax waltoni Regan 1905 (Cyprinidae: Schizothoracinae), is an endemic tetraploid fish in the Yarlung Tsangpo River (YLTR) on the southern margin of the QTP15. Because limited information is available concerning population trends for this species, S. waltoni is assessed as being of Least Concern in the IUCN Red List of Threatened Species16. However, in the new Red List of China’s Vertebrates17, S. waltoni is assessed as Vulnerable. It is one of the most important commercial fishes of this region and is fished mainly by set gill nets and electrofishing. It is long-lived, cold-adapted, has a slow growth rate, late sexual maturity and low fecundity18, and is therefore especially vulnerable to human activities such as overfishing, biological invasion by exotic fishes and construction of hydroelectric dams20.The Lhasa schizothoracin, 21. However, with the increase of immigrants and tourists from inland areas and the rising demand for fish and fisheries products, overexploitation and illegal fishing are now serious threats to the long-term survival of schizothoracine fishes in Tibet19. Concurrently, many non-native species (e.g. goldfish (Carassius auratus) and topmouth gudgeon (Pseudorasbora parva)) have been introduced into the YLTR and are now out-competing and displacing the endemic schizothoracine fishes20. In addition, ongoing construction of hydroelectric dams has contributed substantially to habitat degradation for endemic fishes. As a consequence, S. waltoni is now threatened by sharp declines in population sizes19. Conservation of the natural populations of S. waltoni is now of primary concern, in particular given the limited geographic distribution of this species.Before the 1950s, schizothoracine fishes in Tibet were indirectly protected due to Tibetan religious belief, with restrictions on fishing and fish eating being imposed by the supreme Tibetan religious authorityS. waltoni, little is known about the genetic diversity and genetic structure of its populations, and the information that does exist is derived indirectly from phylogenetic analyses rather than from population genetic analyses. Understanding the level of genetic diversity and population genetic structure of S. waltoni is important for the effective conservation (e.g. hatchery production of juveniles from appropriate stocks) and management (e.g. restrictions on fishing activities) of the species.Despite the ecological and fisheries importance of b gene (Cyt b) and control region (CR) sequencing and an assessment of eleven polymorphic microsatellite loci to evaluate genetic diversity and genetic differentiation within and amongst populations, and to explore conservation management strategies for this species. The challenge faced by a study such as this when working on a threatened species with limited geographic distribution is to sample individuals from sufficient populations and across as broad a geographic range as possible. The results of this study provide new insights into the population genetic structure of this threatened fish that may contribute to conservation, management and sustainable utilisation of this important species, and which may also help to provide context for other threatened endemic fish species in the same or similar river systems.In the present study, we used mitochondrial DNA (mtDNA) cytochrome b and CR were amplified and sequenced from 114 samples of S. waltoni. Full Cyt b sequences 1141 bp exhibited 21 variable sites, 17 of which were parsimony informative. Partial CR sequences (712 bp) had 28 variable sites, 22 of which were parsimony informative, with no indels. There were 17 Cyt b haplotypes and 28 CR haplotypes defined, and their sequences were submitted to GenBank (Accession numbers MK243405–MK243421 for Cyt b and MK243422–MK243449 for CR). Cyt b and CR sequences from each sample were concatenated into one sequence of 1853 bp (5′-Cyt b + CR-3′) for phylogenetic analysis, to give a total of 37 mtDNA haplotypes in the concatenated data set. Three haplotypes  were shared amongst the five populations  and moderate nucleotide diversity (π = 0.0052) values, respectively  and the other populations  were significantly different from zero after FDR correction , but not between regions  yielded trees with very similar topologies based on concatenated mtDNA  analyses supported the hypothesis of relatively recent population expansion of clade A Figs . BSP revFST loci showed that 11 bands (BayesScan), 11 bands (Arlequin) and 15 bands (Mcheza) were detected as outlier candidates to be under selection , Nei’s gene diversity (H) and Shannon’s information index (I) compared to the other four populations  (Table P < 0.01), but not between regions  statistics reached their largest value at K = 2, respectively, suggesting that there were two subgroups in the five S. waltoni populations  Table . AMOVA rns Table . Nei’s uly Table . STRUCTUons Fig. . These wons Fig.  and the ons Fig.  and amonons Fig.  were conons Fig. , except ons Fig.  and PCoAons Fig. .Table 5MΦST/(1 − ΦST) and Ln(d) for mtDNA sequence variation  and Ln(d) based on microsatellite variation  and S. waltoni in particular , such actions are unlikely to safeguard the long-term future of this species. Whilst identifying threats to freshwater fish biodiversity may be relatively straight forward and have been well documented2, the establishment of strategies to mitigate threats that occur at global scales  is a much harder prospect, and is the real challenge now facing conservation biology.As the largest high-elevation ecosystem in the world, the Qinghai-Tibet Plateau (QTP) is characterised by high species richness and abundant endemic species, and has been identified as one of the most important centres of biodiversity in the world26, S. waltoni exhibits high levels of intra-population genetic diversity. Whilst no obvious population genetic differentiation was identified by analysis of mtDNA sequences, pronounced population structure was observed based on microsatellite analysis. The gradient-like nature of the genetic differentiation (from west to east) observed for the nuclear DNA microsatellite strongly suggests that the result is real and not artefactual, despite the limited number of sites from which it was possible to collect fish. These analyses also clearly identified for the first time three genetically distinct subpopulations: west (SG), central  and east (ML) within the YLTR. Additional sampling in the future from sites in the upstream (western) and downstream (eastern) regions of the YLTR will allow testing of both the major east-west differentiation and also of the three clades.Like other polyploid schizothoracine fishes in Tibet27. Our study, using both mitochondrial and nuclear markers, revealed that genetic variation is relatively high in S. waltoni, despite the threats this species presently faces. The mtDNA results (both genetic variation indices Hd and π) reveal that S. waltoni has high levels of genetic diversity comparable to other schizothoracine fishes found on or around the QTP28. However, when combined, the mtDNA results indicate that S. waltoni falls into a group with a high level of haplotype diversity (Hd > 0.5) and a moderate level of nucleotide diversity (π > 0.005)29, which is different from the genetic diversity pattern (high haplotype diversity but low nucleotide diversity) observed in other schizothoracine fishes28.Genetic diversity has been identified by the IUCN as an important form of biodiversity, deserving conservation within each populationS. waltoni falls between the two previous estimates with which comparison can be made30.Due to the tetraploid inheritance pattern of schizothoracine fishes, few population genetic studies based on microsatellite markers for these fishes have been reported, meaning that judging absolute levels of nuclear DNA diversity is difficult. The mean number of bands per microsatellite locus (24.18) of S. waltoni are indicative of either secondary contact between differentiated lineages or a large stable population with a long evolutionary history29. Differentiating between these two explanations is difficult. The QTP has undergone several periods of pronounced uplift since the Quaternary, creating substantial changes in the climate and the natural environment31 and significantly influencing the distributional ranges of schizothoracine fishes. Secondary contact of formerly isolated S. waltoni populations may therefore have occurred due to the uplift and climate change of the QTP. In support of the second explanation, we note that neutrality tests and mismatch distribution analyses confirmed the likely existence of a stable population with no recent expansion events for S. waltoni.A high level of mtDNA haplotype diversity and a moderate level of nucleotide diversity in S. waltoni and its population genetic structure32.Given their different evolutionary histories, mutation rates, modes of inheritance, and effective population sizes, mtDNA markers are expected to reflect more accurately the historical  situation, whereas nuclear DNA markers are expected to better reflect the contemporary situation. Taken together, the results may be informative in terms of understanding how landscape changes  have influenced the distributions over time of Analysis of concatenated mtDNA sequence data indicated that there was moderate-high and significant genetic differentiation between ML (most easterly population) and the other four upstream populations  which formed an undifferentiated group. However, all five populations had private haplotypes which suggests that there must be some minor barrier to gene flow amongst populations to maintain this low level of differentiation over many generations. In the phylogenetic analyses, two clusters (evolutionary lineages) were identified. However, the haplotypes clustered in one subgroup were not from a specific population, but were from all five populations Fig. .34. Towards the eastern end of the YLTR, between Shannan and Mainling, there is the 30 m high Nierikar Waterfall . This waterfall, which is located at the Jiacha Gorge ), impedes contemporary upstream migration of fishes. However, due to the several glacial lakes impounded by the moraine34, the Nierikar Waterfall might not have impeded past  upstream dispersal of S. waltoni. In the late Pleistocene to early Holocene, these ancient glacial lakes were located at the main stream lying immediately upstream of the Tsangpo Great Gorge35. According to He and Chen34, the surface elevation of these ancient glacial lakes  exceeded the elevation of the Nierikar Waterfall . Therefore, the ancient lakes could have extended to the upper stream of the Jiacha Gorge and the Nierikar Waterfall observed today and would not have prevented the upstream dispersal of S. waltoni in the Pleistocene34. No major cascades or waterfalls are found along the YLTR between Shigatse (SG) and Shannan (SN), and thus there is no impediment to gene flow (connectivity) amongst the populations of S. waltoni within this ~300 km of the river. As a consequence of the river’s morphology and geological history, pronounced mtDNA genetic differentiation was observed between ML  and the four other populations. The divergence times amongst the main clades are correlated with later Kunlun-Huanghe Movement (about 0.6 Ma–1.1 Ma) and the Gonghe Movement (~0.15 Ma)31, results are consistent with the main divergence time reported for S. o’connori in the same region (0.30 Ma–0.43 Ma)23.The shared mtDNA haplotypes and overlapping spatial distributions of the fishes in the two evolutionary lineages most probably reflect a scenario of secondary contact after a period of isolation. Historically, geological events and climate change have significantly influenced the diversity and population genetic structure of endemic organisms on the QTPS. waltoni was identified by analysis of microsatellite variation which reflects contemporary (last few generations) gene flow. Consistent with the mtDNA results, the nuclear DNA results revealed significant genetic divergence between ML in the east and the four upstream (west) populations, and they also revealed small but significant genetic divergence between SG (most western population) and the three central populations . Such discordance between nuclear and mtDNA markers is an oft reported phenomenon36. However, no obvious population genetic structure was found based on the analyses of 257 putatively neutral microsatellite bands. Thus, the genetic signal of differentiation is largely or solely contained within the nine bands that are under putative selection, highlighting the importance of retaining signal-bearing bands  under certain circumstances for quantification of spatial genetic differentiation38. We do, however, note that retention of bands that are putatively under selection will violate some assumptions of neutrality associated with many analyses. In addition, we note that the treatment of codominant microsatellite loci as dominant loci  is unusual but is warranted in the present case given the tetraploid nature of the focal species. Regardless, from a management perspective, the data set is informative because it provides evidence of spatial genetic structure that might otherwise have been overlooked.Pronounced population genetic structure of S. waltoni, whereas a mixed cluster was found in the three central populations . These results were confirmed by the PCoA and by a significant pattern of IBD. This pronounced microsatellite population genetic structure reflects the contemporary erosion of genetic differences that accumulated when the original population of S. waltoni was split into two, and is, in effect, a secondary zone of contact between the two contemporary lineages. In terms of directional gene flow between the two lineages there are no substantial waterfalls along the YLTR in the region of the three central populations  today, although several small waterfalls are found between SG and QX which may act to reduce or prevent gene flow and/or dispersal up the river (from QX and further upstream to SG in the west) but not in the other direction. These results indicate that waterfalls in the far eastern (near ML) and far western (near SG) regions, specifically between the populations SN and ML and between SG and QX, may block contemporary gene flow of S. waltoni, whereas contemporary gene flow is likely to be frequent amongst the three central populations where there are no waterfalls. Clearly, these findings and our interpretation of them, will benefit from further sampling of S. waltoni populations, both in the west, above the Nierikar Waterfall to test clade diversity, and in particular to the east, below the Nierikar Waterfall, from where we presently only have one population. Further sampling in the east will help to quantify just how widely distributed and abundant this fish is in a region that appears to be outside its main range of distribution.The existence of two evolutionary lineages received strong support from the STRUCTURE and BAPS analyses of microsatellite variation, which showed that the SG (most westerly) and ML (most easterly) populations represent two different clusters of K-selected life-history characteristics, S. waltoni is susceptible to growth overfishing and stock depletion39. Because of the inherent difficulties in studying S. waltoni, the biology of the species continues to be poorly understood, a fact that has hampered its effective conservation and allowed for conservation planning only on a local scale (i.e. the Lhasa Wild Fish Protection Regulation).Due to its 40. Additionally, there may be changes in the downstream water quality including river temperature, nutrient load, dissolved gases, heavy metals, and sediments40. Dams may cause habitat loss, change fish reproductive environments, and hinder breeding fish migration, resulting in a substantial decline of fish genetic resources42. In 2014, construction of the Zangmu Dam (with a fish ladder), the first dam on the main stream of the YLTR, was completed. Another seven (at least) dams will be built in the main stream of the YLTR in the future and all seven dams are to be located in the region between SN and ML. These dams will add to the existing natural barrier to fish movement that already exists in this region caused by the Nierikar Waterfall. Existing genetic differences between the lineages may be enhanced by the construction of dams that may further reduce or prevent downstream  movement of fishes even more than the existing Nierikar Waterfall. Although the dam plan includes fish ladders, the success of a fish ladder is unknown and will need to be evaluated over a long time to determine its success, given that even the most efficient protective measures cannot prevent some level of deterioration of ecosystem function42.Fishes of the YLTR face a range of anthropogenic threats, including heavy fishing pressure, habitat loss/modification, climate change and introduced species. Of particular concern, however, is dam construction that is both an immediate and long-term threat to connectivity. The environmental impact of greatest concern is that the dam changes the flow of the river from an upstream river valley to a reservoir43. An ESU is defined as a population that exchanges few migrants with others and that has been geographically isolated for long enough to be genetically distinct and independent43. High genetic differentiation (between ML and the four other populations) but no obvious population structure was observed in S. waltoni based on mtDNA analysis. However, moderate genetic differentiation and pronounced population structure are found based on microsatellite analysis. Because no reciprocal monophyly was found in this study, we propose a single ESU for the five populations of S. waltoni. Given the results of the microsatellite analyses, three groups  should be defined as different MUs worthy of protection as distinct stocks. However, S. waltoni collected from the western region (SG or MG) have been used as broodstock in the artificial reproduction programme at ML. The question arises whether these western parental fish are genetically similar to the local fish in ML and whether the juveniles (used for reintroduction downstream) hatched from the western parents are able to adapt to the area of their release (e.g. ML). Our results clearly show that western S. waltoni  are genetically different from the fish at ML, in the east. As such, we suggest that it is appropriate to cancel, or at least postpone, the further collection of sexually mature S. waltoni from the western region to be used as broodstock for release of juveniles at ML until tools enabling the fitness of individuals to be determined in specific environments become available.Evolutionarily significant units (ESUs) and management units (MUs) are two important concepts in conservation geneticsThere were no specific permits required for the field research in this study. We confirm that there was no involvement of any endangered species in the field sampling. The fish sampling plan and animal research protocol were approved by the animal research oversight committee of Huazhong Agricultural University (HZAU). All experimental protocols were approved by the Institutional Animal Care and Use Committee of HZAU, and all methods were performed in accordance with relevant guidelines and regulations.S. waltoni from as many sites as possible in the YLTR  and Nyang River (NYR)) of the YLTR above the Yarlung Tsangpo Grand Canyon14. However, in our sampling, it was difficult to find S. waltoni in the tributaries , and even in the main channel (e.g. Paizhen). Therefore, based on sampling success rather than on number of sites visited, fish were collected from five populations (Shigatse (SG), Maldrogongkar (MG), Quxu (QX), Shannan (SN) and Mainling (ML)) during 2012 to 2013  and partial control region  were sequenced according to Guo et al.23. Cyt b sequences were amplified using primers L14724 and H1591534, and CR sequences were amplified using DL-F and DL-R23. Cyt b sequences were sequenced in forward and reverse directions, CR sequences were sequenced in the forward direction.Complete cytochrome Hd), nucleotide diversity (π), number of segregating sites (S), number of haplotypes (h), number of nucleotide differences (K), median-joining network and Kimura 2-parameter (K2P) genetic distances between populations were performed/estimated following Guo et al.23. We focussed primarily on the concatenated sequence (Cyt b + CR) results because Cyt b + CR provided most information. Analysis of molecular variance (AMOVA) was carried out using Arlequin 3.545 to test for genetic differentiation amongst populations/regions. 10,000 permutations were performed to examine statistical significance of fixation indices (Φ). Correction for multiple testing was performed using the Benjamini-Yekutieli method false discovery rate (BY-FDR)46, and comparisons were considered significant at P < 0.05.Multiple sequence alignment, haplotype diversity  independently using neighbour-joining (NJ) and maximum likelihood (ML) in MEGA 5.047. Except for the HKY + G (Cyt b), T92 + G (CR) and HKY + G (Cyt b + CR) models used for ML analyses, the other procedures of phylogenetic analysis were carried out following Guo et al.23. S. o’connori (GenBank accession no. KC513575), S. macropogon (KC020113) and Schizopygopsis younghusbandi (KC351895) were used as outgroups.To examine relationships amongst populations and to test for evidence of historical dispersal, phylogenetic analysis was employed based on Cyt b and the concatenated mtDNA data (Cyt b + CR) independently following Guo et al.23, and divergence time amongst the main clades were added on the MCMC trees. Coalescent-based Bayesian skyline plots (BSPs) and mismatch distributions were used to estimate historical population dynamics. BSPs were carried out following Guo et al.23 to estimate the time variation of effective population size to determine demographic history. Mismatch distributions48 were implemented in Arlequin 3.5 and DnaSP 5.149. Tajima’s D and Fu’s Fs tests were performed to test if the two mtDNA sequences accorded with the expectations of neutrality51. The sum of squared deviations (SSD) and the raggedness index (r) were calculated using Arlequin 3.5 to test if sequences deviated significantly from a population expansion model52. All P-values were corrected using the BY-FDR. The population expansion time in years (T) was estimated as described by Guo et al.23. The generation time for S. waltoni was estimated to be 10 years based on age of female maturation18. We only considered female age due to the maternal inheritance of mitochondrial DNA. Mutation rates of Cyt b, CR and Cyt b + CR were assumed to be 1.0%, 3.6% and 1.69% per site per million years, respectively23.Bayesian phylogenetic analyses were performed to build Markov chain Monte Carlo (MCMC) trees with Cyt 23 were selected based on allelic size range, annealing temperature and scoring performance. Primers  or absence (0) for each individual. Each band was considered as a single bi-allelic locus with an amplifiable (dominant) and a null (recessive) allele. To detect candidate bands under selection, the FST outlier method was performed using three softwares: BayeScan 2.154, Arlequin 3.5 and Mcheza55. For BayeScan, we used the default values with respect to the thinning interval, tuning of the proposal distributions, the number of pilot runs, and the uniform prior boundaries for FIS and included a burn-in period of 50,000 iterations and prior odds of the neutral model of 10. Default settings were also used in the Arlequin and Mcheza analyses. The data set was divided in two subgroups, “neutral” and “selected” (outlier) loci following Luikart et al.56. For the neutral data set, we removed the bands putatively identified as outliers, both those classified as under directional and stabilizing selection, by any two of the three methods . All analyses were performed on the all bands and the neutral bands data sets.Eleven microsatellite markersrs Table  were synH), Shannon’s information index (I), the percentage of polymorphic loci (PPL), Nei’s unbiased genetic distance, and the relationships between populations and individuals (PCoA) were evaluated following Guo et al.23. Using the binary data set, a Bayesian clustering analysis was carried out in STRUCTURE 2.357 to determine the expected number of genetic clusters, as described by Guo et al.23. Ten independent runs were performed for each cluster set (K) from 1 to 5. The ΔK metric58 was used to assess the best fitting K through Structure Harvester (http://taylor0.biology.ucla.edu/structureHarvester/) and runs were grouped and visually displayed using CLUMPAK (http://clumpak.tau.ac.il/). To confirm the distribution of individuals amongst genetic groups and verify the adscription of individuals to the clusters revealed by STRUCTURE, we also used the clustering approach implemented in BAPS 6.060. BAPS analyses were carried out on groups of individuals (i.e. site-samples) rather than individuals, with simple model assumptions . BAPS was set with 10 replicate runs for each K (from 2 to 5) and another 100 replicate runs with K fixed to the inferred number of genetic clusters (best K). The best fitting K was assessed using the highest Log marginal likelihood [Log(ML)] value. And then, an admixture model was run for the inferred number of clusters .Genetic diversity indices such as Nei’s gene diversity index (http://genepop.curtin.edu.au/) to investigate whether genetic distance ([ΦST/(1 − ΦST)] for mtDNA data or [FST/(1 − FST)] for microsatellite data) was correlated with geographic distance [Ln(d)] amongst the five populations (Table 61. Significance levels were determined using separate Mantel tests for the mtDNA and microsatellite data sets as implemented in ISOLDE by GENEPOP employing 20,000 permutations.We tested for IBD using GENEPOP (ns Table , as recoSupplementary information for phylogeography of <i>Schizothorax waltoni</i>


In gilthead seabream the number of domesticated individuals increased annually, and escape events occur regularly in the Adriatic Sea. Still there is a lack of population genetic characteristics and evidence of the extent and geographic scale of interbreeding resulting from fish-farm escapees. We screened 1586 individuals using a panel of 21 neutral microsatellite loci in several consecutive years and here report on the medium-scale detection of hybrid and farmed seabream in the natural environment. Wild adults showed a lack of genetic structure within basin and sampling years and reduced connectivity with wild offspring collection, suggesting their temporal residency within the Adriatic. On the contrary, by linking the results of multiannual genetic analyses with the results of coupled hydrodynamic and individual based models (IBM-Ichthyop), we observed a strong connection of wild seabream associated with tuna-aquaculture sites and offspring from the nursery grounds, indicating that the surroundings of tuna sea-cage farms can function as a spawning grounds. The study results present the genetic baseline of wild and farmed strains from the eastern Adriatic Sea, as a first step toward development of a mitigation strategy for fish escapees aimed at controlling further erosion of genetic integrity. Sparus aurata, like the European seabass Dicentrarchus labrax, has been the object of intensive farming and has become the most important marine farmed fish in the Mediterranean1. Following EU trends, gilthead sea bream production in Croatia has increased at a rate of 65% in the past ten years. However, production is still relatively small compared to the rest of the Mediterranean region 2.The gilthead sea bream 4, and elsewhere in the Mediterranean, such as Greece5. Along the eastern Adriatic coast, the highest gilthead seabream landings are noted in late autumn (November-December) in the pre-spawning aggregation period of species, reaching daily catches of several tonnes per purse-seins vessel (pers. comm.). Highly abundant and seasonally stable aggregations of gilthead seabream were observed around semi-offshore tuna farms, and displayed enhanced fitness status due to the high energy trophic resources found at farming sites7. In addition, shellfish farms become also very attractive food source sites for seabream populations3. High mussel losses due to gilthead seabream predation have been reported at shellfish farms along the Adriatic coast, significantly affecting the economic stability of this industry8.Interestingly, in recent years, a significant increase of wild gilthead seabream has been documented in coastal areas of the Adriatic Sea13. Escaped fish have been shown to have detrimental effects on native fish stocks, due to competition for resources, spread of disease, and alteration of genetic diversity due to hybridisation14. Hybridization events may break down locally adapted gene complexes, reduce competitive ability and overall fitness of wild populations15. The impact may be more enhanced in cases when farmed individuals are of a different geographical origin, as is the case in Croatian aquaculture, and/or have experienced strong domestication16.It has been suggested that the rapid expansion of sea-cage farming facilities contributed to the population increase through the escape of fish from sea-cage aquaculture and/or escape of viable, fertilized eggs spawned by farmed fish inside sea-cages, i.e. escapes through spawning20. Annual trend distribution of the Mediterranean sea surface temperature (SST) indicates a warming trend throughout the basin with average values of 0.035 ± 0.007 °C per year21. Thus, it could be argued that wild gilthead seabream, as a subtropical Sparid, is taking advantage of the present climate change in terms of increased larval survival and subsequent recruitment success, but also in establishment at the northern limits of distribution areas 23.On the other hand, ocean warming may also be behind the increasing gilthead seabream abundance. This is currently one of the main driving forces causing changes in species abundance and distribution and, thus, in species biodiversity and functioning of marine ecosystems28. In the case of gilthead seabream, the application of molecular markers is a challenge in detecting escapees and hybrids, since (i) gilthead seabream have been domesticated relative recently, i.e. have a weak selection footprint29; (ii) the high dispersal capacity of this species produces a high exchange of migrants among subpopulations, allowing a large effective subpopulation size and low structuring, and (iii) historical samples are not available for comparison analyses.To date, molecular markers have been successfully employed in the discrimination of fish origins and in identifying hybridization processes among wild and farmed fish30. Thus, this study aimed to: (i) examine the possible changes in genetic variation occurring over the spatial and short-term temporal scale of wild seabream populations from the eastern Adriatic, with special attention on populations sampled around fish farms and their potential impact on recruitments from surrounding nursery grounds, (ii) investigate the genetic structure of farmed populations originating from different hatchery sources and (iii) quantify the presence and magnitude of hybridization between wild and escaped farmed individuals.To explore the genetic population structure and footprints of selection in gilthead seabream populations of different origin (wild vs. farmed) and ontogenetic state (juveniles vs. adults) from the Adriatic Sea, we genetically assayed 1586 individuals with 21 putatively neutral microsatellitesSparus aurata were genotyped at 21 neutral microsatellite loci  (Table vs 7.3), allelic richness (7.3 vs 8.6), observed (0.74 vs 0.76) and expected heterozygosity (0.79 vs 0.81)  in comparison to the wild counterparts. Wild young-of-the-year and farm associated populations followed the genetic diversity pattern observed for the wild group  of detecting a true differentiation of FST = 0.005 under different scenarios of effective population size (Ne) and numbers of generations of drift (t) with 1000 replications , supporting a moderate level of differentiation among individual populations. The highest global FST value of 0.041 was recorded within farmed populations in contrast to the lower levels of global FST observed within the other three population groups: 0.015, 0.010 and 0.009 for the wild, farmed-associated and wild YOY group, respectively. Pairwise FST values among populations are detailed in the Supplementary Table FST comparisons were statistically significant when permuted by Fisher’s exact test. Historical wild samples from 2009 showed high and significant pair-wise differentiation in relation to all populations included in the dataset. The majority of non-significant comparisons were found within adjacent temporal wild populations  sampled through the Adriatic where FST ranged from −0.002 to 0.005. On the contrary, adjacent temporal farm-associated populations from 2015 and 2016 showed a biannual break in gene flow toward the wild populations, except for recently sampled ones from 2017  that also showed no significant pair-wise differentiations with farmed populations of Adriatic origin. Interestingly, farm-associated populations paired with the YOY samples from Adriatic nurseries for both sampled years (−0.002 < FST < 0.009). Only the YOY group sampled in the area under aquaculture impact (16JB) showed gene flow towards France-origin farmed fish (15FF). All farmed populations from different origins showed significant pair-wise differentiations within the group (0.009 < FST < 0.076) and between the rest of populations.The global et al.31 approach. Wild populations sampled within the Adriatic Sea were assigned to five different clusters, of which three clusters were exclusively associated with wild fish origin and two were associated with farmed origins . The YoY population sampled in the area near the finfish aquaculture site (16JB) was assigned to the fourth cluster (red), which also comprised farmed populations of Atlantic origin. Farm-associated adults from 2017 appeared to be admixed with individuals assigned partially to the third wild cluster (orange) and also to the fifth cluster (blue) that comprise farmed populations of Mediterranean origin. Farmed populations originating from western Adriatic broodstock  formed the separate sixth cluster (yellow).Initial Structure analysis of the dataset suggested K = 6 after application of the Evanno ins Fig. . Wild hiWhile no further structure was detected within the adjacent temporal wild populations (orange cluster) and within the adjacent temporal farm-associated populations and YoYs (green cluster), subsequent analysis of each of the cluster of farmed origin (red and blue) resulted in further structure in both subsets, with K = 3 for the Atlantic origin subset, grouping 16JB and 15FF populations into one cluster, and K = 3 for the Mediterranean farmed origin subset with included farm-associated adults 2017, grouping 17AK and 17AB with the eastern Adriatic broodstock (Croatia) Fig. .Figure 3In respect to the high genetic similarity of YoYs and farm-associated populations from 2015 and 2016, using the 95% critical LOD value given by CERVUS, a total of 6 parent–offspring pairs were identified, connecting YoYs sampled from coastal nursery areas  with the parents sampled in the close vicinity of tuna farms. Moreover, 3 YOYs sampled in 2015 from the Neretva River were assigned to the parents sampled around the Kali tuna farm on Ugljan Island (15AK), 2 from the Raša River (2016) and one from Pantana (2015) were assigned to the parents sampled around the Brač tuna farm (15AB), respectively. No parent–offspring pairs were identified among parents from wild populations and YoYs.vs Hybrid F1 F2). In comparing the Structure and NewHybrids results, a relatively similar pattern in individual assignment was observed, except for the class of 66% hybrids where high misclassification of purebred individuals as hybrids decreased the overall performance of NewHybrids.Analysis of three simulated data sets, each having a different percentage of hybrids , indicated 0.85 and 0.90 as the best thresholds to be applied to assign individuals as non-admixed or admixed in an empirical dataset, balancing among efficiency and accuracy of measurements for testing overall performance of the software Structure in hybrid detection  was noted, where 14% of wild adults and 17.4% farm-associated and YoYs populations showed to be mutually admixed. Moreover, 2.5% individuals from the green cluster were assigned as non-admixed ones to the orange cluster, and vice versa of 4.5% individuals  Table . The ass32.Spatial particle distributions on 15 May 2016 obtained in the Ichthyop – Adriatic ROMS simulation showed that there was hydrodynamic connectivity between the aquaculture area near Brač Island, as a potential spawning ground for wild gilthead sea breams, and natural nursery ground areas near Pantana and Raša River Fig. . The sam23. In this study, 19 neutral microsatellites loci were used to explore geographically fine-scale population processes of gilthead seabream within a short-temporal window in coastal areas of the eastern Adriatic Sea, to gain a deeper understanding of the factors shaping genetic connectivity and structure, in comparing 1586 sampled individuals grouped by fish origin (wild vs farmed vs farmed-associated) and ontogenetic state (juveniles vs adults).Significant increase of wild gilthead seabream populations in coastal areas of the Mediterranean Sea and its northward expansion has been documented recently, affecting the structure and productivity of ecosystems30 applied in this study showed robustness and effectiveness for pedigree analysis and characterisation of populations. Allelic polymorphisms and expected heterozygosities were comparable with those observed in wild and farmed populations of Atlantic and Mediterranean origin34 and were slightly increased in comparison to previous studies in the eastern Adriatic9 where only ten loci were used.The standardized panel of two microsatellites multiplex PCRs for gilthead seabream37. Similar reports are known9, including HWE departure of farmed seabass in the Adriatic24. Adding wild fish into farmed stocks and swapping breeders between hatcheries is common practice38, particularly in case of gilthead seabream where wild males are continuously introduced into aquaculture since most individuals turn into females after their second year of reproduction39. Still, lower than average number of alleles per locus, significantly lower allelic richness, heterozygosity and effective size in cultured versus wild populations was recorded within the Adriatic  and between farmed and wild populations, except for interactions with wild populations  in which a high number of escapees/hybrids were recorded. A similar pattern of inter- and intra-farmed strain divergence, as a result of the selection in breeding programs, the founder effect and genetic drift, was observed for other farmed species47.Even though gilthead seabream is an important commercial species for the aquaculture and fisheries sectors, population genetic characteristics throughout the range of species distribution are still not clearly resolved. Different types of markers produce incoherent and puzzling patterns of gene flow discontinuity among regions. Some authors indicated either a weak population structure in the Atlantic and Mediterranean SeaFST = 0.012). While wild adults from natural locations showed homogenous genetic pattern along the Croatian coast, wild adults sampled around tuna farms together with wild young-of-the-years sampled from three coastal nursery grounds showed multiannual genetic connectivity and a clear break in gene flow toward the wild adults from natural locations. At a small spatial scale, such gene flow discontinuity observed among wild fish collections adds new insight into population structure dynamic, considering that previous studies using fewer loci indicated a lack of any population subdivision within the Adriatic33. Low values of FST and high gene flow in marine species do not necessary imply an absence of population structure49 and the observed differences could be due to the different resolution of molecular markers used.Another source of genetic divergence was found among wild genotype collections  migratory and (ii) residential adults, i.e. ones observed around tuna farms. Due to the high dispersal capacity of the studied species, these two contingents cannot be considered as completely isolated units, since the Structure analysis identified a bidirectional pattern of hybridization at lower frequencies (<17%). In Croatian waters, migratory adults first appear during autumn in the north-eastern parts and subsequently move southwards, and therefore, we can speculate that they originate from Italian natural lagoons, i.e. immigrant donor areas that are very important nurseries and feeding grounds for seabream along the western coast52. However, more sampling is required along the entire Adriatic coast to obtain a representative pattern of genetic connectivity.The extent of movements of adult 7. The aggregative behaviour has been primarily attributed to the permanent and increased availability of tuna baitfish losses, composed of small pelagic species rich in omega-3 and 6 fatty acids. In addition to the observed morphological differences, farm-associated seabream had a higher reproductive potential than other wild populations, due to the fish-enriched diet7. It seems that reliance on this trophic source has a positive influence on successful spawning and development of fish egg and larvae53 considering the strong genetic connectivity observed between resident adults from three tuna-farm locations with offspring collections in the three coastal nursery grounds, suggesting these sites are spawning areas. This is further supported by parental test analysis where six parent–offspring pairs were identified, connecting parents from the farm surroundings of Brač and Ugljan Islands with offspring from all three nurseries  situated along the coastline. In addition, the coupled numerical system with ROMS and Ichthyop models successfully utilized in tuna offspring distribution studies within the Adriatic54, has confirmed a possible passive transport between tuna-farms areas off the islands of Brač and Ugljan and the Raša and Pantana nursery grounds in 2016.Estimates of effective population size recorded from residential adults suggest the existence of large breeding populations, which is in line with several recent studies that portrayed Adriatic tuna farms areas as a permanent residency of highly abundant wild seabreamFST pair-wise estimates. Hierarchical Structure and DEPC analysis gave 10 distinct clusters, three of which were exclusively associated with the wild fish origin and seven with farmed ones, where each unit corresponded to a different hatchery source of fry. Namely, due to the limited number of national hatcheries, the majority of fry is still imported from France, Italy and Greece. While all historical samples were completely assigned to a single cluster, several wild populations showed to be heavily admixed with different farmed origins. This is especially true for the recently sampled populations around both tuna farms  where a complete shift in population structure was recorded in 2017 in comparison to 2015 and 2016. Both tuna-farms are located few kilometres from seabream-cages farms, and it is possible that seabream escapees from neighbouring farms were attracted by tuna waste fish feed at the time of fish sampling. Namely, the presence of other farms has influenced the movement patterns of escaped fish, by moving repeatedly from the release cages to other adjacent farms56. The overall number of escapes detected in the wild samples was close to 10%, which is consistent with previous studies57; however, more than half of the escapees in this study were captured at the aquaculture sites. Moreover, offspring 16JB collected from the natural bay near a seabream farm in middle Adriatic showed pure Atlantic-farmed origin, and they clustered together with farmed adults sampled in 2015 from the same area, suggesting that they may have originated from eggs spawned by farmed fish inside the cage. Escape through spawning has already been recognized in Greece and authors suggested that this mechanism may be responsible for recruitment peaks in sea bream populations in certain coastal areas of Greece5. According to the risk assessment of the environmental impact of farming58, the observed number of escapees (<10%) in this study presents a moderate risk for further genetic changes in wild populations. Interestingly, genetic temporal changes in population structure has already been recorded here, considering that the wild historical samples collected during an earlier stage of farming (in 2009) showed high genetic divergence toward wild contemporary samples. Long-term and cumulative introgression of farmed fish and the density of the native populations have been recognized as the main drivers of the temporal genetic change in wild salmonids populations26.Both the multivariate and Bayesian based clustering analysis identified similar structure architecture within the basin, supporting the populations 60.Overall performance of simulated hybrid genotypes using both Structure and NewHybrids indicated that our dataset provided the necessary resolution to identify recent hybrids, but failed to distinguish backcross hybrids with high efficiency, as also seen elsewhere62.About 15% of the hybrids in this study were found to have an aquaculture ancestry, with a similar non-random spatial distribution to those of escapees, demonstrating successful genetic hybridization and introgression of farmed escaped gilthead seabream in recipient wild populations. These wild populations showed slightly reduced allelic diversity  or reduced Ne (17AK) in comparison to non-admixed ones. In the long run, repeated escapes of farmed fish in a wild population may cause a decline in the fitness of the recipient population due to reduced genetic variability that might affect the ability of native populations to cope with a changing environment65. The latest research27 indicates significant introgression in half of the wild populations studied, with levels of introgression in excess of 10% in 27 of 109 rivers. Overall, the authors reported decreased genetic differentiation among populations over time27. Similar patterns of introgression level and temporal population instability have been recorded here. Due to the high larval dispersal potential and large natural variation in fish survival, impacted also by climate change and other anthropogenic factors, the degree to which these processes contribute in shaping contemporary regional population genetic patterns is more challenging than introgression estimation per se. Despite the continuous introgression of farmed seabream in the past decade9 where wild populations near aquaculture facilities were most affected, it should be noted that this warm-water species shows a highly adaptive behavioural response and evolutionary capacity to prevailing conditions by increasing its dominance in coastal ecosystems and capacity for range changes towards the northern edge of its distribution. While the solid genetic base of wild and farmed strains from the eastern Adriatic is established here, as a first step toward development of mitigation strategies to prevent further erosion of genetic integrity, abovementioned adaptations require further attention.Studies of farmed seabream introgression in other regions are scarce in contrast to the extensive work conducted in Norway salmon riversThe methods involving animals in this study were conducted in accordance with the Laboratory Animal Management Principles of Croatia. All experimental protocols were approved by the Ethics Committee of the Institute of Oceanography and Fisheries.et al.9, collected from the Brač Channel in 2009, were included in the analysis to test temporal stability in allele frequencies. Fish sampling was conducted in collaboration with local fishermen and farmers. Fish were measured and weighted, and the distal portion of fin-clips was clipped and stored in 96% ethanol for subsequent genetic analysis. Depending on location, sample sizes ranges from 19 to 124 individuals , and each sample was diluted to 15 ng μL−1 in DNAse/RNAse free water. Total data set containing 1586 individuals from 20 locations was characterized using two multiplex PCRs, SMsa-1 and SMsa2 (SuperMultiplex Sparus aurata), developed by Lee-Montero et al.30 with 21 specific microsatellite markers applied  algorithm. The bootstrap 95% confidence intervals (CI) for the global FST values were calculated using 50,000 replicates over loci. Tests for linkage disequilibrium (LD) and deviations from Hardy-Weinberg equilibrium (HWE) for each locus and population were estimated using unbiased exact tests and Markov Chain algorithm  implemented in GENEPOP v.3.1b69. The significance of HWE and LD values were adjusted using the sequential Bonferroni correction for multiple pairwise testing70.MICROCHECKER 2.2.3 software71, while the inbreeding coefficient (FIS) and allelic richness (Ar) were calculated using FSTAT v.2.372. ARLEQUIN v.3.573, was used to calculate observed (Ho) and expected (He) heterozygosity. Contemporary effective population size (Ne) was estimated in the program NeEstimator V274 using the single-sample linkage disequilibrium method for populations with a sample size over 30 individuals. Low frequency alleles ≤0.02 were excluded from the analysis to minimize potential bias caused by rare alleles. Using putatively neutral loci, parent–offspring matches were analysed using the software CERVUS75. The genotyping error rate was set to 1%, and three different estimates  of the proportions of candidate parents sampled were evaluated. The critical LOD value was set at strict 95% confidence, where final LOD value cut-off for identifying parent–offspring pairs was always above 2. The tested dataset included allele frequencies of wild, farm-associated YOY populations.The number of alleles (N) and mean effective number of alleles across loci (Ae) were calculated using POPGENE v.1.3276 was used to assess the statistical power of tests for genetic homogeneity on the applied set of markers and sample sizes. Each simulation was run 1000 times and power was determined as the proportion of simulations that Fisher’s exact test detected as significant at the 0.05 level. Pair-wise and global FST values calculation were performed in ARLEQUIN v.3.573, where confidence levels were estimated by 1000 permutations of the datasets.POWSIM77. Discriminant Analysis of Principal Components (DAPC)78 from adegenetv1.4-179 in R was used to further characterize the potential differences between historical, present-day wild, and farmed fish. The function find.clusters and ‘k-means’ algorithm determined the most likely number of genetic clusters in the data and function xvalDapc was used sequentially using 1000 replicates, to determine the optimal number of principal components to retain in the discriminant analysis.To infer genetic structure in the neutral microsatellite dataset and the extent of admixture between wild and farmed individuals, different statistical tests were performed, including multivariate and Bayesian based clustering analysis. Based on pairwise Nei’s genetic distance matrix, a principal coordinates analysis (PCoA) was conducted using the GENALEX 6. Software80 an R-based implementation of the program Structure28 on the CIPRES portal81 was used to identify genetic clusters and to evaluate the extent of admixture among them. An admixture model was used to determine the number of population clusters (K) with a burn-in of 200,000 followed by 1,000,000 iterations with default parameters and no prior structuring information. K values from 1 to the maximal number of sampled groups were assessed, with 10 replicates per K value. The number of genetically homologous clusters (if greater than two) was determined using the ad hoc statistics ΔK31 implemented in STRUCTURE HARVESTER82 and visualized using CLUMPP83 and DISTRUCT84. To determine the presence of hierarchical structuring of population where one genetic group can be made of several subgroups, the above procedure was repeated in successive steps for all subgroups identified with the deltaK or lnP (D) method until the lowest level of differentiation was recorded in all subgroups or when a subgroup corresponded to a single locality. Analysis of molecular variance (AMOVA) was conducted with Arlequin 3.5. using 20000 permutations on population groupings identified by the Structure analyses.In addition to nonparametric analysis, ParallelStructure85, were identified following the approach of Vähä and Primmer (2006)86. In brief, we first selected 50 pure wild and pure farmed individuals whose Q-values were >0.95 in the preliminary Structure analysis using the neutral microsatellites panel. Next, we created simulated data sets of each of six genotype classes  using the R packages hybriddetective87. To compare the overall performance of each software for hybrid detection, three sets containing different proportions of hybrids  were constructed and analysed separately. The simulated data sets were then run through Structure using k = 2 and the above settings for the real dataset, and NewHybrids to determine the efficacy , accuracy (the proportion of an identified group that truly belongs to that category) and performance (the product of efficiency and accuracy) of these programs in detecting hybrid individuals. For NewHybrids, we used a posterior probability of 50% as the threshold, while for Structure we used threshold values ranging from 0.60 to 0.95 to analyse the assignment of an individual to a specific class. Finally, the threshold value having the most suitable performance was later used to analyse the hybrid percentage in the real dataset.The optimal threshold values to distinguish an individual as admixed in the Structure analyses, or to assign it to a particular hybrid class in NewHybrids85, which provides the posterior probability that an individual belongs to one of six possible classes that differ in the extent of admixture, in our case farm, wild and hybrids , by using Jeffreys prior probabilities and default genotype proportions, following a burn-in period of 20,000 generations and 200,000 MCMC. The simulated pure populations were included in the real population data sets using the ‘z’ and ‘s’ designations indicating pure wild or farmed genotypes.We implemented NewHybrids v.1.1www.myroms.org)93 and Lagrangian individual based model Ichthyop v.3.3 97 was set up to infer larval supply in 2016 of the gilthead seabream adults aggregated around two main tuna aquaculture areas (16AB – Brač Island and 16AK – Ugljan Island) with the natural nursery ground areas 32 had a smaller domain encompassing the eastern coastal area of the middle Adriatic, with a resolution of 1 km . Spatial particle distribution was calculated at the end of the simulation on 15 May 2016, the date of sampling of gilthead sea bream  at nursery locations (see Supplementary Methods). Beaching coastal behaviour was applied throughout the entire domain but with modification suitable for nursery brackish water areas. Namely, outside the area of success, particles that arrived at the coast were neglected in the further dispersion calculations. On the other hand, their arrival at the coast in the area of success around nursery grounds was counted as a successful outcome.Due to high gene flow observed among tuna farm-associated and YoY populations (see Results), a coupled modelling system with hydrodynamic Regional Ocean Modeling System (ROMS, Supplementary information