Gynostemma pentaphyllum, a member of family Cucurbitaceae, is a perennial creeping herb used as a traditional medicinal plant in China. In this study, six polymorphic nSSR and four EST‐SSR primers were used to genotype 1,020 individuals in 72 wild populations of G. pentaphyllum. The genetic diversity and population structure were investigated, and ecological niche modeling was performed to reveal the evolution and demographic history of its natural populations. The results show that G. pentaphyllum has a low level of genetic diversity and high level of variation among populations because of pervasive asexual propagation, genetic drift, and long‐term habitat isolation. Results of the Mantel test demonstrate that the genetic distance and geographic distance are significantly correlated among G. pentaphyllum natural populations. The populations can be divided into two clusters on the basis of genetic structure. Asymmetrical patterns of historical gene flow were observed among the clusters. For the contemporary, almost all the bidirectional gene flow of the related pairs was symmetrical with slight differences. Recent bottlenecks were experienced by 34.72% of the studied populations. The geographic range of G. pentaphyllum continues to expand northward and eastward from Hengduan Mountains. The present distribution of G. pentaphyllum is a consequence of its complex evolution. Polyploidy in G. pentaphyllum is inferred to be polygenetic. Finally, G. pentaphyllum is a species in need of protection, so in situ and ex situ measures should be considered in the future. Gynostemma pentaphyllum. We assessed the genetic diversity and population structure of G. pentaphyllum, explored the migration, and speculated the formation of polyploidies, as well as provided basic information to formulate the corresponding conservation strategy.In the current study, the genetic diversity and population structure were investigated combining with ecological niche modelling to reveal the evolutionary and population demographic history for natural populations of  It can be used to assess the potential for species survival, adaptation, and development. The evolutionary potential of a species and its ability to mitigate against adverse environmental factors depend not only on the level of genetic variation within the species (genetic polymorphism), but also on the population genetic structure . However, it is difficult to determine the ploidy based on the morphological features  molecular markers, also known as microsatellites, are codominant molecular markers with putative neutral evolutionary history. They can be used to measure or infer bottlenecks  assess the level of genetic diversity in natural populations; (b) evaluate the degree of differentiation and structure among populations; (c) explore the origins and migration of G. pentaphyllum; (d) speculate on the origin of polyploidy; and (e) provide basic information that can be used to formulate a conservation strategy.In the current study, SSR markers were used to investigate the genetic diversity and population structure of 22.1G. pentaphyllum samples were collected from most of the georeferenced sampling sites; the sample set covers the full longitudinal and latitudinal extent of G. pentaphyllum in China  and reserved for further laboratory analysis. A handheld GPS  was used to determine the latitude and longitude of each site. Voucher specimens for the samples were deposited at the Northwest University .Wild a Figure . Five to2.2G. pentaphyllum  following the manufacturer's protocol. Preliminary analyses investigated 14 nSSR and 16 EST‐SSR primers developed in The protocols of Sullivan were employed for the nSSR genotyping  of each locus and population were estimated by SPAGeDi , the percentage of polymorphic loci (PPL), and geographic distance (GGD) among population pairs. The IBM SPSS Statistics v21.0 (SPSS Inc.) software was used to calculate the bivariate correlation between the longitude and latitude and three diversity indices: expected heterozygosity, Shannon's Information Index, and the frequency of private alleles. The Pearson two‐tailed test was used to test correlations, with a significance value of 0.05. The correlation between ploidy and genetic diversity was calculated. The distribution of private allele frequency (Fp) and expected heterozygosity (He) of populations were mapped using the ArcGIS (Esri) program, employing a kriging spherical interpolation method.The polymorphism information content (PIC) of each primer was calculated to estimate the allelic variation of SSRs according to the formula:K) of genetic clusters with the online program STRUCTURE HARVESTER  as suggested by Pritchard et al. (K (ΔK) according to Evanno, Regnaut, and Goudet  and the fixation indices calculation in Arlequin 3.5 , include the effective migration rate  paired in both directions, and the theta value (Θ = 4Neμ where Ne is the effective population size). Uniform priors and metropolis sampling with 10 short and 1 long chain with 50,000 and 500,000 iterations, respectively, were used to investigate genealogies. Genealogies were sampled 100 steps apart, and the first 1,000 were discarded. The gene flow and number of migrants per population (Nm) were estimated from the values of M and Θ. Before running the program, the results of STRUCTURE were used to define 2 and 5 clusters. The effective population size (Ne) per population was estimated using an average mutation rate for microsatellites of 5 × 10−4 . Nineteen bioclimatic variables were taken from the WorldClim website  modeling was used to predict suitable paleo‐ and current distribution ranges of 33.1The ploidy of every individual was tested, and mixed ploidies were recognized in a few populations. Confounding individuals were removed to give a single ploidy for each population. Further analyses were performed on the remaining 1,020 individuals from 72 populations.FST, and GST were 3.543, 0.595, 0.334, 0.491, and 0.508, respectively . The value of Ar, I, and PPL for each population ranged from 1.09 to 2.74, 0.046 to 0.987, and 10% to 100%, respectively  and south cluster (S) with little admixture Figure . There i5 Figure b. Some pNei's genetic distance among the 72 populations divided the accessions into five main branches, with three additional subclusters within those branches  and FST value and geographic distance . These results indicate that the genetic diversity and variation are related to geographic distribution.The results of AMOVA reveal that the genetic variation is mostly within populations Table . The per3.4Nm) between the two clusters is also asymmetrical  to 415 individuals in the northeast cluster  to north‐central 1 (NC1) cluster. Bidirectional contemporary gene flows of the related pairs were symmetrical, with slight differences. The highest migration rate (0.157) was calculated for migration from the NW cluster to the S cluster; the S cluster provided less immigrations.Our study indicated an asymmetrical pattern of historical gene flow among clusters. When the 72 populations are divided into two clusters, the mean migration rate (M) from the north (N) to the south (S) clusters is 11.323 and from S to N is 92.507. The gene flow (p < .05) and that 52 populations show a shifted mode in mode‐shift indicator .Results of the genetic bottleneck analysis indicate that 34.72% of the populations (25 out of 72) have a high probability of genetic bottleneck . The trend of these indexes is fairly similar; the lowest and highest diversity were found in the HN and HF populations, respectively. In contrast, Wang, Zhang, Qian, and Zhao , based on a study of ISSR markers. The difference may relate to the reproductive attributes of this species, the sample size, and/or the characteristics of the molecular markers. G. pentaphyllum is a perennial dioecious herbaceous plant that can be pollinated by insects or propagate asexually by rhizomes or bulbils. In the long term, asexual propagation would lead to a reduction of genetic differences among individuals within populations and enhance differences between populations. Moreover, insects' activity can increase the gene flow among individuals. The results of the AMOVA suggested that the maximum contribution rate is within populations. However, there was also a greater degree of variability among populations . It is speculated that the differentiation of populations might be related to the species' asexual reproductive characteristics, geographic isolation, and human activity. G. pentaphyllum has been overexploited in recent years, so the natural resources are becoming scarce. Moreover, many of the populations have a fragmented distribution, which also contributes to the genetic differentiation of G. pentaphyllum. Habitat fragmentation, therefore, has consequences for the genetic structure of species as well as for the ecological processes, abiotic factors, and the quantity and structure of species that make up an ecosystem , the populations fall into two groups located in the north and south of the study area, with mixed in the west. Based on the assumption that southwest China is the origin and diversity center of Gynostemma species , the five clusters are not geographically independent, and there is mixing in some areas, for example, the Hengduan Mountains and Qinling–Daba Mountains. An exception is provided by the HN population, which is located in the southernmost extreme of the distribution area, but groups with the eastern populations. It is possible that this population originated in southwest China but experienced a similar evolutionary history to the eastern group. Some populations consisting of single genetic component  might have experienced significant bottleneck or founder effects.Patterns in genetic structure are produced by evolutionary and demographic processes at different temporal scales  is much less than one successful migrant per generation . A possible reason for the discrepancy is that the large number of samples and sampling strategy in this study reduced the geographic distances among the populations. G. pentaphyllum is a perennial herbaceous plant that is dioecious and pollinated by insects. Pollen flow mediated by insects can promote gene exchange among adjacent populations and individuals. Moreover, according to the Bayesian clustering results, the clusters were not completely independent, but show mosaic phenomena in some areas where the genetic diversity was also abundant, such as the Hengduan Mountains and Qinling–Daba Mountains. It is, therefore, possible that high genetic diversity can be used as evidence for frequent gene flow.A previous study has suggested that the effective gene flow for G. pentaphyllum , have been established to breed G. pentaphyllum, but there is still a risk that the wild resource could be depleted. Therefore, both in situ and ex situ measures should be taken to protect G. pentaphyllum resources.Studies of the genetic diversity and genetic structure of species are important components of biodiversity conservation. Preferential conservation of populations with high diversity optimizes the potential of a species to adapt. However, populations with low genetic diversity should be protected from the threats that arise from evolutionary factors. As a traditional medicinal plant in China, G. pentaphyllum include: (a) education to enhance public awareness and understanding of the importance of wild plants and develop a culture of protection; (b) the establishment of demonstration bases to encourage the public to protect G. pentaphyllum; (c) correct usage of G. pentaphyllum resources. Natural populations of G. pentaphyllum should not be excavated, and its living habitats should be protected; (d) hybridization between cultivated and wild individuals should be prevented to avoid genomic contamination; and (e) in situ measures should be undertaken to protect populations with high levels of genetic diversity , and populations that exhibit specific genotypes and private alleles  should be conserved by a combination of in situ and ex situ measures, for example, removal of plants to a park or botanical garden for protection and scientific study. To summarize, the wild populations of G. pentaphyllum resources should be protected and developed sustainably to enable continued utilization of this natural resource.Potential measures to protect None declared.G.Z. and Z.L. conceived the ideas; X.Z., H.S., J.Y., and L.F. contributed to the sample collection; X.Z. did the experiments, analyzed the data, and written the manuscript. All authors read and approved the final manuscript.


Ruppia species. Established long-term and large-scale patterns of connectivity in lagoon systems can be strongly determined by patterns of nearshore and coastal currents next to local bird-mediated seed dispersal. Despite the importance of dispersal in landscape ecology, characterizing patterns of connectivity remains challenging in aquatic systems. Here, we aimed at inferring connectivity distances of Ruppia cirrhosa along European coastal lagoons using a population genetic imprint and modeled dispersal trajectories using an eddy-resolving numerical ocean model that includes tidal forcing. We investigated 1,303 individuals of 46 populations alongside subbasins of the Mediterranean  and the Atlantic to Baltic Sea coastline over maximum distances of 563–2,684 km. Ten microsatellite loci under an autotetraploid condition revealed a mixed sexual and vegetative reproduction mode. A pairwise FST permutation test of populations revealed high levels of historical connectivity only for distance classes up to 104–280 km. Since full range analysis was not fully explanatory, we assessed connectivity in more detail at coastline and subbasin level using four approaches. Firstly, a regression over restricted geographical distances (300 km) was done though remained comparable to full range analysis. Secondly, piecewise linear regression analyses yielded much better explained variance but the obtained breakpoints were shifted toward greater geographical distances due to a flat slope of regression lines that most likely reflect genetic drift. Thirdly, classification and regression tree analyses revealed threshold values of 47–179 km. Finally, simulated ocean surface dispersal trajectories for propagules with floating periods of 1–4 weeks, were congruent with inferred distances, a spatial Bayesian admixed gene pool clustering and a barrier detection method. A kinship based spatial autocorrelation showed a contemporary within-lagoon connectivity up to 20 km. Our findings indicate that strong differentiation or admixtures shaped historical connectivity and that a pre- and post LGM genetic imprint of R. cirrhosa along the European coasts was maintained from their occurrence in primary habitats. Additionally, this study demonstrates the importance of unraveling thresholds of genetic breaks in combination with ocean dispersal modeling to infer patterns of connectivity.Coastal salt- and brackish water lagoons are unique shallow habitats characterized by beds of submerged seagrasses and salt-tolerant  Ruppia cirrhosa populations can co-occur with other seagrasses such as Zostera and with marine macroalgae  occurs along the Atlantic, North Sea and Baltic Sea, whereas a diverse haplotype group (B) occurs as either pure populations or mixed with haplogroup C in the Mediterranean  R. cirrhosa population genetic information across Europe and (2) estimate the connectivity of R. cirrhosa populations at the level of coastlines and subbasins, using genetic, statistical and dispersal modeling approaches. The null hypothesis refers to a random process without spatial structure. Therefore, we assessed populations of R. cirrhosa in Europe, considering various geographic areas , at distances ranging from a few to hundreds of kilometers within subbasins. We combined nuclear microsatellite based genetic structure and connectivity analysis with physical connectivity assessments to discern whether local dispersal or LDD could explain observed population structures. More specifically, we aim to test for potential genetic breaks at different spatial scales, namely for (1) local contemporary dispersal and inferred connectivity range within hydrologically connected sites, and (2) historical connectivity within subbasins at a regional scale. Simulated ocean dispersal trajectories and patterns of regional connectivity inferred from genetic data are compared with other species and discussed for potential interference with bird-mediated processes. In particular, we propose to conduct alternative approaches: breakpoint analysis, classification and regression trees (CRT) for threshold determination, and a combination of Bayesian population structure and barrier detection with dispersal trajectory modeling of a common submerged aquatic plant in coastal lagoons.In this study, we aim to (1) analyse the global imprint of Ruppia cirrhosa plants were collected during the period 2006–2012 in 46 coastal water bodies from Europe  and 27 from a hybrid Ruppia  were identified as potential for designing primers with Primer3 (http://primer3.wi.mit.edu/). From these tested primer pairs, we selected polymorphic loci presenting at least 10 di-, tri- and tetranucleotide repeats flanked by more than 10 nucleotides between primers region and motifs  were obtained by 100 bp paired-end sequencing on an Illumina Hiseq by Macrogen . Generated reads were first converted from FASTQ format to FASTA using.NET Bio 1.01 (https://bio.codeplex.com). Subsequently, QDD2.1 . Eight polymorphic loci designed from R. cirrhosa were retained for this study: RC3, RCS5, RCS8, RCS9, RCS27, RM3, RM12, RM26. One microsatellite (RMB15) of European R. maritima was cross-amplified from Triest and Sierens  in a multiplexed reaction  as in Triest and Sierens . Microsafs Table . Additio Sierens . All prion Table  using thR = 1–G/1–N), mean number of alleles (A), effective number of alleles (Ae), allelic richness (Ar at k = 20), mean allele sizes, gene diversities (observed and expected heterozygosities HO and HE), individual inbreeding coefficient . The mean of the abovementioned variables and the global ANOVA-based F-statistics and R-statistics  were calculated at the level of coastal Europe and at coastline or subbasin level . To visualize genetic structure at subbasin or coastline level, a discriminant analysis of principal components (DAPC) was performed ]. Also, the slope [a regression over ln(distance)] over the full distance range was tested for Euclidean and for sea current distances .Similar multilocus genotypes (MLGs) were obtained from GenAlex v6.5 . Similarly, an ANOVA approach was done for RST and allele permutation testing to verify for potential evolutionary signals over distance ranges within each subbasin. Based on the outcome of testing five distance classes, we additionally tested for isolation-by-distance (IBD) significance of the slope (regression over ln distance) over a relevant restricted distance range of 300 km , using the FST ANOVA approach for Euclidean distances. Euclidean distances and sea currents were equally representative over shorter distances within each subbasin.Five distance classes as defined to obtain an equal number of pairwise comparisons of populations were considered in an ANOVA approach  for pairwise FST and geographic distance of populations. Additional data mining was done using a CRT analysis with FST as dependent variable and geographic distance as a continuous predictor. The tree structure with nodes, size of nodes, node mean, node variance, and a split variable determine a threshold value as estimate for connectivity within an IBD relevant context. Breakpoint and threshold analyses were performed with STATISTICA v.12.A piecewise linear regression with breakpoint analysis was done, considering full distance ranges at the European level and at coastline level, using pairwise FIJ)  to August 31 (23h00), 2012 and were advected by the simulated ocean surface currents for floating periods of 1, 2, 3, and 4 weeks respectively. End locations of the seeds for all four simulation periods are shown in K = 4 and K = 11 were selected), with 10 replicates and p < 0.05 for the strain admixture . The minimum size of a population that will be taken into account for estimating admixture was set at 5 (50 iterations). An input number of 10 reference individuals from each population was considered (10 iterations). To check whether or not dispersal could be limited by physical barriers of opposite sea surface currents, rather than geographic distance, we calculated barriers to gene flow based on pairwise FST values at the level of each locus with BARRIER v. 2.2 . The Monmonier maximum difference algorithm was run on the genetic distance matrices and geographical coordinates of sampling location to detect genetic breaks based on an a priori defined number of barriers. We followed an a priori assignment of three barriers, primarily testing for barriers between subbasins. The robustness of obtained major barriers was verified by running again with only one a priori barrier set, since the first boundary is the most important one.The obtained scenario of modeled dispersal distances and trajectories were compared as an overlay with spatial clustering using a spatial Bayesian method and a barrier detection method. Bayesian analysis of population structure  of 46 populations on average was 0.80 and ranging from R = 0.12–1  whereas those from Balearic had highest (0.83). Similar MLGs were removed for all further analysis such that the number of ramets (N = 1303) was reduced to the number of genets (G = 955). Ten polymorphic loci revealed a total of 192 alleles in 46 R. cirrhosa populations across Europe.RUMR4) showed maximum two alleles per locus. Those nine loci were the ones primarily designed from R. cirrhosa RC3, RCS5, RCS8, RCS9, RCS27, RM3, RM12, RM26 and one cross-amplified locus from R. maritima (RMB15). These nine loci were not showing tetraploidy in concert but on average for only 1–3 loci at a time within an individual. At population level, one to eight loci showed more than 2 alleles in most R. cirhosa populations across Europe. Apparently, populations sampled along the North Sea  and Atlantic coast  had a maximum of 2 alleles for each locus, whereas only one small-sized water body in the Mediterranean contained maximum 2 alleles per locus (22_SP), potentially indicating a limited number of founders or multiple bottlenecks.Nine loci harbored 3 or 4 alleles within an individual under an autotetraploid condition, whereas one cross-amplified locus (R. cirrhosa was 18.1 (Effective number Ae = 5.9) (Table A = 9.1 and Ae = 3.4), whereas the Mediterranean populations had highest levels  than in the Mediterranean basins (HO ranging from 0.556 to 0.573 and HE from 0.704 to 0.743). The individual inbreeding Fi was significantly positive in 38 out of 46 populations, for each subbasin and for the total. Baltic-Atlantic populations showed the highest level of inbreeding (0.610), whereas Mediterranean subbasins had somewhat less elevated levels (0.480–0.526). Populations with lowest number of genets  may show less reliable estimations of allele diversity, heterozygosities, or individual inbreeding.The mean number of alleles per locus in 955 individuals in European F-statistics (Table FIT = 0.574 ranging from 0.497 to 0.627), within-population inbreeding (FIS = 0.361 ranging from 0.255 to 0.414) and populational differentiation (FST = 0.333 ranging from 0.228 to 0.365). Highest population differentiation was found along the Baltic-Atlantic coastline and weakest for the Balearic Sea (Table FIS referred to mating among relatives within a population (transects) because the estimated selfing rates were low and non-significant. RIT, RIS and RST were nearly similar or lower than the F-based values, indicating no signal of global stronger differentiation due to allele size differences (not shown).Global ANOVA-based cs Table  were calAe < 2 are in North Sea populations, whereas Ae > 2 was found in other sites, see Table The DAPC of populations within each geographic region Figure  revealedp < 0.05 when considering sea current distances). The latter can be explained from the strongly differentiated populations on E. Sardinia. The slopes and r2 were higher for the populations of the Baltic-Atlantic (r2 = 0.30) and the Adriatic-Ionian (r2 = 0.57) than for Balearic and Tyrrhenian Sea (Table All slopes of the regression with ln(distance) over the full range for all populations across Europe  and within each of the coastlines 563–1,497 km) were highly significant for either Euclidean distances or for sea current distances  were found in the Adriatic-Ionian Sea. The average FST values within each subbasin were thus elevated, either already at very short distances (Tyrrhenian Sea) or beyond abovementioned maximum distances of 104-280 km, albeit short dispersal distances when considering the long coastlines and the size of the subbasins. However, the full-range distances are not fully explanatory because lower FST were observed in first distance classes but then suddenly increasing and already leveling off at high FST values at further distance classes .At the level of four coastlines and subbasins , pairwise es Table  revealedbeyond 10 km were FST approach, additional IBD testing was done within a restricted range of 300 km. All distance classes beyond 300 km showed high FST and were not significantly lower than the average FST. Hence, these could be deleted from further connectivity estimations. A regression of the population differentiation over a geographical range restricted to 300 km  or K = 35 clusters [Log (ml) = −30 424 and probability of 0.45]. These clusters correspond to a lagoon level and grouped only the open, connected sites within close vicinity  = −36 858] to K = 15 [Log (ml) = −49 122]. To test for an eventual strong structure at a wide geographic level  = −45 264] and gave a clear separation of the homogeneous  cluster of Baltic—North Sea—Atlantic populations. Within the Mediterranean, there was a West-East gradient with very clear assignment of populations from the Balearic, though with admixtures, especially in the Balearic Islands and W. Sardinia. Populations from Sardinia and the Tyrrhenian Sea contained individuals that could be assigned to three different clusters whereas populations from the Adriatic-Ionian-Aegean clustered as entities with limited cases of admixtures. Thus, at K = 4 only the Baltic-North Sea-Atlantic was assigned as a single gene pool, fully separated from the Mediterranean.A group level mixture analysis (BAPS) of individual multilocus genotypes from 46 populations revealed an optimal partition for ty Table . An indiK = 11 [Log (ml) = −38 590] an optimal resolution was obtained for each of the coastlines or subbasins  assigned populations , genetic structure, threshold distances of connectivity and hydrodynamics , and therefore rejected the null hypothesis of a completely random process of showing no structure. In R. cirrhosa, a complex IBD pattern with genetic breaks at European and at subbasin level was obtained including some mixture of populations as a group though with admixed individuals. When a study area is homogenous in terms of gene flow patterns and dispersal, a Mantel test makes sense. It is thus possible to get further insights into details of genetic variation by computing these statistics locally . Decomposition of genetic variance is a better method than a Mantel test  inbreeding within patches of a lagoon. Generally, local R. cirrhosa populations seem to be maintained by high genet turnover and by frequent seedling recruitment besides vegetative regrowth from persistent rhizomes. A local seed bank may stabilize after yearly replenishment and recruitment originated mainly within the same lagoon. In Zostera noltii, the absence of recent 1st and 2nd generation migrants indicated that LDD is rare although migrants may have entered during the life-span of a meadow  suggest that sexual reproduction is more important than previously thought. Overall, dispersal in seagrasses is far more likely to occur through seeds than through pollen  invest significant amounts of energy in sexual reproduction. In R. cirrhosa there is a high allelic and gene diversity but also limited clonal regrowth. High levels of local dispersal are expected from within-lagoon processes such as water currents, wind action and water birds). The lagoon inhabiting R. cirrhosa bears less fruits than e.g., R. maritima but the former can disperse as drifting detached shoots with fruit-developing inflorescences. Rafting is frequent within lagoons as can be observed from piled up mats at the edges. Rafting might occasionally occur along coastal stretches, given that the lagoons are open to the sea. In Zostera marina, reproductive floating shoots gave a high variance of inferred or simulated dispersal distances, ranging from 0.7 to 150 km  when washed outside the Arcachon lagoon (France-Atlantic coast) and stranded along the shore of the main coastline.Observations of high genetic diversity levels in many K = 35 as least negative marginal likelihood and highest probability) and by a corresponding fine-scaled genetic structure with significant FIJ up to distance classes of 20 km.The local dispersal and contemporary connectivity was visualized by the Bayesian analysis that defined a very high number of gene pools ; Arta lagoon , amongst others. BAPS determines the number of genetically distinct populations, thereby assuming Hardy-Weinberg and linkage equilibrium, as well as a low mutation rate  km for the Baltic Sea-North Sea-Atlantic, between 2.2 and 200.1 (sd 81) km for the Balearic Sea, between 4.4 and 221.3 (sd 83.6) km for the Tyrrhenian Sea, and between 3.1 and 194.6 (sd 69.1) km for the Adriatic-Ionian-Aegean subbasins. Maximum dispersal distances after 4 weeks ranged between 3 km  up to more than 400 km , while minimum dispersal distances ranged between zero (no movement) to 64 km . Interestingly, releases in the population of Nord-Pas-de-Calais (7-8_FR) show pronounced dispersal distances already after 1 week of coastal transport Figure . Vast diCystoseira amentacea in Marseille Bay) and to test the correlation between genetic and hydrodynamic connectivity using a model simultaneously considering local winds, river inputs and offshore circulation. A strong genetic structure however was not correlated with geographical distance (thus a lack of IBD), but zygotes may travel 4–18 h over distances up to 23 km , showing either clear geographic entities  or a mixing of gene pools, especially of Balearic and Tyrrhenian Sea populations. Importantly, the number of a priori defined genetic groups is required  and genetic breaks were empirically estimated at 104–280 km from a distance class permutation test. Consequently, because of these genetic breaks, we did not find good and clear evidence for IBD using simple regression over longer distances. Zostera noltii of Black Sea populations had very high pairwise FST values reaching values of 0.54 for an average reciprocal distance between sites of 360 km  are global statistics in the sense that their computation involves “all” data points and they reflect global properties of the populations sampled over the whole study area. IBD is often significant but could be an artifact of sampling design  can be confounding to assess the other factor, e.g., dispersal distance from a smooth IBD  using BAPS, BARRIER, and a dispersal model that was forced using high-resolution oceanographic data as an overlay at population level. Dispersal trajectories remained mostly along the same coastline . Genetic breaks can be matched with these routes because a portion of propagules remains locally, while an important part is transported off-coast with positions in the open ocean after 4 weeks of floating. Longer floating periods could allow for sporadic stranding on other coastlines, and eventually result in connectivity if establishment conditions are suitable.The Malécot,  instead Malécot, , then anRuppia  and is responding slowly to contemporary changes in connectivity . Indications of possible LDD has been rarely assessed using both genetic assessments and physical modeling of ocean currents . The latter habitats with fluctuating salinities, often ephemeral, are also populated by R. maritima s.s., a Mediterranean taxon of hybrid origin, hybrids between R. cirrhosa and R. maritima and R. drepanensis  distances, e.g., few km between three vegetation beds at northern edges of Mar Menor and within two beds of Cadiz Bay in the abovementioned regional study.A strong population genetic structure and isolation was observed in a regional study of the Southern Iberian Peninsula  or might remain below detection sensitivity. However physical and genetic methods detected limited connectivity from congruent threshold levels among populations at a distance of up to tens to a hundred of kilometers, which can be regarded as an ecologically significant scale for putative passively dispersing rafting of R. cirrhosa fruiting shoots. We showed for R. cirrhosa that oceanographic features may play an important role in shaping the overall historical connectivity of primary habitats. Biotic vehicles of transport (waterfowl) might interfere at a certain spatial scale and in secondary habitats, though not explaining the obtained genetic breaks and clustering of gene pools, when overlaid to modeled dispersal trajectories of ocean currents. The understanding of abiotic and biotic interactions of submerged plants, their pollination mode, dispersal vectors and habitat suitability benefit from a combination of genetic and hydrodynamic modeling to improve our understanding of connectivity and consequences of movement in coastal lagoons and wetlands.In conclusion, this study combined genetic analysis, threshold estimations of connectivity (CRT) and oceanographic modeling to understand mechanisms of dispersal and to give insight into species life-history traits of LT performed the fieldwork, conceived and designed the experiments, contributed reagents, materials, analysis tools, interpreted, and analyzed the genetic data, wrote the paper, prepared tables. TS performed and interpreted the microsatellite experiments. TVdS and DM carried the modeling component of this research at the Jet Propulsion Laboratory (JPL), California Institute of Technology , TVdS under a JPL Visiting Student Researchers Program (JVSRP), and DM under a contract with the National Aeronautics and Space Administration (NASA). TVdS prepared figures. TVdS and DM reviewed drafts of the paper.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The human genetic diversity around the world was studied through several high variable genetic markers. In South America the demic consequences of admixture events between Native people, European colonists and African slaves have been displayed by uniparental markers variability. The mitochondrial DNA (mtDNA) has been the most widely used genetic marker for studying American mixed populations, although nuclear markers, such as microsatellite loci (STRs) commonly used in forensic science, showed to be genetically and geographically structured. In this work, we analyzed DNA from buccal swab samples of 296 individuals across Peru: 156 Native Amazons  and 140 urban Peruvians from Lima and other 33 urban areas. The aim was to evaluate, through STRs and mtDNA variability, recent migrations in urban Peruvian populations and to gain more information about their continental ancestry. STR data highlighted that most individuals (67%) of the urban Peruvian sample have a strong similarity to the Amazon Native population, whereas 22% have similarity to African populations and only ~1% to European populations. Also the maternally-transmitted mtDNA confirmed the strong Native contribution (~90% of Native American haplogroups) and the lower frequencies of African (~6%) and European (~3%) haplogroups. This study provides a detailed description of the urban Peruvian genetic structure and proposes forensic STRs as a useful tool for studying recent migrations, especially when coupled with mtDNA. The rapid advancements in genotyping techniques and the growing availability of genetic data in open databases have greatly improved our view of human population structure. Many regions of the human genome can be analyzed to investigate admixture events among populations from different continents, as those associated with the European colonization and the African slave trade in the Americas. New methods for analysis of genome wide SNPs data contributed to determine the continental ancestry in admixed populations from urban Brazilian people, showing their high degree of admixture along with a strong European contribution , 2. In aMany STRs, having an observed heterozygosity >70%, show a high individual discriminating power. Therefore, these markers are widely used in human individual identification for resolving forensic cases –10. AlthThe complex historical origin of urban populations in South America was mainly investigated through uniparental and non-recombining genetic markers , by means of region-specific haplotypes or haplogroups , 13. StuIn this work, we analyzed 16 STR loci, commonly used in forensic science, in Native Amazon Peruvians from Ucayali, Loreto and Lambayeque regions and in Peruvians from Lima's urban area and other urban areas of Peru . MoreoveBuccal swabs of a total of 296 individuals were sampled across the entire territory of Peru during three sampling campaigns along the years 2012–2015. Of these, 156 were Native Amazonian Peruvians belonging to Ashaninka, Cashibo and Shipibo people from Ucayali, Huambiza from Loreto and Moche from Lambayeque, while 140 were individuals from the urban area of Lima and other 33 Peruvian towns . The ind® NGM SElect™ PCR Amplification Kit  for the D10S1248, vWA, D16S539, D2S1338, Amelogenin, D8S1179, D21S11, D18S51, D22S1045, D19S433, TH01, FGA, D2S441, D3S1358, D1S1656, D12S391 and SE33 loci [® ID-X . All runs included a negative (water) control, 6 replicates of the reference allelic ladder included in the kit, as well as the positive control provided by the manufacturer (Control DNA 007). Profiles were inspected by two independent operators. Independent spreadsheets were produced and compared. Profiles with missing amplification at one or more loci were discarded.Genomic DNA was extracted using standard procedures  and amplE33 loci . After t3. 2. 1 [To detect hidden relatedness, we also ran the program Familias 3. 2. 1  using al3. 2. 1  and Nort3. 2. 1  were emp3. 2. 1 . This stThe mtDNA of 132 urban Peruvian samples and 10 Native Amazon individuals belonging to Moche population were analyzed by sequencing, while mtDNA haplotypes of the other Native individuals were already published . The ampAllele frequencies, observed and expected heterozygosity, Fis and Fst values, and the exact test for the Hardy-Weinberg equilibrium (HWE) were calculated using Arlequin v. 3. 5. 2. 2 and 1 million steps in Markov chain .To estimate possible contribution of non-Native American source populations to the urban Peruvian gene pool, we added to our data set genetic profilesfrom two different population samples both from USA : one of factoextra to graphically represent affinities among all genotypes and to ascertain which alleles mainly contributed to between-individuals diversity.Principal Component Analysis (PCA), based on individual STR profiles, was carried out by R package adegenet [find. cluster. The retained PCs (100) were passed to a Linear Discriminant Analysis and the first two components were shown on Scatterplots of the DAPC.To assess the relationships between different possible population sources  and urban populations, an independent evaluation of membership probabilities for each individual in each population was obtained by means of Discriminant Analysis of Principal Components (DAPC). This multivariate method defines a model in which the component of genetic variation between groups is maximized by minimizing the within-group component . Analyseadegenet . Then, aFor maternal ancestry identification, each mtDNA was phylogenetically classified and standard diversity molecular indices and Tajima's D test of neutrality were calculated for all populations in our database on the basis of the HVS-I haplotype using the software Arlequin v. 3. 5. 2. 2 , 37. UsiAfter relationship filtering, the final dataset comprised 232 subjects , all typed at 16 STR loci . The numTo check for a decrease of heterozygosity, Fis indices were calculated for all Native Amazon and urban Peruvian populations. They were quite symmetrical around 0, with no significant values . HoweverWe performed an exploratory analysis to highlight genetic structure caused by different continental ancestries. The best clustering model was identified by STRUCTURE 2. 3. 2 software , evaluatPCA based on STR genotypes mainly confirmed admixed structure of urban Peruvians contributed by Native Amazon and African populations . The totA comparable degree of admixture for Lima and other Peruvian urban regions was confirmed not only by a null Fst value  of Lima vs. pooled data of the other Peruvian regions, but also by null Fst values between the single population samples . ConsideWe used DAPC to define clusters of genetically related individuals. The best fitting model in the wide STR database was 5 K (BIC = 1755.36). After a Linear Discriminant Analysis, the first two components were represented on Scatterplots of the DAPC , which sThe model highlighted an association between some clusters and the populations under study . SpecifiThe results of clustering of STR profiles obtained by DAPC were compared with those from mtDNA analysis. mtDNAs of 132 urban Peruvian and 10 Moche individuals were newly genotyped, while the haplotypes of the remaining 90 Native Amazons were already available . In S1 TTo accurately estimate the native contribution, a dataset reporting only mtDNA haplotypes belonging to the Native American haplogroups A, B, C and D was created for urban Peruvian sample, and it was then compared with the mtDNA Native haplotype dataset of admixed and Native people from Peru, Bolivia, Chile and Amazon region of Brazil . The genOnly 13 mtDNAs (10%) out of the 132 genotyped in urban Peruvians belonged to non-Native American haplogroups : 8 belonPairwise genetic Fst matrix was built on the mtDNA HVS-I haplotype data obtained from the present research and other populations from urban, Amazon and Andean places of the South American West Coast. They were plotted through 3D nmMDS to identify maternal genetic relationships with 0.02 Stress value . The linThe same populations were grouped according to a geopolitical or ecoregional criterion and for each grouping we performed AMOVA. Grouping described by 3D nmMDS showed greater amount of variance among groups than geopolitical and ecoregional grouping . MoreoveFinally, to test possible associations between geography and genetics, the Fst matrix was correlated with both altitudinal and geographical distance matrices among populations. This test showed a light correlation index between altitude and genetics , while no correlation between genetics and geographical distances  was found.The three different grouping are as follows: Geopolitics ; Ecoregions ; 3D nmMDS first group (Andes Peru): urban Peru, North and Central Andes Peru;second group (Lake Titicaca): sub Andes Bolivia, La PazBolivia, Titicaca Peru, Temuco Chile; third group (Amazon): Llandos Bolivia, Amazon Natives Peru, Amazon Natives Brazil; fourth group (Chile): Conception Chile, Iquique Chile, Punta Arenas Chile,Santiago de Chile,Natives South Argentina Chile).In this work, we tried to shed light on the transcontinental contributions to the gene pool of admixed urban Peruvian populations, using recently developed multivariate methods for clustering analysis on STR loci commonly used in individual identification. Moreover, we also took advantage of the geographic origin information provided by the maternally-transmitted mtDNA.The slightly reduced heterozygosity  showed by urban Peruvians, may be due to a low level of endogamy in these populations. Inbreeding of urban people in Peru was also confirmed  by positThe clustering and multivariate methods applied on STR genotype database allowed to highlight admixed origin of urban Peruvian populations, in which the African component was evident on the most abundant Native background, especially in the Lima sample Figs  and S1. As regarding Peru, the genomic ancestry proportions based on autosomal STRs showed 30% of admixture with non-Native American populations , while pThe identification of STR alleles with geographic variation on global scale was the other main point of this work. In the present study, the main contributor to individual clustering provided by DAPC was the TH01-7 allele . High frThe second part of our study extends this discussion through the study of mtDNA background. mtDNA haplotypes belonging to non-Native haplogroups were concentrated only in Lima and on the urban Coast region. In particular, in the here studied urban Peruvians, the African maternal contribution (6%) was slightly more represented than the European maternal contribution (3%) . Indeed,These data fitted with STR cluster proportions: 13% and 9% of urban Peruvian samples resulted to belong to African clusters 2 and 3, whereas only 1% belonged to the European cluster. These data could suggest past slavery, which especially involved Lima and towns on the Coast region and influenced heavily the population composition of this area: by XVIII century more than a third of the Lima's population included slaves, mainly Africans . These rFinally, the Native mitochondrial component showed a strong similarity in urban Peruvian and Andean populations, indicating Andean people as the most probable Native source population of urban Peruvians. This scenario is plausible, because, unlike Native Amazon populations, Andeans maintained larger population sizes also after European colonization and greater mobility . The anaIn this work, we tried to shed light on the presumed admixed origin of urban Peruvian populations through clustering and multivariate methods. In the STR genotype database strong signs of continental ancestry were highlighted, also supported by mtDNA composition. Finally, this work confirmed the important role of autosomal STRs and mtDNA for historical reconstructions, underlining the advantage of a combined use of the autosomal and uniparental markers usually employed in forensic applications.S1 FigThe colors are as follows: dark grey for European, grey for African and light grey for Native Amazon ancestry component. The presence of more than one component in US European and US African samples was due to the multiethnic origin of United States populations.(TIF)Click here for additional data file.S2 FigGeographic distribution of haplotypes,reported in (TIF)Click here for additional data file.S3 Fig3DnmMDS on the first three axes based on the matrix of pairwise Fst values of HVS-I mtDNA after grouping into 14 geographic samples. Color shades from bright red to black refer to position on dimension 2. The references of all samples were reported: UrbanPeru (this paper); NCAndePeru  (this pa(TIF)Click here for additional data file.S1 TableList of sampled individuals with birthplace and geographic information, geographic coordinates, response after filtering with Familias 3 software, STR DAPC cluster, mtDNA haplotypes and haplogroups.(XLSX)Click here for additional data file.S2 TableRelative allele frequencies at 16 STR loci Relative allele frequencies at 16 STR loci in the population samples and two pooled samples (only Amazon and urban Peruvians).(XLSX)Click here for additional data file.S3 TablePairwise Fixation Indices (Fst) in all STR loci: a) using all single population samples. b) considering whole dataset as only 4 populations. All values were significant (p < 0.05). Above diagonal P-values; below diagonal pairwise Fst value. In bold: not significant P values.(XLSX)Click here for additional data file.


The historical province of Dobruja, located in southeastern Romania, has experienced intense human population movement, invasions, and conflictual episodes during the Middle Ages, being an important intersection point between Asia and Europe. The most informative source of maternal population histories is the complete mitochondrial genome of archaeological specimens, but currently, there is insufficient ancient DNA data available for the medieval period in this geographical region to complement the archaeological findings. In this study, we reconstructed, by using Next Generation Sequencing, the entire mitochondrial genomes (mitogenomes) of six medieval individuals neglectfully buried in a multiple burial from Capidava necropolis (Dobruja), some presenting signs of a violent death. Six distinct maternal lineages  with different phylogenetic background were identified, pointing out the heterogeneous genetic aspect of the analyzed medieval group. Using population genetic analysis based on high-resolution mitochondrial data, we inferred the genetic affinities of the available medieval dataset from Capidava to other ancient Eurasian populations. The genetic data were integrated with the archaeological and anthropological information in order to sketch a small, local piece of the mosaic that is the image of medieval European population history. Most of them shed light on the genomic history of different European regions from the Mesolithic to the Bronze Age, whereas the genetic heritage mirrored in more recent time transects remains partly obscured due to the limited number of analyzed samples and/or populations. This scenario reflects the situation of southeastern Europe. Based on the genomes of four prehistoric samples from Romania, González Fortes et al.5 revealed that the Neolithization process in this area relied on the movement of both people and ideas. The analysis and interpretation of genome-wide aDNA data from more than 200 individuals inhabiting southeastern Europe between 12,000 and 500 BC, showed that this geographical region “served as a genetic contact zone between east and west over thousands of years6”. This pattern was also observed in a small medieval group of individuals from southeastern Romania (Dobruja)7. The genetic connections to Central Asia were reflected by the presence of the N9a haplotype in 2 out of 10 successfully analyzed samples7. Evidence from present-day maternal haplogroup diversity in the historical provinces of Romania showed that the Asian influence in Dobruja is greater than in the other regions, and suggested that the Carpathian Arch might have had an influential role in migration patterns8. Other findings from ancient mitochondrial DNA (mtDNA) research revealed the contribution of Hungarian Conquerors to the gene pool of the Carpathian Basin and suggested that most probably they descended from steppe nomadic people9. However, the archaeogenetic picture of medieval southeastern Europe is far from being complete.Over thousands of years, the Lower Danube Basin witnessed striking social and cultural changes and several waves of human population migrations that have contributed to the shaping of the current European genetic landscape. Large-scale studiesThe aim of the current study is to catch a glimpse into the maternal population history of the Lower Danube Basin by integrating full-length mitochondrial data with archaeological and anthropological evidence of a small group of medieval individuals  discovered in southeastern Romania (Capidava necropolis). This study is an attempt in understanding why these individuals were collectively buried in a particular fashion, which contrasts with the typical Christian medieval funerary practices observed at the same site, to evaluate the levels of variability within this group, and the relationships to other ancient populations from Eurasia.th century and were initiated by Vasile Pârvan and Grigore Florescu10. Archaeological research in and near the Capidava fortress has started in 1924 and continues without major interruptions to date, but until recently the biological material discovered here was not fully exploited. The archaeological excavations have highlighted dramatic changes of the fortress structure since it was built at the end of the third century AD11. At the end of the 6th century AD, after the Huns burned down the fortress, a small quadrilateral fort occupying the southern quarter of the precinct was built. A century later, amid the attacks of Avars and Slavs, the fortress was completely destroyed and abandoned by the last troops overseeing the area. In the 10th century another wave of destruction and rebuilding was recorded, this time the walls being reconstructed following the initial pattern used in Roman times11. During the 10th-11th centuries, the Lower Danube Basin was politically part of the Byzantine Empire. This was a troubled period, with complex interactions between several populations . As Capidava fortress is placed on the fringe of the Danubian Byzantine Empire, many migratory populations used this settlement in their passage12. Due to lack of solid archaeological evidence, particularly absence of any grave goods, the individuals from the C58 archaeological complex, the subject of this study, cannot be associated to any invasive ethnic groups or to any local populations .Capidava fortress , a civil and military center after the Roman conquest, stands on the right bank of the Danube, halfway between Hârșova (Carsium fortress) and Cernavodă (Axiopolis fortress), the road linking the localities passing by the walls of the fortress. The first archaeological surveys in the Capidava area started at the beginning of the 2012.The assemblage of human skeletal remains belonging to the ten individuals was placed in a multiple burial pit (C58) and was not arranged according to the Christian burial customs of the medieval period, as observed in the majority of the graves from this archaeological site . The skeletons were found on the bottom of an elliptical pit, with no artifacts present  and the remaining two exhibited skeletal markers which indicate that they were probably females . This small group of individuals is pretty diverse in terms of age since only the old adult category is absent. The male individuals recovered from the C58 funerary assemblage exhibited signs of violent traumas  sequences. The rates of cytosine deamination at the 5′ end of the molecules were high, varying from 24.7% to 41.3%. The resulted mtDNA fragments are short, with a median length of 57.87 base pairs (bp) which ranges in the typical size length for aDNA16. In addition, the percentage of possible present-day human contamination was evaluated in order to further asses the authenticity of the ancient mitochondrial genomes. No significant levels of contamination were detected, as shown in the Supplementary Table We successfully reconstructed the complete mitochondrial genomes for all six individuals from the Capidava multiple burial selected for molecular analysis. The bioinformatics processing of the raw reads reveals that the resulted sequences for all analyzed samples reach standard quality requested to assure the authenticity of the NGS data. The details of NGS data for each sample are summarized in the Supplementary Table The mutation patterns revealed by the analysis of the complete mitochondrial genomes of six samples from the C58 archaeological complex can be classified into five macro-haplogroups   were used in order to discern between the samples analyzed in this study and other present-day or historical samples. Red nodes correspond to the Capidava samples, orange circles represent ancient samples and the modern ones are colored green. Black circles represent hypothetical haplotypes. The sizes of the circles are proportional to the frequency of each haplotype; the smallest colored circles representing only one sample. The numbers of cross lines in the branches between adjacent nodes denote number of mutations. The length of the branches is not relevant as they were adjusted to fit the page. The closest samples to those studied are labeled with GenBank accession number and their geographical origin.The increased level of resolution of full length mtDNA data allowed for the identification of direct links among closely related ancient and modern mitogenomes and for the precise assignment of geographic affinities. Phylogenetic analysis showed that three C58 haplogroups, H11a1 Fig. , and J1c7. The medieval population from Capidava showed the lowest distances from four ancient populations: Bronze Age population of the Balkan Peninsula  (FST = −0.0348), Srubnaya (SRU) (FST = −0.02367), Poltavka-Potapovka (PBA) (FST = −0.01677), and Hungarian Conquerors (HUN_Conq) (FST = −0.01325); these values were not significant (p > 0.05). Five ancient groups  appeared most distant to the individuals in our dataset, displaying significant differentiation (p < 0.05)  plot  possibly reflect the poor life quality of this group of individuals. When comparing the presence of pathological features between the individuals from the C58 complex and the ones from the rest of the necropolis, a slight increase in the incidence of stress indicators can be seen. Cribra orbitalia has an incidence of 20% in the C58 group and 17% in the necropolis group, while porotic hyperostosis occurs in 50% of the individuals from the C58 complex and in only 7% of the individuals from the necropolis. Linear enamel hypoplasia is present in 18% of the individuals from the necropolis, while in the C58 complex, it occurs in 10% of the cases. It is very likely that they had experienced one or more of the following: nutritional deficiencies, physiological stress during childhood, repetitive physical activity, and low immunological status. With regard to trauma and fractures, 8% of the individuals from the necropolis group suffered cranial trauma, while a much higher incidence, 30%, can be seen in the C58 complex. All adults show mild signs of osteoarthritis, mainly on the long bones of the upper and lower limbs, which can be associated with moderate physical activity during their lifetime. The marginal social status  of this group at the time and place of their deaths seems a reasonable explanation when correlating the inconsiderate burial with the observed pathologies. The pattern of physical trauma observed here indicates a violent death for nearly half of the individuals, all of them males, which might be the result of some kind of skirmish. A higher frequency of skeletal trauma in males in comparison to females is not unexpected, because they were usually involved in more physically challenging and dangerous activities than females18. The prevalence of frontal craniofacial injuries determined in all analyzed male individuals could be a consequence of an imbalanced fatal physical confrontation. This injury pattern indicates that these individuals were not attacked from behind (execution style). Cuts on the humerus and rib of Cap-C58-5 suggest he might have been involved in a physical struggle. Skeletal evidence of deliberate interpersonal violence was previously recorded, being linked to different historical periods such as Neolithic multiple and collective graves from Germany19, a Copper Age mass grave from the territory of Croatia20, and Early Iron Age settlements from Dobruja17. The number of similar cases that date to the medieval period is limited to few notable examples21. For instance, the first attempt at identifying the reasons for the violent death of late medieval individuals buried in a mass grave from the University Square  was recently documented22. Comparable examples to the analyzed sample set in terms of demographic profiles (high number of women and children) were best explained by raids23, attacks that usually result in killing everyone encountered24. The disorganized body positions and the absence of religious rites specific to the medieval period observed in the C58 complex suggest that these individuals were perhaps outsiders , unwanted or without rights in the local community whose representatives are not evident, at this point, in the adjacent necropolis.The analysis and interpretation of the available bioarchaeological data provides some evidence regarding past human interaction patterns and mortuary practices, while genetic analysis points out biological relationships among individuals. However, it is only possible to speculate about the reasons for which the C58 individuals, who died at roughly the same time, were buried together in such a special and rare funerary context. They showed no clear pattern of organization which suggests that they were rather disposed of into the pit, as opposed to ritual deposition, possible due to haste and/or lack of consideration for the dead. In contrast, previously published medieval Capidava sampleset al. and published three years later25. The exact location of the multiple burial and the spatial relationship to the C58 burial cannot currently be accurately identified based on the published landmarks. This grave contains, according to the authors, a minimum number of nine individuals, similarly disposed of as the remains in C58, 8 adults and 1 child with possible supplementary remains belonging to one or more infants. Analyses concerning sex, age at death and traumas of these individuals were not recorded in this or ulterior publications. Nevertheless, a small paragraph pertaining to the position of the skeletal remains of a child from this grave (1959) raises the hypothesis that it may have been decapitated. In contrast to the multiple burial discussed in the present paper, the 1959 burial contained also fragments of metallic armour used in the archaeological dating of the context at 9th-10th century AD25. The 1959 multiple burial human remains were not available for genetic analyses. The presence of two similar archaeological contexts dated to approximately the same age, by different means, seems to hint to a period of local turmoil and vulnerability for local and/or transiting groups.A very similar multiple burial was discovered in the proximity of Capidava fortress in the 1959 archaeological campaign by Florescu e.g. paternal) cannot be excluded. Four individuals  were not selected for aDNA analysis because of their poor preservation and absence of teeth.The nucleotide substitution patterns displayed by the complete mitochondrial genome of each C58 individual, the absence of identical haplotypes amongst them, show the lack of close maternal relationships between the studied samples. Other kinds of biological relationships  share two macro-haplogroups, namely N and U. The higher level of classification based on complete mtDNA data revealed that the derivative lineages clustered under N macro-haplogroups are distinct  and have different phylogenetic backgrounds. Two lineages descending from the common ancestor U were found in each set of individuals . Derivative sub-branches of haplogroups J and T which are commonly distributed across Europe were exclusively found in the multiple burial individuals of all genetically processed samples from this necropolis. Haplogroup H, the most widely spread and diverse maternal lineage in Europe was observed in lower frequencies among the samples from C58 complex than in the other medieval samples from Capidava. The influence of the maternal familial relationships on the funerary ritual is suggested by the presence of identical haplotypes only in adjacently buried individuals (single graves)7.None of the haplotypes present in the multiple burial individuals matches the other five whole mitochondrial genomes found in the previously published samples8. The only matching haplotype is T2b which was detected in modern samples from all historical provinces of Romania, except Dobruja. Most probably the other haplotypes could not be detected in modern samples due to the small resolution of the control region data and/or to low frequencies of these haplotypes in the modern population. Of all haplogroups described in this study, the most frequent one in the modern Romanian population is J1c, which is most common in present-day Dobruja individuals. Haplogroups H11 and U4 are more frequent in modern Walachia and Moldavia than in Transylvania, while N1a is absent from the Transylvanian set.All the haplogroups identified in the ancient samples from this study are also present in the modern Romanian population as shown by the mtDNA control region sequences of 714 Romanians26, in a Bronze Age sample from Hungary (Rise247)2 and was also found associated to the Unetice culture (BZH1)27. H11a1 was found in a medieval sample belonging to an adult female of the Hungarian Conquest period9, but it is not an exact match to the C58-1 sample 28. This haplotype includes three ancient maternally inherited genomes, all from Hungarian Conquerors9. The haplotype of Cap-C58-2 contains all of the expected U4d2 diagnostic mutations aside from 16189 C, and four personal transitions. The same maternal genetic signature occurs in present-day Slavic populations   and in aboriginal Siberians   of J macro-haplogroup in present-day Europe. This specific haplotype variant is rare in modern mtDNA data and seems to be connected mainly to the Near East, more sparsely to Europe and, to our knowledge, is absent from the published ancient datasets. The detected J1c15 haplotype is most similar to a sample observed in the gene pool of Tatars inhabiting the territory of the middle Volga River30. Equivalent haplotypes were found in remains from the Linear Pottery culture (LBK) in Central Europe31 and in an Early Neolithic skeleton from north-western Anatolia (I1099)1 1 Fig. . The sam32. Ancient N1a3a haplotypes were documented in an Iron Age sample from Iran33 and a Middle Bronze Age individual from Lebanon34.N1a3a sub-branch defined by the 16201 T substitution was detected in the Cap-C58-9 sample. The phylogenetic network analysis  currently occurs at high frequencies in the central-western Mediterranean range as shown in Fig. 36 and basal haplogroup U6 has been identified in a 35,000-year-old Homo sapiens from Romania (Muierii cave)37.Cap-C58-5 displays the mutational motif for U6a1a1, a derived lineage nested within U6a1 which is spread from the Near East to northwestern Africa7. In contrast, according to the phylogenetic analysis of the C58 haplotypes, multiple connections with ancient Middle East mtDNA genomes from different historical periods were found34, as well as links to the medieval Hungarian conquerors9. Close genetic ties to the Conquerors were also exposed by the population genetic analysis  reflects the lack of close maternal relationships among individuals, and quite an intricate genetic history, as the identified subclades have diverse geographic distribution . The full length mitogenomic data reconstructed in this study enriches the available genetic information for the medieval period, particularly for Dobruja. All the existing mtDNA information on the medieval Capidava population provides further evidence for genetic connections to the Hungarian Conquerors, a Bronze Age population from the Balkans and Bronze Age populations of steppe origin (Srubnaya and Potapovka-Poltavka).extra muros, Information Center point, C58 archaeological complex) . All human remains belonging to ten individuals discussed in this paper have been transferred to a permanent collection deposited for research at the Molecular Biology Center, Interdisciplinary Research Institute on Bio-Nano Sciences, “Babeș-Bolyai” University in Cluj-Napoca and carry the following codes: Cap-C58-1, Cap-C58-2, Cap-C58-3, Cap-C58-5, Cap-C58-6, Cap-C58-7, Cap-C58-9, Cap-C58-10, Cap-C58-11. The collection is open to researchers, upon request.The collection of archaeological human remains analyzed and reported in this study was unearthed from the medieval Capidava necropolis , most of them being simple, quadrilateral inhumation graves that contain a single individual. With the exception of two Bronze Age individuals, the rest of them were dated to the medieval period based on funerary rituals, grave goods or subsequent radiocarbon dating. Peculiar for this necropolis is the presence of a circular multiple burial pit containing the skeletal remains of ten individuals which are the subject of this study  for 45 minutes, on each side. The powdered tissue used for the isolation of genetic material was obtained from the tooth roots using the same dental device at a very low rotation speed. For each sample, DNA was extracted from 50 mg of biological material following a silica-based protocol, specially designed to target ultra-short molecules42. Illumina libraries were constructed using a previously developed protocol43. No enzymatic treatment for damage repair was applied in order to preserve and consequently analyze the degradation patterns of DNA fragments. The libraries were amplified to reach plateau and enriched for human mitochondrial DNA using a selective bead-capture approach by hybridization of aDNA with probes consisting of long-range PCR products14. A negative control was processed during all analytical phases to monitor for possible contamination. The enriched libraries were pooled in equimolar ratios with libraries from other samples and paired-end sequenced (2 × 75 + 8 + 8 cycles) using the Illumina MiSeq platform.Six specimens consisting of intact multi-rooted teeth  were sampled and stored for genetic analysis during the archaeological excavation. All procedures leading to Next Generation Sequencing (NGS) were performed in dedicated aDNA facilities of the Molecular Anthropology Laboratory, University of Florence. Standard criteria for the analysis of aDNAschmutzi, an iterative approach that jointly estimates present-day human contamination and assembles the endogenous mitochondrial genome15. Forward and reverse reads were merged into single sequences with a minimum overlap of 10 bp between paired-end reads and the adapters were trimmed using SeqPrep44. Unmerged sequences and sequences shorter than 30 bp were discarded. BWA45 software package was used for mapping the filtered reads against the revised Cambridge Reference Sequence , applying recommended parameter settings for aDNA molecules “–l 1000 –n 0.01 –o 2”. After removing PCR duplicates, only sequences with a map quality score ≥30 were retained and used to align at unique positions along the reference sequence. Consensus sequences for the mitochondrial genomes of all samples were called using schmutzi (parameters: “–logindel 1–uselength”). DNA damage patterns at the ends of the molecules and average fragment length were taken into account to identify and call endogenous bases. Present-day human contamination estimates were performed using a non-redundant database of 197 human mitochondrial genomes available in the software package. Misincorporation patterns at the 5′ and 3′ ends were computed using contDeam, a program provided with schmutzi packages. A summary of NGS data for each analyzed sample can be found in the Supplementary Table 47, based on PhyloTree48 build 17  or were requested from the authors  were calculated from complete mtDNA genomes using the Arlequin 3.5.2.2 software53. Nucleotide positions showing point indels (309.1 C(C), 315.1 C, AC indels at 515–522, A16182c, A16183c, and 16193.1 C(C)) were excluded from the analysis as they can cause difficulties when multiple mtDNA genomes are aligned. The most appropriate nucleotide substitution model and the estimate of gamma parameter were determined with jModeltest 2.1.10.55. The FST values of the ancient dataset were computed assuming a Tamura & Nei56 substitution model, 10000 permutations for p-value calculation and an allowed level of missing data of 0.05. The matrix of Slatkin FST values (Supplementary Table 57 of R 3.3.258. The FST values were also represented by different color shadings to indicate the degree of similarity or dissimilarity of the ROU-med population to the ancient Eurasian populations and visualized on a geographic map (Fig. Another database of full-length mitochondrial sequences comprising 282 ancient samples from 17 relevant Eurasian populations was assembled from published literature (Supplementary Table Supplementary InformationSupplementary Dataset 1


Rana pipiens) from 41 wetlands (30 samples/wetland) across North Dakota. Genetic structure of the sampled frogs was evaluated using Bayesian and multivariate clustering methods. All analyses produced concordant results, identifying a major east–west split between two R. pipiens population clusters separated by the Missouri River. Substructuring within the two major identified population clusters was also found. Spatial principal component analysis (sPCA) and variance partitioning analysis identified distance, river basins, and the Missouri River as the most important landscape factors differentiating R. pipiens populations across the state. Bayesian reconstruction of coalescence times suggested the major east–west split occurred ~13–18 kya during a period of glacial retreat in the northern Great Plains and substructuring largely occurred ~5–11 kya during a period of extreme drought cycles. A range‐wide species distribution model (SDM) for R. pipiens was developed and applied to prehistoric climate conditions during the Last Glacial Maximum (21 kya) and the mid‐Holocene (6 kya) from the CCSM4 climate model to identify potential refugia. The SDM indicated potential refugia existed in South Dakota or further south in Nebraska. The ancestral populations of R. pipiens in North Dakota may have inhabited these refugia, but more sampling outside the state is needed to reconstruct the route of colonization. Using microsatellite genotype data, this study determined that colonization from glacial refugia, drought dynamics in the northern Great Plains, and major rivers acting as barriers to gene flow were the defining forces shaping the regional population structure of R. pipiens in North Dakota.Prehistoric climate and landscape features play large roles structuring wildlife populations. The amphibians of the northern Great Plains of North America present an opportunity to investigate how these factors affect colonization, migration, and current population genetic structure. This study used 11 microsatellite loci to genotype 1,230 northern leopard frogs ( Then, spatial analyses were applied to the genetic data to determine whether isolation by distance alone (H02) or models that included modern‐day landscape features best described how the identified populations are spatially structured (Ha2). Further, Bayesian coalescence models were used to evaluate likely divergence times for the defined genetic clusters. Finally, species distribution model for R. pipiens was developed to investigate how changes in climate and climate refugia may explain the evolutionary relationships between distinct populations of R. pipiens.This study applies population genetic tools on a finer scale than previous range‐wide studies to understand what regional landscape features and aspects of climate history have played important roles in how 22.1R. pipiens were sampled throughout North Dakota , by Hoffman and Blouin , and by McKee, Lance, Jones, Hagen, and Glenn . Amplifications were conducted following the procedures published for each locus . Eleven microsatellite loci were amplified using primers developed by Hoffman, Arden, and Blouin  for R. pd Blouin  for the nd Glenn  for the 2.2R. pipiens. Linkage disequilibrium (LD) and deviations in Hardy–Weinberg equilibrium (HWE) were assessed using GENEPOP’007  was calculated between each sampling site and was used to construct an Unweighted Pair Group Method with Arithmetic Mean (UPGMA) tree using the phangorn package . Each analysis consisted of 200,000 simulations after an initial burn‐in of 20,000 simulations. The analysis was run for K values ranging from 1 to 41 possible clusters with 10 independent runs each. The ΔK method , and the K value with the lowest BIC value was selected for further evaluation. Sample sites were classified into populations based on which cluster the majority (>50%) of individuals from the sample site were assigned. For sample sites where no cluster represented a majority of individuals, the top two clusters within that sample site were combined into one cluster and this was applied to all samples across the dataset. This process was repeated until all sample sites contained a majority of individuals from one cluster. The identified population clusters were used as predefined groups for discriminant analysis of principal components ] and geographic distances was performed to find evidence for isolation by distance in the R. pipiens sampling sites across the state using the mantel function from the vegan package in R  was performed on the R. pipiens to move between populations were included in a redundancy analysis . A stepwise mutation model with a average mutation rate of 10−3–10−4 was used to describe mutation dynamics across the whole set of microsatellite markers, while individual marker mutation rates ranged from 10−2 to 10−5, representing a range of mutation rates commonly seen in vertebrates, including amphibians  before it was classified as a separate species. The remaining observations were also screened for duplicate records from the same location and records from fossils or captive observations, resulting in N = 801 final observations to use in habitat suitability modeling  for each fitted model was calculated using the K group of validation points left out during model fitting and was used to create a weighted average of all model results [w = (AUC − 0.5)2]. Models predictions of suitability were rescaled to the same scale and averaged together using the weighted average to produce the final maps of habitat suitability. The averaged models were used to estimate habitat suitability during the present day, Last Glacial Maximum (~21 kya), and the mid‐Holocene (~6 kya) using publicly available bioclimate variable layers produced by the CCSM4 historical model scenarios  across all sites and all loci was 0.768, and overall expected heterozygosity (eH) was 0.788. Observed heterozygosity within each sampling site ranged from 0.661 to 0.882 (Table ISF) within sample sites varied from −0.0706 to 0.1146 .No null alleles, significant deviations from Hardy–Weinberg equilibrium, or evidence of linkage disequilibrium was observed for any of the 11 loci. Allelic richness for each locus varied from 3 to 28 with an average of 17.8 alleles per locus (Table FST = 0.0930), and all population structure analyses produced concordant results. The UPGMA tree  and K‐means clustering determined K = 16 clusters to have the lowest BIC. Further analysis of the K = 16 clusters revealed some of the clusters did not constitute a majority within any one site. Once the clusters were combined into majorities within each site, the PCA results matched the STRUCTURE and BAPS analyses with the same 10 major clusters. Discriminant analysis of the principal components (DAPC) also suggested hierarchical structure. The first discriminant function supported the east–west divide around the Missouri River found by the other analyses and explained 37.6% of the total genetic variance  in the hierarchical STRUCTURE, BAPS, and DAPC . Hierarchical STRUCTURE, BAPS, and DAPC assigned individuals to the same population cluster with membership probability (Q > 0.5) 89.0% of the time. The two Bayesian clustering methods, STRUCTURE and BAPS, agreed on population assignment of individuals 95.7% of the time. DAPC assigned individuals to the same populations as STRUCTURE and BAPS 90.6% and 90.7% of the time, respectively. Because results were so similar, further analysis of population structure will be reported using results from DAPC only.Average membership assignment probability to each population cluster ranged from 0.967 to 0.817. Individuals from the Upper Red/Sheyenne and the Oahe/James populations had the lowest average probabilities of assignment . The majority of individuals from the Upper Red/Sheyenne population assigned to a different population were either assigned to the Lower Red  or the Oahe/James population (3.8%). Likewise, most of the discordant individuals from the Oahe/James came from the Upper Red/Sheyenne  or the Lower Red population (4.3%). The high rate of cross‐assignment of individuals within these bordering river basins suggests there may be admixture between these populations. There were two individuals from sample site 17 on the east side of the Missouri that had a genotype with significant assignment probabilities (>0.4) to populations to the west of the Missouri River, suggesting there may be some limited dispersal across the Missouri River between the Oahe/James and Cannonball–Heartknife populations.3.2r = 0.515, p < 0.001). Geographic distance was positively correlated with genetic distance .The Mantel test indicated there was significant isolation by distance (IBD) among sample sites , and there was no evidence of local structuring within sampling sites . The top three sPCA axes that were retained explained 84.6% of the spatial genetic structure. The first sPCA axis explained 47.3% of the spatial genetic structure and indicated a stark split between populations on opposite sides of the Missouri River . The partial RDA conditioned on the geographic coordinates of sites found a significant effect of landscape variables after removing the effects of isolation by distance . The IBD effect accounted for 60.8% of the variance in the sPCA axes, 36.8% was explained by the landscape factors, and 2.4% was unexplained. Partial RDA models focusing on individual landscape variables found two variables that explained a significant amount of variation in the sPCA axes , and the Missouri River explained 4.0% of the variance . None of the land use types explained a significant amount of variance.The full RDA model explained 97.6% of the variation in the first three sPCA axes , a period when the northern Great Plains region went through extreme drought cycles (Valero‐Garcés et al., s Mushet . During s Mushet . The conR. pipiens populations in North Dakota. Reduced connectivity during long‐term droughts could also explain the most recent population divergence between R. pipiens in the Upper Red/Sheyenne and the Lower Red basins. The best support for this divergence in the DIY ABC model indicates it occurred approximately 600 years BP, during the Little Ice Age when the northern Great Plains had a relatively arid climate (Fritz et al., R. pipiens located in the Red River basins.Isolated refugia during drought periods in the mid‐Holocene would explain the structuring and coalescence times seen in the R. pipiens populations in North Dakota. Isolation by distance was strongly supported by Mantel tests (Figure R. pipiens in North Dakota according to the RDA variance partitioning analysis (Table Rana pipiens commonly disperse distances of 800 m from their natal ponds (Bartlet & Klaver, Rana pipiens are more capable of long‐distance dispersal than many other amphibians, so patterns of isolation by distance may be difficult to detect in smaller areas with high wetland density due to high levels of gene flow (Mushet et al., Isolation by distance was the final landscape factor underlying the genetic variation of s Figure  and was is Table . Isolatiis Table , as evenis Table . Rana piR. pipiens at the scale analyzed in this study. North Dakota has a fairly homogenous landscape, largely comprised of grassland, pasture, and cultivated crops. Intensive agriculture and cattle grazing can have negative effects on the dispersal ability of some amphibians (Mushet, Euliss, & Stockwell, R. pipiens can use cultivated crop fields as well as native grasslands if the amount of cover and level of soil moisture in agricultural fields are comparable to the native grasslands allowing frogs to avoid desiccation (Bartlet & Klaver, R. pipiens metapopulations than could be detected at the spatial scale used in this study. Finer scale sampling using higher‐resolution genetic markers may be able to detect local effects of land use on the biotic connectivity between prairie wetlands.Land use did not appear to influence population structure of 5Rana pipiens populations in North Dakota are highly structured, typical of amphibian populations at regional geographic scales. The patterns of genetic population structure reflect the colonization history and historical climate influences of R. pipiens in the northern Great Plains region. The interplay between wetland connectivity and drought cycles appears to be one of the major factors influencing R. pipiens populations in this region. Wetland connectivity throughout North Dakota is currently being threatened by climate change, agricultural expansion, and wetland draining (Carter Johnson et al., Rana pipiens populations southwest of the Missouri River, though currently stable, are characterized by lower genetic diversity (Stockwell et al., R. pipiens range. Conservation of wetlands and riparian areas across the region will be important, both for securing at risk R. pipiens populations on the Missouri Plateau and Badlands, and for maintaining the genetic diversity found throughout the R. pipiens populations on the glaciated northern Great Plains.Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.None declared.CAS, JDLF, KP, and DM designed the project. JDLF performed fieldwork and laboratory work. KP and CAS provided guidance on data analyses. JW and JDLF conducted data analyses. CAS supervised the study. All authors participated in writing the manuscript. Click here for additional data file.


Austropotamobius torrentium) and includes samples from previously unstudied sites. Two mitochondrial markers were used to reveal evolutionary relationships among haplogroups throughout the species’ distributional range and to estimate the divergence time by employing both substitution rates and geological calibration methods. Our haplotype network reconstruction and phylogenetic analyses revealed the existence of a previously unknown haplogroup distributed in Romania's Apuseni Mountains. This haplogroup is closely related to others that are endemic in the Dinarides, despite their vast geographical separation (~600 km). The separation is best explained by the well‐dated tectonic displacement of the Tisza–Dacia microplate, which started in the Miocene (~16 Ma) and possibly carried part of the A. torrentium population to the current location of the Apuseni Mountains. This population may thus have been isolated from the Dinarides for a period of ca. 11 m.y. by marine and lacustrine phases of the Pannonian Basin. The inclusion of this geological event as a calibration point in divergence time analyses challenges currently accepted crayfish evolutionary time frames for the region, constraining the evolution of this area's crayfish to a much earlier date. We discuss why molecular clock calibrations previously employed to date European crayfish species divergences should therefore be reconsidered.Crayfish can be used as model organisms in phylogeographic and divergence time studies if reliable calibrations are available. This study presents a comprehensive investigation into the phylogeography of the European stone crayfish ( Inclusion of these individuals may be essential for estimates of the phylogeography and divergence times, because they are geographically isolated from other populations in the Pannonian Basin  how is the newly discovered APU population related to the other known populations, and (b) how does incorporation of the APU population, in light of the tectonic history of the region, affects the divergence time estimates of all A. torrentium populations?This study reconstructs the phylogeny of 22.1A. torrentium phylogeography  as outgroups  or 47°C (COI) for annealing, 60 s at 72°C for extension, and 10 min at 72°C for final extension. Geneious  according to the manufacturer protocol, and DNA was stored at −20°C until running the polymerase chain reaction (PCR). Two mitochondrial (mtDNA) gene fragments were amplified: the COI protein‐coding gene with the primer pair LCO‐1490/HCO‐2198 . Molecular clock rate calibrations were based on the widely used  orogenic system. The ACD orogenic system evolved during the Paleogene–Neogene and is a consequence of several tectonic events  final tectonic rotation (including the Apuseni Mountains) and includes the various estimates of the beginning of the marine phase in the formation of the Pannonian Basin  It https://doi.org/10.5061/dryad.t72v91c). Twenty‐five percent of the sampled trees were subsequently discarded as burn‐in, and nodal support as posterior probabilities was annotated on the MCCT of each BEAST tree  for 100 M generations per replicate, after which traces and sampled trees were combined and assessed for convergence using Tracer v1.6. Divergence time analyses were run using a birth–death speciation model and a relaxed molecular clock with an uncorrelated log‐normal distribution, to account for possible rate variation among lineages. Additional information on priors and operators employed can be found within the BEAST2 XML files available in Dryad  were assessed by Mantel tests based on Spearman correlation. These were performed using the package ecodist . All new sequence data from this project were curated, annotated, and deposited via NCBI in the GenBank database  with the exception of the SB and BAN groups.A total of 83 unique concatenated mtDNA COI + 16S) haplotypes were recovered Figure . A new h6S haplot3.3Following the computation of log‐likelihood scores for all models of evolution available in PartitionFinder, the models of best‐fit were selected based on BIC scores. This resulted in an optimal partitioning scheme consisting of a single partition for the 16S mitochondrial gene (HKY + G model) and codon‐based partitioning for COI . The combined mtDNA phylogenetic analysis recovered eight monophyletic clades, seven of which were statistically supported Figure . The sev3.4A. torrentium to be ~20 Ma (HPD 24–16 Ma), with the GK lineage originating at this time. The remaining populations originated during the Burdigalian around 18 Ma (HPD 15.8–21.5). The APU population split from the ZV population around 16 Ma (HPD 15–17), represented by the calibration point of the Tisza–Dacia mega‐unit disruption of the Dinarides. The LD‐ ŽPB‐BAN‐SB‐CSE populations evolved at the same time . The LD‐ŽPB divergence occurred at around 13 Ma, which is similar to the divergence between BAN and SB‐CSE populations. The youngest population split is the one of CSE, which had the most recent common ancestor appearing in the Zanclean around 4 Ma (HPD 2.9–6).Divergence times were estimated using two different calibration points: (a) a geological event that represented the tectonic displacement of the Tisza–Dacia microplate and the beginning of the marine phase in the formation of the Pannonian Basin around 16 Ma and (b) a molecular clock based on a commonly used arthropod COI mtDNA substitution rate , along with the GK population. All other populations originated in the Piacenzian, soon thereafter ~2.7 Ma (HPD 2–3.5). The APU population would have diverged from the ZV population around 2.2 Ma (HPD 1.3–3), LD split from ŽPD ~1.9 Ma (HPD 1.2–2.7) and BAN split from SB‐CSE at the same time . The MRCA of the youngest population, CSE, originated in the Middle Pleistocene around 0.75 Ma (HPD 0.5–1). It should be noted that our estimates based on the substitution rate from Brower (https://doi.org/10.5061/dryad.t72v91c).The arthropod molecular clock analysis shows drastically younger ages, when compared to the geological divergence analysis Figure b. Using m Brower  differ gm Brower  or Klobum Brower . This di3.5r = 0.837) and weakest for the CSE haplotypes (r = 0.137). However, visual inspection of the scatter plots of genetic distance versus geographical distance reveals that, in the case of CSE haplotypes, there are numerous pairs of populations separated by large geographical distances for which the genetic distance was zero (data not shown). Since this could be indicative of two distinct spreading events, a supplementary Mantel test was performed, after having removed populations with zero genetic distance from others in the haplogroup. The association between geographical and genetic distances for the remaining 28 populations was much stronger (r = 0.357).The spatial distribution of haplotypes shows distinct areas of spread for each haplogroup with virtually no overlap Figure . The ManSupporting information Figure 44.1A. torrentium in the Apuseni Mountains are endemic, highly divergent, and related to endemic NCD populations. We suggest that this molecular relationship, which defines the geographical distance, can be explained by the paleogeography of the Dinarides and the Tisza–Dacia mega‐unit during Oligocene and Lower Miocene times. Between 35 and 16 Ma, both the Dinarides and the Tisza–Dacia mega‐unit, including the Apuseni Mountains, were part of the same continental region , which begun at ~16 Ma, and the start of the Pannonian Basin marine phase, resulted in the isolation of the populations in the Apuseni Mountains. The Apuseni Mountains, as a part of the Tisza–Dacia mega‐unit, continued their northeasterly movement and rotation until 11 Ma, by which time they had reached their present location , the Apuseni Mountains formed a large island that was cut off from the Dinarides by the Paratethys Sea initially and then later by the Pannonian Lake. The freshwater system of the Apuseni Mountains came back in contact with other freshwater systems in the area ~5 Ma (see expanded justification in the next section below).Our molecular investigations reveal that the populations of Austropotamobius took place earlier than assumed, at ~42 Ma , and the split between Astacus and Austropotamobius occurred ~48.8 Ma (HPD 62.4–37.5), which is in concordance with the timeframe estimated by Bracken‐Grissom et al. (BPBP) model  showed the highest correlation between geographical and molecular distances , but since the Pannonian Basin was at that time in the paleo‐Danube phase, the colonization of such a highly specific restricted area as the Apuseni Mountains cannot be reasonably explained. Present‐day Tisza River and its tributaries, which could have been used by A. torrentium to reach the northern part of the Apuseni Mountains, were formed after 5 Ma  in the Apuseni Mountains through the well‐established plate tectonic history of this area: the Tisza–Dacia mega‐unit (which includes the Apuseni Mountains), which broke away from a larger plate that included the Dinarides and traveled toward the northeast during the Miocene. The mega‐unit carried with it part of the A. torrentium population and kept it isolated for ~11 m.y. as the plate was surrounded by saline water (first by the Paratethys and later on by the Pannonian Basin).Phylogenetic reconstruction of a species based on molecular data requires full geographical coverage. Previous species phylogenies of A. pallipes and A. torrentium within the context of the Dinarides orogeny. The timing of this split was fixed subjectively at mean values of either 16 or 12.5 Ma, but the uplift of the Dinarides was a much longer process that started in the Eocene and continued during the Miocene and into the Quaternary.Alternative scenarios based on traditional molecular clock calibrations failed to explain the endemism of the APU haplogroup. We propose that the calibrations that were used misinterpreted the timing of the separation between A. torrentium, as was previously proposed for the endemic haplogroups in the Dinarides by Klobučar et al. (All these cumulative evidences might constrain the crayfish evolution in the area to a much earlier time frame. The large genetic separation of the APU haplogroup lineage may have interesting taxonomic implications. We therefore raise the question of whether this haplogroup might be eligible for consideration as a new species, or as a subspecies of r et al. .None declared.LP conceived the idea and collected crayfish field samples, partially supplemented by AW and BG; I‐DP under the supervision of AS performed molecular analyses; JLP‐M and HBG performed molecular data analyses and processing; CZ performed spatial analyses; CP and LD carried out of geological and geographical context; LP, CP, LD, HBG, and CDS wrote the first version of the manuscript; and all authors contributed and approved the final version. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.