DNA fragments (the cytochrome c oxidase submit I (COI), cytochrome b gene (Cytb), and 16S) were concatenated as a mitochondrial concatenated dataset (MCD) to examine the genetic diversity, population structure, and demographic history of Shinkaia crosnieri and Bathymodiolus platifrons. The genetic diversity differences between vent and seep populations were statistically significant for S. crosnieri but not for B. platifrons. S. crosnieri showed less gene flow and higher levels of genetic differentiation between the vent and seep populations than B. platifrons. In addition, the results suggest that all the B. platifrons populations, but only the S. crosnieri vent populations, passed through a recent expansion or bottleneck. Therefore, different population distribution patterns for the two dominant species were detected; a pattern of population differentiation for S. crosnieri and a homogeneity pattern for B. platifrons. These different population distribution patterns were related to both extrinsic restrictive factors and intrinsic factors. Based on the fact that the two species were collected in almost identical or adjacent sampling sites, we speculated that the primary factors underlying the differences in the population distribution patterns were intrinsic. The historical demographics, dispersal ability, and the tolerance level of environmental heterogeneity are most likely responsible for the different distribution patterns.Deep‐sea hydrothermal vents and cold seeps, limited environments without sunlight, are two types of extreme habitat for marine organisms. The differences between vents and cold seeps may facilitate genetic isolation and produce population heterogeneity. However, information on such chemosynthetic fauna taxa is rare, especially regarding the population diversity of species inhabiting both vents and cold seeps. In this study, three mitochondrial  Deep‐sea hydrothermal vents, first discovered on the Galapagos Rift in the eastern Pacific Ocean in 1977  mussels, which are the dominant species in vents and cold seeps, have been described beyond 18 species. Only three Bathymodiolus species in Japanese waters  are capable of inhabiting both vents and cold seeps. In particular, the same haplotypes have been found to be shared by B. platifrons from distant localities and highly differentiated environments  is also considered the dominant member of the fauna inhabiting many deep‐sea hydrothermal vents and minority cold seeps, including Hatoma Knoll, the Formosa Ridge off southwest Taiwan, and the Okinawa Trough  are ideal models as they exhibit various population distances and inhabit different habitat types.Bathymodiolus (Mytilidae: c oxidase submit I (COI), cytochrome b gene (Cytb), and 16S) were employed as a mitochondrial concatenated dataset (MCD) to evaluate the genetic diversity, genetic structure, and demographic history of B. platifrons and S. crosnieri. The current study also sought to explore the adaptability of the two dominant species to different deep‐sea chemosynthetic environments.In this study, three mitochondrial DNA fragments  protocols.S. crosnieri from three vents and one cold seep habitat, and 52 specimens of B. platifrons from two vents and one cold seep habitat were collected by the manned submersible “Jiaolong” during June 2013 and the ROV “Faxian” during April 2014. All the sample information and photographs used in this study are provided in Table A total of 64 specimens of S. crosnieri  following the manufacturer's instructions. Several bivalve species have an unusual mode of mtDNA inheritance known as doubly uniparental inheritance (DUI) , 1.5 μL of each primer (10 mmol/L), 1.5 μL of dNTPs (2.5 mmol/L each), 0.375 μL of Taq DNA polymerase , and 1.0 μL of DNA template (50–100 ng/μL). The cycling parameters were 94°C for 5 min; 32 cycles of 94°C for 40 sec, 43–48°C for 30 sec and 72°C for 1 min, and a final elongation step at 72°C for 10 min. The PCR products were visualized on 1.2% low‐melting agarose gels stained with ethidium bromide. Then, the products were purified and sequenced on an ABI3730 XL sequencing system using the primers described in Table S1.Three mitochondrial DNA fragments, COI, Cytb, and 16S were amplified using the primers listed in Table S1 . The sequences were aligned and trimmed to the same length using the software package MEGA 5.0  and haplotype diversity (h)  and Geothelphusa dehaani (GenBank: AB187570) were set as outgroups for S. crosnieri. Mytilus californianus (GenBank: NC_015993) and Mytilus edulis (GenBank: NC_006161) were set as outgroups for B. platifrons.The average genetic distances within and between populations were estimated according to the Kimura 2‐parameter Kimura  model in (h) Nei , and the (h) Nei . The max (h) Nei  with 100F‐statistics (FST) with 10,000 permutations, based on the distance method in Arlequin 3.5 (Excoffier and Lischer Median‐joining network (MJN) analysis was performed with Network 4.6  (Harpending Nm) was evaluated from GammaSt  for the vent and seep populations were examined using two different approaches. First, the demographic history was investigated by comparing the mismatch distributions in each habitat‐type sample with those expected in stationary and expanding populations using DnaSP 5.10 , Cytb (GenBank accession nos. KR003178‐KR003222), and 16S (GenBank accession nos. KR003236‐KR003244) of S. crosnieri and COI (GenBank accession nos. KR003158‐KR003177), Cytb (GenBank accession nos. KR003223‐KR003235), and 16S (GenBank accession nos. KR003245‐KR003280) of B. platifrons were deposited in GenBank. For S. crosnieri, the MCD sequences (1480 bp) contained 111 variable sites, 65 of which were parsimony informative. For B. platifrons, MCD sequences (1539 bp) contained 45 variable sites, 11 of which were parsimony informative.All three mitochondrial gene fragments were successfully amplified for 64 h), and nucleotide diversity (π) for each population of S. crosnieri are presented in Table h = 0.972, π = 0.0062) and highest in the vent WTS1 population (π = 0.0062).The number of haplotypes (H), the haplotype diversity , whereas the variance among the intragroup populations (0.35%) and within populations (19.95%) was relatively small , indicating a high level of geographical population structure . The values of Nm based GammaSt (from 1.08 to 29.93) and FST (from 0.27 to 43.98) indicated the fluctuation of gene flow levels among the four S. crosnieri populations (Table S2). The level of gene flow between the vent and seep populations was very limited, which was consistent with the statistically significant FST values among them.For population structure analysis, all samples were divided into vent and seep groups. An AMOVA analysis revealed that most of the molecular variance of re Table . In addiS. crosnieri was approximately unimodal for the whole vent dataset   Table .H, h, and π for each population of B. platifrons are presented in Table B. platifrons showed high haplotype diversity and several shared haplotypes were detected among the vent and cold seep populations. A comparison of the genetic diversity of B. platifrons detected a similar level of haplotype and nucleotide diversities among all populations.The values of B. platifrons. The mean genetic distances within and between each of the populations are shown in Table The overall average genetic distance among individuals was 0.0021 for B. platifrons , whereas variance among populations within groups (7.35%) and among groups (3.00%) was relatively small (3.00%) , indicating a low level of geographical structure (Table FST was found only between WKC and the vent NIS2 population (P < 0.001) (Table FST (from 2.37 to 9.96) indicated a slight stabilization of the gene flow levels among the three B. platifrons populations (Table S2). The gene flow levels among the vent populations were obviously large. Especially for vent NIS2 and the seep WKC populations of B. platifrons, the gene flow was rather weak, which was also consistent with the statistically significant FST values between them.For population‐structure analysis, all samples were divided into vent and seep groups. An AMOVA analysis revealed that most of the molecular variance of re Table . In addigroups 7.5% and amB. platifrons was obviously unimodal   Table .S. crosnieri and B. platifrons showed high haplotype diversities but low nucleotide diversities, which are normally associated with an expansion model , except NIS2‐WKC, which was probably related to small sample size. For S. crosnieri, the results were also supported by a weblike statistical haplotype network and ML tree analyses. The lack of interpopulation contact might be related to its ecological habits (vent and seep) and the long distance of the distribution areas (the distance between the vent and seep are more than 983.8 km). This phenomenon could be proven by the lack of gene flow between vent and seep populations but higher gene flow levels among vent populations, especially for WTS1‐WTS2. However, for B. platifrons, the statistical haplotypes network and ML tree analysis showed that the haplotype distribution did not mirror the geographical origin of the populations because several haplotypes were shared among individuals from different habitat populations. In addition, gene flow was also detected among the populations. The results suggested that extrinsic restrictive factors for the distributions were not related to environmental types (vents vs. seeps)  was evaluated from the values of GammaSt and FST for the Shinkaia crosnieri and Bathymodiolus platifrons populations.Click here for additional data file.


Juglans regia L) is an economically important species cultivated worldwide for its high-quality wood and nuts. It is generally accepted that after the last glaciation J. regia survived and grew in almost completely isolated stands in Asia, and that ancient humans dispersed walnuts across Asia and into new habitats via trade and cultural expansion. The history of walnut in Europe is a matter of debate, however. In this study, we estimated the genetic diversity and structure of 91 Eurasian walnut populations using 14 neutral microsatellites. By integrating fossil pollen, cultural, and historical data with population genetics, and approximate Bayesian analysis, we reconstructed the demographic history of walnut and its routes of dispersal across Europe. The genetic data confirmed the presence of walnut in glacial refugia in the Balkans and western Europe. We conclude that human-mediated admixture between Anatolian and Balkan walnut germplasm started in the Early Bronze Age, and between western Europe and the Balkans in eastern Europe during the Roman Empire. A population size expansion and subsequent decline in northeastern and western Europe was detected in the last five centuries. The actual distribution of walnut in Europe resulted from the combined effects of expansion/contraction from multiple refugia after the Last Glacial Maximum and its human exploitation over the last 5,000 years.Common walnut ( Juglans regia L.) is an economically important tree species, highly valued for its timber and edible nuts. This species grows well in virtually all parts of the world with a temperate climate [Juglans spp. such as SSR markers [Common walnut ,  regions . Genetic regions . Humans, regions –7. The oJ. regia was growing in southern Spain, Italy, France, Switzerland (Alps), Bulgaria (Rhodopes Mountains), Greece (Epirus), southwestern Turkey and Albania during the Upper Pleistocene  , after the Last Glacial Maximum [th to 5th centuries BCE (2800–2500 BP) [J. regia may have survived the cold, dry glacial intervals in refugia located in southern Europe [J. regia survived the LGM in Europe as no polymorphism was detected in 29 demes of walnut in Eurasia using chloroplast PCR-RFLP markers [Fossil pollen deposits clearly indicate that ,000 BP) . Conside Maximum  and its  Maximum . A secon2500 BP) –11. Thisn Europe  and the n Europe –18  whether western Asia and the southern European/Balkans peninsulas represent two separate regions of walnut evolution. In addition, we evaluated the hypothesis that cultural/historical factors played a key role in shaping the genetic resources of walnut in Europe since the Late Holocene.Here, we report on a large-scale study of the spatial genetic structure of walnut populations in Europe using microsatellite markers, and its comparison with autochthonous walnut populations sampled in Asia. Our objective was the integration of fossil pollen, cultural and historical data with population genetics (the landscape genetic overlay approach) , and theJ. regia, including 40 Asian autochthonous walnut populations sampled from China (6 populations), Kyrgyzstan (9), Uzbekistan (17), Tajikistan (1), Pakistan (2), Iran (1), Turkey (2) and Georgia (2) which have already been genotyped [Over the last two decades, the CNR-Institute of Agro-environmental and Forest Biology , CNR-Institute of Agricultural Biology and Biotechnology  and the Earth Trust  have monitored and sampled common walnut trees in Europe and across the species’ range in Asia. Although we were unable to obtain samples from all areas, we assembled a large and unique collection of Dehydrated leaf tissue (60 mg) from each European walnut sample was homogenized in a 2ml micro-centrifuge tube containing a 5 -mm steel bead cooled with liquid nitrogen using a Mixer Mill 300 . Genomic DNA was extracted and purified using a DNeasy96 Plant Kit (Qiagen), and stored at -20°C.In this study, all European samples were genotyped using 14 unlinked nuclear, neutral microsatellite (SSR) markers  already selected and used for genetic characterization of walnut in its Asian range . The allA), effective number of alleles (Ae), observed (HO) and expected (HE) heterozygosity and polymorphic information content (PIC), the three unbiased estimators of Wright’s F-statistics, within-population inbreeding coefficient f (FIS), total-population inbreeding coefficient F (FIT) and among-population genetic differentiation coefficient θ(FST) and the unbiased estimator of Jost’s (Dest) [Standard measures of genetic diversity, total number of observed alleles (s (Dest)  were coms (Dest) . Similars (Dest) .A), observed (Ho) expected (HE) and unbiased expected heterozygosity (UHE) using the GenAlEx software 6.3 [Rs) and private allele richness (PAR) were computed by the rarefaction method with HP-Rare software [Rs and PAR were standardized on a minimum sample size of eight individuals. Following the procedure of Pollegioni et al [Rs) and unbiased expected heterozygosity (UHE) computed for all 91 walnut populations. The within-population inbreeding coefficient FIS [FIS was tested using a non-parametric approach with 1,000 permutations. To determine whether within-population genetic variation was correlated with geographic gradients, we performed a simple linear regression analysis followed by the sequential Bonferroni correction of allelic richness (Rs) and unbiased expected heterozygosity (UHE) against three geographic variables, latitude, longitude and elevation of sampled sites.Levels of genetic diversity were estimated for each walnut population across all loci in terms of the mean number of alleles per locus  for each predefined population and each individual multilocus genotype in each of the inferred clusters using Markov Chain Monte Carlo (MCMC) simulations. STRUCTURE was run assuming a pre-assigned number of clusters (K) ranging from 1 to 90, the admixture model on the whole dataset without a priori population information and with the correlated allele frequencies between populations option. Based on initial results, a series of six independent runs was performed for K between 1 and 12 with a burn-in period of 100,000 steps followed by 106 MCMC replicates. The final posterior probability of K, Ln P(K), and ΔK, the rate of change of Ln P(K) between successive K values [Q-matrices were graphically displayed by DISTRUCT software [Q-values for the K clusters estimated from STRUCTURE using the IDW function implemented in ArcGIS 9.3. A synthetic map representing the genetic structure of walnut in Eurasia was obtained by overlaying the computed K clustering surface maps. We combined multiple K interpolated raster bands in a single multiband raster dataset by the Composite Bands function implemented in ArcGIS 9.3. The integrated use of the Composite Bands-tool and RGB color code allowed us to display the inferred genetic clusters of J. regia populations.Two complementary statistical approaches were used to detect the genetic structure of walnut populations in Eurasia. First, a Bayesian clustering approach implemented in STRUCTURE software 2.3.3  was applK values , was calK values . The corsoftware . After dhttp://tree.bio.ed.ac.uk/software/figtree/).Finally, to confirm the genetic repartition of walnut populations inferred by STRUCTURE, a Neighbor-Joining phylogenetic tree was constructed based on  genetic The demographic history of walnut and its human-mediated postglacial dispersal routes in Europe were further explored using the approximate Bayesian computation (ABC) procedure originally introduced by Beaumont et al  and receDue to computational limitations and the complexity of possible scenarios, we split DIYABC analysis into two stages and we pooled a subset of Eurasian walnut samples into four groups as inferred by STRUCTURE and Neighbor-Joining tree analysis . Gene poIn the first stage of the DIYABC analysis, we tested five competing broad-scale scenarios (Scenarios 1a-5a) based on historical and fossil pollen data . ScenariThe second stage of the DIYABC analysis was at a finer scale, assuming two refugia  or three refugia , with admixture in the Balkans, a population size expansion in northeastern Europe, and decline in western Europe. We also evaluated the dispersal of walnut into northern Europe from western Europe , from the Balkans  or as a result of admixture between western Europe and the Balkan germplasm  .−4 and 10−3. The observed and simulated genetic datasets were summarized using the mean number of alleles, mean genetic diversity, mean allele size variance for each population, Wright’s FST, mean individual assignment likelihoods and mean index of classification (DAS) among populations. We generated a reference table containing 105 simulated datasets for each scenario, and subsequently 1% of the simulated datasets closest to the observed genetic dataset were used to estimate posterior probabilities  for each scenario using direct and logistic regression approaches [I Error  as the proportion of times that the selected scenario did not exhibit the highest posterior probability compared with the competing scenarios for 500 pseudo-observed datasets generated under the best-supported model, and (2) Type II Error  as the proportion of times that the selected scenario was incorrectly selected as the most likely scenario for 500 pseudo-observed datasets generated under each of the competing scenarios. Finally, we performed a model checking analysis to evaluate if a model-posterior combination fitted the observed data correctly. The observed summary statistics were compared with those computed for 1,000 datasets simulated from the posterior distribution of parameters obtained under the selected scenario [The prior values used for all the demographic parameters selected for ten scenarios are listed in proaches . The posscenario .Rs) and unbiased expected heterozygosity (UHE): 1) south–central Asia including sites in Tibet (32-DASH), Kashmir–western Himalaya , northern Pamir ridges , Gissar Mountain , western Tien Shan ; 2) four Trans-Caucasus sites  and 3) four Balkan populations   .P = 0.00015) and increasing latitude . Of 199 alleles detected, 33 were unique to a single geographic site, with 23 unique to Asian and ten to European walnut populations (FIS ranged from -0.066 (74-SANNIO) to 0.280 (28-GUILI-2), and was significantly greater than zero in 31 of 91 sampled sites, indicating a surplus of homozygotes in 18 (45%) and 13 (26%) of Asian and European walnut populations, respectively (P < 0.05) signals of recent reduction in effective population size were detected in a large proportion of European sites (73%), but only in four (10%) Asian populations . By contrast, using the M ratio test, we observed a genetic signature consistent with a bottleneck in all populations. The G–W values ranged from 0.28117 (36-KARAJ) to 0.37939 (72-VALCO), which is substantially lower than the critical threshold of 0.68   . In addi 0.8227) .Q2 ≥ 0.7639). Cluster 3 comprised all nine Kyrgyz and four Uzbek populations  sampled in the walnut forests of the western Tien Shan mountains (Q3 ≥ 0.7856). The remaining three walnut populations in the western Tien Shan mountains  and two populations from the Gissar mountains (15-Djarkurgan) and the Zaamin mountains  in eastern Uzbekistan were mainly admixtures between cluster 2 (0.2013 ≤ Q2 ≥ 0.3740) and cluster 3 (0.4987 ≤ Q3 ≥ 0.7118). Cluster 4 included all European walnut populations sampled in Spain, Italy, France, Slovakia, Crete (Greece) and Hungary (Q4 ≥ 0.7648), except for five easternmost Balkan populations located in Greece , Romania (45-BRASOV), and Moldova (46-CHISINAU) and the remaining population from Tajikistan (35-SHOULI), which showed admixed profiles between cluster 1 (0.3101 ≤ Q1 ≥ 0.7420) and cluster 4 (0.2230 ≤ Q4 ≥ 0.6663)  .Subsequent STRUCTURE analysis within each of the previously inferred clusters revealed genetic substructure, except for cluster 3 . The infTwo sub-clusters of the inferred cluster 2 (K” = 2) corresponded to two distinct groups of walnut populations sampled in east-central Uzbekistan (sub-cluster 2–1) and China  and logistic regression (P2) approaches identified scenario 5a as the most likely model .The ABC method enabled us to test ten demographic scenarios  and to dP1 = 0.3840, 95% CIs: 0.0000–0.8103, P2 = 0.7838, 95% CIs: 0.558–1.0000). The model checking procedure showed that the observed summary statistics for our data were not significantly different (P < 0.01) from the simulated ones calculated from the posterior predictive distribution of parameters for scenario 6b. These findings provided further support for a high-goodness-of-fit observed dataset to selected scenario 6b (I Error = 16%) and false positive (Type II Error = 0–3%) rates clearly indicated that our method selected the true scenario with high confidence, showing high power to distinguish among alternative demographic scenarios (Four excluded scenarios assumed that populations from Anatolia (Scenario 1a-2a) or the Balkans (Scenario 3a-4a) served as a unique source for the human-mediated walnut colonization of the rest of Europe. Scenario 5a proposed two independent dispersal events of walnut from Anatolia (Pool 1) and western Europe (Pool 4) to the Balkans with subsequent genetic admixture (Pool 2). In the second stage of the DIYABC analysis, we tested six fine-scale scenarios always including two  or three glacial refugia  with admixture events in the Balkans . A companario 6b . The comcenarios .t4 median value, 95% CIs: 217–2,010), and between western Europe (Pool 4) and pool NG1 at 118 generations   and a hypothetical ancestral European pool (NG1) at 579 generations (2.3–192) .t2 median value, 95% CIs: 28.6–59.7) resulting in the walnut populations currently present in the Balkans (Pool 2). Walnut dispersal from the Balkans and western Europe at 19.7 generations  promoted a second admixture across northeastern Europe (Pool 3) , 9,440 to 12,980 BP (t3), 4,140 to 5,630 BP (t2) and 1,576 to 2,167 BP (t1) (A secondary contact between NG1 and Anatolian groups occurred at 51.3 generations ((Pool 3) . Assumin BP (t1) , Fig 5.td median value, 95% CIs: 1–13.8), corresponding to ~418–575 BP, and a recent population decline of western European pool 4  at 1.96 generations . During the last two centuries (~ 157–216 BP), western European germplasm was reduced to 21.4% of its former size , 2,550 (N2), 6,460 (N3), 6,320 (N4), 1,620 (NG1) and 6,210 (NA) . In addimer size .Our analyses detected a high degree of walnut genetic diversity in the Balkans , similar to that recorded in other native regions such as the Caucasus , and the mountainous regions of central Asia including the Himalayas , northern Pamir (Tajikistan), the Zaamin ridges, the northern Gissar ridges, and part of the Tien Shan mountains . In addition, we demonstrated a clear longitudinal trend of walnut genetic diversity in Eurasia with a marked loss of allelic richness and heterozygosity running from eastern to western Europe, as well as molecular signals of recent reduction in effective population size.J. regia might have survived after the LGM. Walnut was detected during the Early Holocene in Turkey , F.Y.R.1,485 BP , Greece 1,485 BP ) and the1,485 BP ). As rep1,485 BP . The tra1,485 BP –53. Therunlikely –10, and is Mill. , Quercussuber L. –56 and Qs cerris , the infPinus pinea L. across the Mediterranean, followed by human-mediated dispersal starting around 3000 BP, resulted in a nearly complete loss of genetic diversity in the species [Juglans-type fossil pollen , Spain EPD data –69) or FEPD data ; ArmoricEPD data ) seem plOur genetic structure analysis of Eurasian populations corroborated the theory of separate regions of walnut evolution in Eurasia, dividing the walnut samples into four main clusters: clusters 1–3 centred in Asia with cluster 4 located in Europe see . Our genThe approximate Bayesian analysis of ten alternative hypotheses confirmed the existence of three glacial refugia for walnut in the Mediterranean. It also revealed complex population dynamics during the late Holocene, presumably the consequence of anthropogenic translocation and use of walnut germplasm. Although time estimates should be taken with caution, the inferred demographic scenario indicated that a continuous ancestral European pool (NG1) diverged from the Anatolian-Turkish pool during the last Early-Middle Pleniglacial Period, from 63,690 BP (with a generation time of 110 years) to 46,320 BP (generation time of 80 years), predating the LGM. Our data confirmed the splitting of NG1 into western European and Balkan germplasm from the Younger Dryas  to the Early Holocene  .Juglans starting from 15,000 BP [Castanea sativa Mill. [Olea europaea [J. regia in Europe resulted from the combined effects of expansion from multiple European refugia after the LGM and human dispersal of walnut germplasm.Last Glacial reconstructions have revealed a long-term contraction of temperate tree species in southern Europe, superimposed on millennia-scale climatic fluctuations –74. This5,000 BP  suggesteva Mill. –80 and Oeuropaea –82, thesth millennium BP onward. The occurrence of non-native oilseed species, such as Lallemantia [Carthamus spp [Punica granatum L. [Cucumis melo L. [Our data clearly indicate a contact zone in southeastern Europe where walnut populations accumulated high genetic diversity as a result of admixture of genetic lineages from the Balkans and western Asia. Although DIYABC analysis only tests instantaneous admixture events or population size changes , we can lemantia  and Cartamus spp , and frunatum L.  and Cucu melo L. , in nort melo L. . However melo L. , the motAs outlined for the distinct Beysehir Occupation Phase  , the masJ. regia throughout Europe occurred after 2,500 BP, and was likely the result of walnut’s widespread use during Greek and Roman periods [st and 2nd centuries CE , the cultivation of walnut was incorporated into the local agricultural tradition of north-central Europe, losing its character of exclusivity as an imported luxury food [th century, forests of many western European countries were substantially cleared, followed by the introduction of intensive agriculture based on new crops such as the potato and other changes precipitated by the Industrial Revolution [Another important feature that may have contributed to dispersal, planting and maintenance of walnut across Eurasia is the high quality of its wood. Unfortunately, the history of tree plantation and forest management in Asia and the eastern Mediterranean is poorly documented . Convers periods , 92–93. ury food . In partury food . Therefoury food . Conversvolution . This stvolution .In conclusion, our results demonstrate that the present spatial genetic structure of walnut in Europe resulted from the combined effects of expansion and contraction from multiple refugia after the LGM and the human dispersal and management of walnut over the last 5,000 yr. The evolutionary history of walnut is tightly linked with human history during the Late Holocene, making it a permanent feature of the economic, cultural and rural heritage of Europe.S1 FigKyrgyzstan (1–9), Uzbekistan (10–26), China (27–32), Pakistan (33–34), Tajikistan (35), Iran (36), Georgia (37–38), Turkey (39–40), Greece (41–44), Romania (45), Moldova (46), Hungary (47–56), Slovakia (57),France (58–61), Spain (62) and Italy (63–91).(TIF)Click here for additional data file.S2 FigBayesian Inference of (a) K, the most probable number of clusters, based on microsatellite analysis of all 2,008 common walnut samples, (b) K’, the most probable number of sub-clusters, based on microsatellite analysis of 217 common walnut samples of cluster 1, (c) K”, the most probable number of sub-clusters, based on microsatellite analysis of 280 common walnut samples of cluster 2, and (d) K”‘ the most probable number of sub-clusters, based on microsatellite analysis of 929 common walnut samples of cluster 4 using STRUCTURE software . Log-lik(TIF)Click here for additional data file.S3 FigP) of each scenario and its 95% confidence interval of P (in brackets) computed using a direct (P1) and logistic regression (P2) approach are provided under each scenario. The most likelihood scenario for each stage is marked with a red rectangle.All scenarios tested in stage 1 (a) and stage 2 (b) of DIYABC analysis. In these scenarios, N# refers to effective population size of each corresponding gene pool, and t# refers to time-scale in terms of the number of generations (more details for population parameters and models in (TIF)Click here for additional data file.S1 TableJuglans-type fossil pollen (radiocarbon-dating) during the Holocene and the related citation (a) and the presence/absence of Juglans-type fossil pollen and its classification  in each selected time interval (b) were recorded for each site.The geographic coordinates in decimal degrees , early presence (1700–11.923 Ka BP), first detection of discontinuous and continuous occurrence of (PDF)Click here for additional data file.S2 TableNumber of samples (N), geographic coordinates  and elevation above sea level (Elev) for 91 common walnut populations collected in Eurasia.(DOCX)Click here for additional data file.S3 TablePopulation pools and the prior distributions of the parameters used for the two stages of DIYABC analysis.(DOCX)Click here for additional data file.S4 TableDescription of the scenarios of common walnut expansion across Europe considered in the two stages of DIYABC analysis.(DOCX)Click here for additional data file.S5 TableE), polymorphic information content (PIC), and the unbiased estimate of Wright’s fixation indices, within-population inbreeding coefficient f (FIS), total-population inbreeding coefficient F (FIT) and among-population genetic differentiation coefficient θ (FST), among-population genetic differentiation coefficient calculated on allele frequencies adjusted for null allele estimates FST (null) and the estimator of actual differentiation Dest, [Total number of alleles (A), the effective number of alleles (Ae), observed (Ho) and expected heterozygosity Click here for additional data file.S6 TableO), expected (HE), and unbiased expected heterozygosity (UHE) and inbreeding coefficient (FIS) are shown.Mean number of alleles per locus (A), effective number of alleles (Ne), allelic richness (Rs) and private allelic richness (PAR) standardized to eight individuals from the original number of trees per population, observed (H(DOCX)Click here for additional data file.S7 TableWilcoxon’s signed-rank’ test , shifted(DOCX)Click here for additional data file.S8 TableQ) of each predefined common walnut population in each of the four (K = 4) clusters, two (K’ = 4) sub-clusters for cluster 1, two (K” = 2) sub-clusters for cluster 2 and two (K”‘ = 2) sub-clusters for cluster 4 inferred by Bayesian approach using STRUCTURE software . Q-values greater than 0.75 are reported in bold.Percentage of membership (admixture proportion-(DOCX)Click here for additional data file.S9 TableSsimul.< Sobs.).Model checking of the most likely scenario inferred in the first stage (scenario 5a) and in the second stage (scenario 6b) of DIYABC analysis. Deviation of summary statistics computed for the observed dataset from the posterior predictive distribution of the most likely scenario is given as a proportion of data sets simulated from the posterior having a value lower than the observed dataset ((DOCX)Click here for additional data file.S1 VideoJuglans-types fossil pollen in Europe and western Asia before the LGM and during the Holocene.Distribution of the radio-carbon dated (MOV)Click here for additional data file.


Pinna nobilis. To address a large geographical scale, partial sequences of cytochrome oxidase I  were used to evaluate phylogeographical patterns in the Western Mediterranean, and in the whole basin using overlapping sequences from the literature (243 bp). Additionally, we combined (1) larval trajectories based on oceanographic currents and early life-history traits and (2) 10 highly polymorphic microsatellite loci collected in the Western Mediterranean. COI results provided evidence for high diversity and low inter-population differentiation. Microsatellite genotypes showed increasing genetic differentiation with oceanographic transport time (isolation by oceanographic distance (IBD) set by marine currents). Genetic differentiation was detected between Banyuls and Murcia and between Murcia and Mallorca. However, no genetic break was detected between the Balearic populations and the mainland. Migration rates together with numerical Lagrangian simulations showed that (i) the Ebro Delta is a larval source for the Balearic populations (ii) Alicante is a sink population, accumulating allelic diversity from nearby populations. The inferred connectivity can be applied in the development of MPA networks in the Western Mediterranean.For marine meta-populations with source-sink dynamics knowledge about genetic connectivity is important to conserve biodiversity and design marine protected areas (MPAs). We evaluate connectivity of a Mediterranean sessile species,  For most benthic marine species, the exchange of individuals between populations occurs primarily during a pelagic stage2. Exchange is influenced by oceanographic processes , topography, larval behaviour and species life-history traits3. The measurement of connectivity remains extremely challenging due to poor understanding of the interactions between dispersal and oceanic features. However, the combination of oceanographic and genetic tools4 has made it possible to estimate the influence of seascape variables on connectivity estimated with genetic markers .Understanding marine connectivity is crucial to implement effective conservation measures and designing representative MPA networks8. This study aims to investigate connectivity patterns in this region as baseline knowledge to enable better design of MPA networks. We use the pen shell Pinna nobilis as a model species, a Mediterranean endemic and endangered bivalve. The pen shell can reach more than 1 m length9 and is ecologically important in providing hard substratum for colonization by many benthic species in its soft natural habitat, Posidonia oceanica meadows10. Consequently, any population disruption could have cascading effects on the associated benthic community11. Due to anthropogenic impacts (e.g.12) and the loss and fragmentation of its natural habitat13, the pen shell P. nobilis is on the list of endangered species of the Mediterranean Sea  and it is protected under the European Council Directive 92/43/EEC (Annex 4). However, despite more than 20 years of protection, abundances and densities of P. nobilis are still very low in many areas14. Such endangered species with small (effective) population size may be predicted to have low genetic diversity due to bottlenecks and drift, and to have reduced connectivity due to limited fertilization success of propagules when populations have small sample sizes and low density15. Thus, assessing diversity and connectivity among Pinna nobilis populations is fundamental to help in the design of a network of MPAs for conservation in the Mediterranean Sea.The Mediterranean Sea is a global marine biodiversity hotspot where high levels of endemism coexist with intensive anthropogenic pressures on marine biodiversity18 and nuclear19 DNA sequences (18S and 28S). Recently, 10 microsatellite loci for P. nobilis were designed and tested in two populations from the Balearic Islands20. These are faster evolving genetic markers providing higher resolution than mtDNA, rendering them a better choice for studies of contemporary population connectivity and enabling the capture of more recent demographic patterns21.Until now, the genetic structure of the pen shell has only been studied in the Eastern Mediterranean and in the Tyrrhenian and Sardinian Seas using mtDNAP. nobilis at a broader scale, improving thus the coverage of the current geographic range. We then zoom into our study area, where we employed a multidisciplinary approach combining microsatellite loci20 and Lagrangian simulations of theoretical dispersal probabilities of the larvae based on hydrodynamics and early life-history traits of the species. Specifically, we aim to (i) study the phylogeographical pattern of P. nobilis in the Mediterranean with mtDNA markers (COI); (ii) assess the genetic diversity of the populations of P. nobilis in the Western Mediterranean Sea using microsatellites; (iii) infer the connectivity pattern between the populations of P. nobilis from the Balearic Islands and the Mediterranean mainland Coast of Spain and France; (iv) identify source and sink populations for this species in the Western Mediterranean Sea; and (v) use this information to suggest areas of conservation priority for a network of marine protected areas.Here, we extended the sampling design of the previous mitochondrial analyses (COI) to the north-Western Mediterranean basin (a region from which genetic information is lacking) in order to understand the genetic variability of 22 of the Regional Oceanic Modeling System (ROMS). ROMS is implemented over a domain that encompasses the Western Mediterranean Sea, from 7.8°W to 9.2°E and from 33.4°N to 44.5°N. The horizontal grid is 681 × 574 points with a resolution of 2.1 km (1/40°) and the vertical discretization considers 42 sigma levels, allowing the representation of mesoscale structures in this region. The bathymetry was acquired from 1′ topography database23. The simulations were nested and initialized from the Mercator PSY2V4R3 simulation24. Hourly outputs from a regional configuration of the atmospheric model Weather Research and Forecasting (WRF25); are used to force ROMS using a bulk formula26. Similar configuration has been used and validated by27.The oceanic simulations were performed at 6 localities in the Western Mediterranean Fig. , using tth of each year and lasted for a period of 4 months. However, due to the lack of data assimilation in the ocean model, a short spin-up (3 weeks) was used to avoid too much drift of the ocean model from observed conditions. Because of this, simulations were used only from the 23rd of June of each year; corresponding to the beginning of time frame larval propagules are expected in the water column (pelagic period of P. nobilis larvae from end June–September).Due to great inter annual changes in current patterns the simulations were performed from year 2010–2014. The model was started on June 1P. nobilis larvae) were released and backtracked in the 6 sampling locations . The particles’ location at each time was determined using a fourth-order Runge-Kutta method. Thus, the model is able to determine the origin of larvae ending up at each sampling location, identifying potential source populations.In total, almost ~100,000 particles were launched. Once released, the particles acted as drifters embedded in the circulation flow fields and were backtracked for the pelagic period of P. nobilis, tissue samples from 6 localities . This opening device was designed to obtain a maximum aperture of 1.2 cm, according to the natural range of shell aperture of P. nobilis9. The mantle tissue of individuals was preserved in 95% ethanol and stored in 1.5 ml eppendorf tubes.To investigate the genetic structure of P. nobilis populations, juveniles were sampled with larval collectors modified from28. Two collectors per sampling locality were deployed in June and recollected in November 2014. Each device consisted of 2 independent replicate polyethylene mesh bags for oyster aquaculture filled with a mesh  that mimic P. oceanica rhizomes. These bags were attached at 5 m depth to a rope that was fixed to a buoy. The buoy was suspended at 2–3 m depth to keep the bags afloat. After recollection, 90 post larvae were obtained in Banyuls, 35 in Mallorca and 1 in Alicante. These recruits were stored in 1.5 ml eppendorfs with 95% ethanol. No post larvae were obtained in the other localities, as collectors were lost due to unknown reasons (storms or human contact). In order to have an equivalent and representative number of post larvae of each location, solely 35 post larvae from Banyuls and Mallorca were used.In order to assign juveniles to adult 29. A fragment of 590 bp of the cytochrome oxidase I gene was amplified by PCR using the universal primers HCO2198 and LCO149030. Each PCR reaction mixture was performed in 20 μl total volume containing 50 ng of 1:50 diluted genomic DNA, 1.4 μl MgCl2 (25 mM), 0.16 μl dNTPs (2 mM), 3 μl of each primer (10 μM), 2 μl PCR GoTaq Flexi buffer and 0.1 μl GoTaq Flexi DNA Polymerase (Promega). Amplifications were performed in a thermocycler (Applied Biosystems®): 2 min at 95 °C, 35 cycles at 95 °C for 50 s, 50 s at an annealing temperature of 49 °C, and, 1 min 20 s at 70 °C and a final extension at 72 °C for 7 min. Amplicons were sequenced in an automated capillary sequencer (ABI PRISM 3130).DNA was extracted from 57 individuals, around 10 per site, following the protocol of20.Using the same DNA extraction protocol mentioned above, genomic DNA was extracted from 204 individuals (134 adults and 70 post-larvae). Afterwards, all 204 individuals were genotyped using ten microsatellite loci2 (25 mM), 1 μl dNTP’s (2 mM), 0.5 μl mM of each primer (10 μM) , 4 μl GoTaq Flexi buffer and 0.1 μl GoTaq Flexi DNA Polymerase (Promega). PCR conditions were as follows: 3 min at 95°, 35 cycles of 50 s at 95°, 50 s at annealing temperature20, 1 min at 72° and a final elongation for 5 min at 72 °C. Amplicons were separated using an ABI PRISM 3130 automated capillary sequencer. Alleles were scored in STRAND software v. 2.4.5931 using the 350 ROXTM size.Microsatellites amplification was carried out in different PCR reactions  and were composed of 20 μl of reaction mixture, containing 50 ng of 1:50 diluted DNA template, 1.2–1.6 μl of MgCl32. After adding 235 COI sequences available from the literature from 24 Pinna nobilis in the Tyrrhenian and Sardinian Seas and in the Eastern Mediterranean Sea  and expected (HE) heterozygosities were estimated using ARLEQUIN v. 3.1133. Deviations from Hardy-Weinberg equilibrium (HWE) were characterized by the inbreeding coefficient (FIS) with GENETIX v. 4.0540 and P-values where calculated GENEPOP v. 4.241. Putative scoring errors were checked with MICRO-CHECKER v. 2.2.342 and FreeNA v. 9.343 was used to to evaluate possible differences between estimates of global and pairwise FST values including and excluding null alleles . The assumption of linkage equilibrium was tested in GENEPOP 4.242.Allelic frequencies, observed  of the allele frequencies to detect differences and similarities between populations, using the BiodiversityR48 package in R software. Finally, the population genetic structure was explored with the software STRUCTURE v. 2.349, a Bayesian clustering method that assigns individuals to groups (k) without prior information. The analysis was run under the admixture model49 with K ranging from 1 to 9 (n° of sampled populations plus three) and 20 independent runs with a burn-in of 100,000 iterations and a run-length of 500,000 iterations. The most likely K (number of groups) was inferred using the DeltaK criterion50 with STRUCTURE HARVESTER51.The quantification of genetic differentiation was established through 52 under the Bayesian assignment method53. Adult genotypes of each of the six sites were used as reference populations and juveniles  were then either assigned or excluded from each of the populations using the Monte Carlo re-sampling approach 54. Juveniles were considered immigrants when the probability of been assigned to any population was lower than 0.05 (type I error). When a juvenile showed probabilities of assignment greater than 0.05 to only one population it was assigned to that population. Finally, when a juvenile was assigned to more than one population (with p > 0.5) it was considered to have originated from an unsampled source.Juveniles were assigned to adult populations using GENECLASS v. 2.0M = m/μ, where m is the fraction of the new immigrants in the population per generation and μ is the mutation rate of the gene) were obtained with the program MIGRATE v. 3.2.755. In order to determine source and sink populations between connected localities and to obtain more accurate results (Migrate-n works better with ≤3 populations), we divided our localities in 3 analysis according to the clusters identified by STRUCTURE. In each analysis we included the three sites that showed the highest estimated membership proportion to each of the clusters: (1) BA, DE and AT, (2) AT, MU and IB and (3) DE, IB and MA. These analyses were conducted under the Bayesian inference approach and involved a Markov Chain Monte Carlo search of 10000 discarded trees per chain followed by 5000 steps with parameters recorded every 500 steps, a uniform prior on theta  and a uniform prior on migration . Convergence was checked by inspecting posterior distributions of the parameters.Estimates of migration rates (56); in IBD v. 1.52. The oceanographic distance (MOD) and time (MOT) between each grid cell of the Lagrangian trajectories was quantified as in57:i, j) is the distance from grid cell i to grid cell j, M is the number of particle transitioning from i to j and T is the transit time from grid cell i to grid cell j.Finally, to determine whether genetic differences were related to the Median Oceanographic Distance (MOD) and the Median Oceanographic transport Time of larvae (MOT), Mantel tests were implemented . In those cases, the MOD and MOT of that pairs of population was established to be ≥than the maximum oceanographic distance and time calculated for all the populations.For the trajectory of each pair of population, all intermediate positions were used to calculate the MOD and MOT. The shortest average distance (MOD) and time (MOT) for each pair of populations was used as inP. nobilis (20 days: Iris Hendriks pers. comm.). The rest of the pairs of populations exchanged larvae between each other within their pelagic life-time  fragment of COI was aligned with available Genbank sequences, obtaining a 243 bp sequence alignment for 292 es Table . Most haes Table . The hapAt a Western Mediterranean scale, the 590 base pair (bp) of COI also showed low nucleotide and high haplotype diversity across the 57 individuals collected at six localities Table . SequencThe Mediterranean-wide analysis (using 243 bp of COI) showed no clear division between Western and Eastern Mediterranean basins and indicated the Venetian Lagoon as the most distinct population. At a Western Mediterranean scale, genetic similarities were found between Delta, Alicante, Mallorca, Ibiza and the Western Mediterranean haplogroup defined by . In contrast, Banyuls and Murcia showed significant genetic differentiation with this haplogroup Table . The Med3b was restricted to populations from the Tyrhenian and Sardinian Sea , which shared in total six haplotypes  with populations from the Western Mediterranean mainland. Longer COI sequences revealed solely 5 shared haplotypes: 1a , 2a , 3a (shared between Banyuls and Alicante) and two haplotypes shared between Mallorca and Ibiza (4a and 5a). All locations, except Murcia, presented exclusive haplotypes  and the sampled Western Mediterranean localities with longer COI sequences (597 bp) the statistical parsimony network of the COI haplotypes exhibited a star structure  24 populations from the whole Mediterranean basin; 2) 6 Western Mediterranean populations, revealed an unimodal distribution  and mean expected heterozygosity (HE) of P. nobilis adults were high , with Alicante showing the highest and Banyuls the lowest values. P. nobilis juveniles  presented similar allelic diversity and expected heterozygosity values  was positive and significant at all locations (Adults and Juveniles). None of the loci presented large allele dropout or any other evidence of genotyping errors; however, evidence of null alleles was detected. Although the high FIS observed could be explained by the presence of null alleles at some loci, these were not removed from the analyses as no bias due to null alleles was found when comparing the original data set with that excluding null alleles . In contrast, the migration rates of the population from Alicante suggest that these populations could act as a sink population, receiving genes from Murcia . The migration rates of the Ebro Delta showed a predominant gene flow from this locality to Ibiza and from this population to Mallorca, pinpointing the Ebro Delta as a potential source population for the Islands  Table .Assignment tests demonstrated that only 10% of the sampled juveniles were originated in one of the adult populations Table . JuvenilFST (genetic differentiation estimate) and Median Oceanographic Distance and Median Oceanographic Transport Time was found  have high diversity and low inter-population differentiation. This discovery has strong consequences for conservation of this endangered species, as it does not support the highest concern hypothesis of small isolated populations. The results of the multiple analyses all indicate that P. nobilis throughout the Mediterranean comprises one lineage that underwent a recent population expansion from a single original population with low effective population size, as hypothesized by18. The causes of this past event might have been linked to historical variations in climate and/or habitat availability, given the strong dependence of the species on seagrass habitat.This study shows that on a broad scale, P. nobilis from the Venetian Lagoon differed from most of the studied P. nobilis populations, likely as a result of the semi-enclosed nature of the Adriatic Sea. Genetic differentiation between the Western and Eastern Mediterranean was not detected, possibly due to the low resolution of the analysis (243-bp COI sequences). Although18, with slight longer COI sequences (338-bp), detected subdivision between Western and Eastern basins, which, together with the low diversity observed in the eastern side, supports the hypothesis of an eastward expansion during the colonization of the Mediterranean. This has been proposed as the most common route of natural colonization of the Mediterranean in marine species61, although there is evidence for other patterns (e.g.62). A hypothetical eastward expansion would also agree with the suggestion of63 that the Pinnidae originated and diversified in the Indo-pacific and subsequently invaded the Atlantic Ocean and the Mediterranean Sea eastwards.The populations of P. nobilis estimated with higher resolution genetic markers (microsatellites) was strongly influenced by oceanographic currents. This result highlights the importance of ocean currents and pelagic larvae transport time in shaping the population connectivity of Pinna nobilis in the study region. The considerable distance between Banyuls-Murcia and Mallorca-Murcia resulted in significant genetic differentiation between these sites, following a pattern of isolation by distance, as described in65. Banyuls and Mallorca also experienced limited gene exchange, possibly due to the Balearic Front, a density barrier created by the NC flowing southward along the Western Mediterranean Coast and the Atlantic water flowing north-eastwards66. This genetic break was also been described for several fish species67.Within the Western Mediterranean, the connectivity pattern of P. nobilis populations with the mainland. The locality of Ibiza appeared to be a key population in order to ensure connectivity, receiving genes from the mainland  and exporting them to Mallorca. Migration rate estimates pointed the Ebro Delta as a source population, exporting genes to Ibiza and the latter to Mallorca. It is noteworthy that over 90,000 P. nobilis individuals inhabit the waters of Alfacs Bay, the largest population so far reported in shallow water68. This could be attributed to optimal growth conditions at this locality, because semi-enclosed bays such as Alfacs Bay in the Ebro Delta, with low hydrodynamic energy and a certain input of organic material, favour the growth of P. nobilis69. If we consider the number of individuals able to spawn in this source population, many sites of the Balearic Islands could benefit from the number of exported larvae. The southern shore of Alfacs Bay (the Banya Sandspit) was included in the Ebro Delta Natural Park in 1986 and is also part of the Natura 2000 site70. However, free access to high-density areas of P. nobilis and the lack of regulation of the boating activity is causing damage and mortality of individuals in the bay68.Microsatellite loci and Lagrangian simulations revealed no isolation of the Balearic Migration patterns reflected the influence of the AC, which enable larvae to be transported from Murcia to Alicante, the latter accumulating genetic diversity as a sink population. Both genetic markers detected the highest genetic diversity in Alicante. Genetic diversity may be high as a consequence of long-term stability of large populations (absence of bottlenecks) but higher diversity might also simply result from a sink population structure. These scenarios do not have the exact same consequences for species conservation, as the second case suggests a population whose high diversity cannot be maintained in the absence of migration, should the sources be impacted.P. nobilis here inferred provides useful information to be applied in the development of a MPA network in the Western Mediterranean. This network of MPAs should protect areas with specific interest in terms of their diversity and connectivity with other populations of P. nobilis, as the functioning of populations is dependent upon processes of reproduction and recruitment from a surrounding area71. The Ebro Delta should be included in a network of MPAs as a source population for the Balearic Islands. Localities with high genetic diversity, like Alicante , should also be included in a network of MPAs, as they retain the genetic diversity of P. nobilis in the Western Mediterranean. Finally, this network should maintain connectivity between the Mainland with the Balearic Islands to prevent isolation and avoid the loss of genetic diversity. This could be accomplished by protecting the sampled location of Ibiza, which presents gene flow with the populations from the localities of Alicante, the Ebro Delta and Murcia.The connectivity pattern of P. nobilis populations of the Central Spanish Mediterranean sea72, among them, Alicante, Murcia, Ibiza and Mallorca. Our study highlighted Alicante as one of the populations with the highest genetic variability values in all the Mediterranean Sea  suggest that there are populations with high diversity values in the Tyrhenian and Sardinian seas that share several haplotypes with the Western Mediterranean populations  with mortality rates up to 100% of the a Tables , which muences 24 bp suggeons Fig. . In thisSupplementary Tables


Halyomorpha halys) is an East Asian species now established across North America and Europe, that in the Eastern United States of America (US) and Italy is causing significant economic losses to agriculture. After US populations were shown to originate from Northern China, others have tried to source BMSB populations now in Canada, Switzerland, Italy, France, Greece, and Hungary. Due to selection of different molecular markers, however, integrating all the datasets to obtain a broader picture of BMSB’s expansion has been difficult. To address this limitation we focused on a single locus, the barcode region in the cytochrome oxidase I mitochondrial gene, and analyzed representative BMSB samples from across its current global range using an Approximate Bayesian Computation approach. We found that China is the likely source of most non-native populations, with at least four separate introductions in North America and three in Europe. Additionally, we found evidence of one bridgehead event: a likely Eastern US source for the central Italy populations that interestingly share enhanced pest status.Human mediated transportation into novel habitats is a prerequisite for the establishment of non-native species that become invasive, so knowledge of common sources may allow prevention. The brown marmorated stink bug (BMSB,  However, in order for any non-native species to become established it must first successfully navigate the first phase of the invasion process, which is transportation into a novel habitat3. Inadvertent human-mediated transportation of organisms often occurs due to global trade of goods4. Therefore, the physical and energetic limitations of long distance dispersal are bypassed and can result in unintended rapid and widespread establishment of non-native species6. If non-natives become destructive or dangerous in their novel habitats, and spread rapidly beyond their introduced location, they are considered invasive1. Prior to becoming invasive, newly introduced non-native species can go unnoticed for some time until populations reach levels that result in significant economic impacts and high management costs8. This danger is inflated for countries that trade regularly, as trade has been positively correlated with introduction rates of non-native species9. Research on invasive species has led to recommendations that preventive actions be taken to limit the impacts of new invaders10, such as a better understanding of the source and likelihood of introductions, followed by novel strategies that allow early detection of incipient non-native populations12.Over the past few decades the introduction of non-native species, which are species that have been moved by human action into novel habitats beyond their natural geographic range13. While that strategy works when there are clear genetic discontinuities among the native populations being evaluated, it can still be difficult to assign formal probabilities to alternatives (e.g. whether the introduced population came from a native source or secondarily from another introduced population (i.e. bridgehead effect))14. This is especially the case when the analysis is based on a single or a few genetic loci, which has been common in the analyses of non-model organisms with worldwide distributions18. Approximate Bayesian Computation (ABC) is a statistically robust Bayesian analysis that allows the direct comparison of multiple introduction hypotheses (known as scenarios) providing distinct likelihoods for each. ABC performs inference computations under a Bayesian framework19 that takes into consideration putative evolutionary histories, or in this case introduction histories, by quantifying support for modeled scenarios given the data provided. ABC accomplishes this by generating simulated data, known as pseudo-observed datasets (PODs), and randomly selecting (with replacement) the PODs closest to the observed data (i.e. the genetic data collected) by a Euclidean distance measure. These PODs then have relative posterior probabilities calculated via a logistic regression estimate, which allows the user to determine the most probable invasion scenario20. Of course, ABC does have its drawbacks. First, the computational time and power necessary to run moderately complex invasion models can be fairly demanding, at times taking several days to complete one analysis. Second, the scenarios to be evaluated are created by the modeler, and can be subject to bias unless all possible alternative hypotheses are included. Finally, the data must be of sufficient quality to address the desired questions being modeled in the scenario. Without appropriate data, estimates can be biased and inappropriate conclusions can be drawn. When correctly executed, however, ABC is an excellent analysis method for determining the most probable invasion pathways of unintended introductions13.Approaches to identify the source of an invasive species often make use of genetic methods that compare haplotypes or allele frequencies from potential native ranges with those in the introduced population(s)Halyomorpha halys (Stål)). BMSB is native to Northeast Asia, but non-native populations of BMSB were first detected in the United States of America (US hereafter) in Allentown, Pennsylvania in 199621. Since then the species has been detected in at least 40 US states, Canada, and several European countries24. BMSB can cause significant damage both to agricultural crops and ornamental plants25, such as the documented damage to tree fruits in New Jersey and Pennsylvania in 2006 and 200726 and WV and MD in 2010 and 201127. BMSB feeding injury has resulted in significant economic impacts to growers; a one-year loss in excess of 37 million USD across the mid-Atlantic in apples alone, as well as 100% losses to peaches in Maryland25, and 60–90% losses of peaches in New Jersey 28 during a population outbreak in 2010. Since the outbreak in 2010, established BMSB populations have been detected as far south as Georgia and as far west as Michigan, which experienced high populations in 2016 and injury in apples ; and in the Pacific Northwest, specifically Oregon and Washington, where injury to hazelnuts and small fruits has been documented30. To evaluate possible BMSB source populations, Xu et al.31 analyzed genetic variation at two mitochondrial loci in US specimens collected between 2004–2008, as well as in specimens from several populations across the native range of China, Republic of Korea, and Japan. They found best match to populations from the northern region of China, around Beijing, and low mtDNA haplotype diversity in the US populations relative to the native range, possibly indicating a single introduction of a small number of individuals31.Here we incorporated an ABC approach to unravel the pathways of the worldwide expansion of the brown marmorated stink bug 35. The first detection of BMSB in Europe was in Zurich, Switzerland in 200736, and soon after it was collected in several locations throughout Switzerland37. To find the source population(s), and determine the invasion pathways, genetic analyses were carried out in Switzerland, Italy, France, Greece, and Hungary using mtDNA40. The likely source(s) for many of the established European populations was not determined due to insufficient power of the analyses to match or reject the few native populations examined39. Of note, Cesari et al.40 hypothesized that BMSBs in Lombardy, Italy were likely the result of southward spread from Switzerland , while the population in Emilia-Romagna, Italy was an independent introduction into Italy possibly from the US40. Again, due to insufficient samples from the native range, the authors were unable to determine the likely source.In Europe, there are currently known established BMSB populations in Switzerland, Italy, France, Greece, Hungary, Serbia, and Romania40 and an expanded sampling in the US and native ranges. By combining these datasets, we aimed to shore the power of the analyses and increase the likelihood of ascertaining the source(s) of all non-native populations. We therefore amassed and analyzed the largest BMSB dataset to date, with more than 900 individual DNA sequences (both existing and newly generated) including 214 from its native range in China, the Republic of Korea, and Japan. Although we are using a single mtDNA locus, we make use of ABC as our analysis framework to reach robust conclusions about invasion pathways of this global pest species.To address the limitations of the individual studies and provide an updated analysis of the worldwide expansion of BMSB, we developed a meta-analysis using existing dataet al.31, as well an additional 80 specimens collected in 2016 in the US (48), Japan (28), and the Republic of Korea (4). Combined with preexisting data from the European studies, we amassed a total of 916 individual DNA sequences for our global dataset  previously reported (Table We amplified and sequenced 685 bp of cytochrome oxidase I CO1) for 110 of the 139 specimens examined by Xu  for 110 et al.31 supported their conclusion that China was the source population for the initial introduction of BMSB into the US (probability (p) = 0.89)  Table . When we9) Table . The hap9) Table .Table 2PTests for multiple introductions to the US indicated that Northwestern US populations (in Washington and Oregon) were also likely separate introductions from China (p = 0.88) Fig. , Table 2Regarding questions two and three, which were to identify the source(s) of the introduction into Europe (excluding Greece) and to assess the likelihood of a bridgehead from the US to Europe Table , our resNext, we addressed question four, which was to determine whether there were multiple introductions into Europe and identify the sources Table . We did Halyomorpha halys) from across the world, as well as multiple populations from the native range, to assess the most probable worldwide invasion pathways. To accomplish this, we combined published genetic data from four studies of BMSB in non-native regions using the CO1 marker40, added new sequences from both the introduced and native range as needed and feasible, and performed a Templeton, Crandall, and Sing (TCS) haplotype network analysis41 and Approximate Bayesian Computation (ABC) analyses to quantify pathway probabilities. Sadly, our analyses excluded published sequences that did not match the CO1 barcoding region  as well as specimens from the most recent discovered populations in Serbia, Romania, Russia, ARA, Georgia, and Bulgaria due to lack of access to specimens of BMSB from those populations. Though ABC does have its drawbacks , we carefully tried to minimize bias in our study by modeling all scenarios under numerous alternative hypotheses to prevent forcing a desired outcome. Furthermore, we kept many questions at the country level due to low sample size in several parts of the native range and lack of genetic differentiation at the barcode CO1 locus. Case in point, unlike Xu et al.31 we did not attempt to identify the specific location(s) of origin within China. Instead, the worldwide analyses provide insights into broader patterns of expansion of this economically important pest species.We developed an analysis that included representative infestations of non-native brown marmorated stink bugs . This is an important result because numerous invasion events all from China, possibly even from the same location, in a relatively short amount of time, indicate the existence of an export pathway that if identified could be closed leading to major decreases in the spread of BMSB across the World. The next step then is to identify the invasion vectors, and while careful vetting of cargo potentially harboring BMSB may be onerous, it may prevent the much higher economic losses associated with this agricultural pest continuing to spread globally.While we recommend evaluating the invasion pathways of the more recent detections into other parts of Europe , and found evidence of one long-distance bridgehead event, most critically our analyses indicate that the expansion of BMSB across the world is still primarily sourced from China Fig. . This i40. The study performed in the US primarily sequenced regions of the cytochrome oxidase 2 (CO2) locus and the control region (CR), with very limited sequencing in the cytochrome oxidase 1 (CO1)31. In contrast, Canadian and European studies examined sections of CO1, CO2, and Cytochrome b (Cyt b)40, though CO1 was the only common locus between these studies , with Proteinase K incubation overnight (minimum of 8 hours) to ensure complete digestion.We started by sequencing CO1 for many of the specimens from the US and Asia in Xu 44 used by the European studies40 with primers LCO1490 (5′-GGTCAACAAATCATAAAGATATTGG-3′) and HCO2198 (5′-TAAACTTCAGGGTGACCAAAAAATCA-3′). Amplifications were accomplished in 20 μl reactions consisting of 1 × PCR buffer , 2.5 mM MgCl2, 100 μM of each dNTP, 200 nM of each primer, 1 unit of Amplitaq Gold DNA polymerase  and approximately 20 ng gDNA. The protocol was optimized to run at an initial denaturing temperature of 96 °C for 10 minutes, followed by 45 cycles of the following steps: denaturing at 96 °C for 20 seconds, annealing at 50 °C for 30 seconds, and extension at 72 °C for 30 seconds. Final extension was completed at 72 °C for 2 minutes. All PCRs were run on a Veriti 96-Well Thermal Cycler . We visualized amplifications in a 1% agarose gel with Ethidium Bromide, and selected DNA fragments of appropriate size for sequencing. Successful amplicons were cleaned using ExoSAP-IT , and mixes of 25pmoles of primer and 20 ng of template DNA were sent for cycle sequencing and sizing . Cycle sequencing was performed using both the forward and reverse primers to create a consensus sequence and increase haplotype reliability. Chromatograms were cleaned and aligned in Sequencer 5.1 . All sequences were evaluated for insertions and deletions, as well as translated to amino acids to check for stop codons and limit the presence of nuclear copies45. We then exported the full CO1 contig in nexus format and created a TCS haplotype network using the program PopArt46 . These questions were chosen not only to check assumptions made in the literature regarding the invaded range in prior studies40, but also to address hypotheses only testable with a worldwide dataset. We modeled these invasion pathway scenarios based on the initial findings of the genetic data, possible pathways hypothesized in other papers40, and other a priori factors that can affect introductions . We then compared appropriate scenarios against each other to quantitatively determine which had the highest likelihood of having taken place based on logistic posterior probabilities.Once we obtained a global dataset of variants of CO1 in BMSB we conducted several analyses using Approximate Bayesian Computation (ABC). Specifically, through our analyses we sought to address four major questions regarding the spread of BMSB globally Table . These 20. Before addressing our four major questions, we sought to evaluate the performance of this analysis method, based on a single mitochondrial locus, by testing the hypothesis that China was the native source population of the US introduction, as proposed by Xu et al.31 using two loci. For parity, we limited the analysis to the same specimens analyzed at the time. To accomplish this, we developed three simple scenarios and tested them against each other: (1) US haplotypes were sourced from the China population; (2) US haplotypes were sourced from the Japan population; and (3) US haplotypes were sourced from the Republic of Korea population. All three scenarios were weighted equally, with priors set to fit a uniform distribution and the US effective population size restricted to be lower than the native populations. We determined the evolutionary model to be used via the program PartitionFinder 1.1.147 in Python v2.7 under an unpartitioned whole gene model scheme with a MrBayes filter. We did so to ensure the evolutionary models selected by PartitionFinder would be limited to the model options supported by the DIYABC software. Once complete, we used the recommended Hasegawa, Kishino and Yano (HKY) model48 and set priors as shown in Table We selected the program DIYABC to carry out our analysesOnce the computations were complete, we performed a pre-evaluation of the scenarios and prior combinations using a principal component analysis (PCA) approach within the program. We inspected both the PCA plot and the numerical values and proceeded only when the observed dataset was within the cloud of pseudo-observed datasets (PODs) and the numerical values displayed summary statistics for simulated data with very few values below the observed dataset . We then computed the posterior probabilities for each of the scenarios to assess which was most likely to have occurred given our dataset, and evaluated confidence in scenario choice using posterior based error.31, we began developing models for our four questions regarding the global invasion of BMSB. To address question one  Caline Table , with thWe addressed both questions two and three Table  by firstet al.40 that the southern-most population in Italy (Emilia-Romagna) was a bridgehead event from the US, while the northern most population (Lombardi) was a dispersal from broader Europe. We tested this with two scenarios, one involving a dispersal event from Northern Italy to Southern Italy and the other a bridgehead event from the Eastern US into Southern Italy (Figure We addressed question four Table  by firsty Figure . Lastly,y Figure .Accession numbers to all downloaded and generated sequence data analyzed are provided within a supplementary table Table , sorted Supplementary Table and Figure


Fundulus heteroclitus inhabiting the heavily polluted New Bedford Harbour (NBH) estuary have shown inherited tolerance to local pollutants introduced to their habitats in the past 100 years. Here we examine two questions: (i) Is there pollution-driven selection on the mitochondrial genome across a fine geographical scale? and (ii) What is the pattern of migration among sites spanning a strong pollution gradient? Whole mitochondrial genomes were analysed for 133 F. heteroclitus from seven nearby collection sites: four sites along the NBH pollution cline (approx. 5 km distance), which had pollution-adapted fish, as well as one site adjacent to the pollution cline and two relatively unpolluted sites about 30 km away, which had pollution-sensitive fish. Additionally, we used microsatellite analyses to quantify genetic variation over three F. heteroclitus generations in both pollution-adapted and sensitive individuals collected from two sites at two different time points (1999/2000 and 2007/2008). Our results show no evidence for a selective sweep of mtDNA in the polluted sites. Moreover, mtDNA analyses revealed that both pollution-adapted and sensitive populations harbour similar levels of genetic diversity. We observed a high level of non-synonymous mutations in the most polluted site. This is probably associated with a reduction in Ne and concomitant weakening of purifying selection, a demographic expansion following a pollution-related bottleneck or increased mutation rates. Our demographic analyses suggest that isolation by distance influences the distribution of mtDNA genetic variation between the pollution cline and the clean populations at broad spatial scales. At finer scales, population structure is patchy, and neither spatial distance, pollution concentration or pollution tolerance is a good predictor of mtDNA variation. Lastly, microsatellite analyses revealed stable population structure over the last decade.Populations of the non-migratory estuarine fish  NBH has been contaminated since 1940 [Fundulus these adaptive responses to contaminants occurred rapidly [et al. [Ne) relative to neighbouring unpolluted areas. The fish evaluated by Reid et al. [−1 dry weight (dw) of PCB126). However, the polluted habitat in NBH extends at least 5 km south of this collection site, with sediment pollution levels decreasing outwards towards Buzzards Bay, where pollution remains around 541 ng g−1 dry weight of PCB126, and Fundulus populations inhabit the entire stretch of polluted estuary (hereby referred to as pollution cline). Work by Nacci et al. [126 levels depending on their local habitat, and show differential survival . Polluthan 1 km ,18. Sincb), is inhabited by pollution-sensitive individuals. Two additional pollution-sensitive populations were collected approximately 30 km from NBH. Finally, we used microsatellite markers to test the genetic signal's temporal stability over the last decade (2000–2008). Microsatellite analyses were conducted on two populations, one within and one outside NBH, at two time points, 1999/2000 and 2007/2008. Both these markers, mtDNA and microsatellites, are highly sensitive to recent demographic events [In addition, we used mtDNA sequences to characterize population structure and connectivity between and among pollution-adapted and pollution-sensitive populations. We collected fish from five sites distributed along the NBH pollution cline . Four offigure 12.F. heteroclitus were reconstructed from raw reads from the National Centre for Biotechnology Information (NCBI) Short Read Archive (SRA) BioProject ID: PRJNA291654 published in [b) lie on a steep pollution cline between 1 and 3 km of each other ; the remaining three  lie in adjacent, relatively unpolluted habitats [figure 1a) and NBH sites in 2007 and 2008, respectively, using minnow traps and seine nets. Tissue samples from historical populations (WI-1999 and NBH-2000) were provided by the US EPA Atlantic Ecology Division. DNA for microsatellite analyses was extracted from 30 fish each from the NBH and WI populations using the animal tissue spin-column protocol of a Qiagen Dneasy® Tissue Kit. Eight oligonucleotide primer pairs designed for the amplification of trinucleotide ATG microsatellite repeats were chosen from Adams et al. [Complete mtDNAs of ished in . These ss et al. . Forwardet al. [Genotyping at eight microsatellite loci was conducted at the Centre for Applied Genomics at the Hospital for Sick Children in Toronto, Canada. A mutation step consisting of one nucleotide base pair was discovered post-genotyping at the FhATG-17 locus. This was assumed to be an error because the most common allele at FhATG-17 consists of a 135 bp fragment and the incompatible mutation step (which yielded a 136 bp fragment) was only present in three individuals, one of which was a homozygote. It is very unlikely that such an extremely rare allele would exist as a homozygote and, therefore, the four 136 alleles were changed to 135. Fragment lengths flanking the trinucleotide repeats were determined for each locus by aligning primer sequences with sequence data made available by Adams et al.  through π = K/L, where L is the sequence length and K is the estimated average number of nucleotide differences [S), haplotype number (h) and haplotype diversity (hd) were conducted using DNAsp v. 5.10.1 [FST) were conducted in Arlequin v. 3 [et al. [F. heteroclitus. For all pairs of populations compared, we asked whether a panmixis model , or a stepping-stone model (i.e. two collection sites are discrete demes with asymmetric migration), would better fit the data. All analyses were conducted using uniform priors for both theta (Θ) and k M→ i . We used complete mtDNA sequences as input using the ‘sequence data’ option. This parameter ensures that the input is read as haplotypes (i.e. SNPs are not considered independent). Runs were performed using four heated chains . Runs were allowed a burn-in of 1 × 105 steps, and the long chains ran with 5 × 105 steps. Run convergence was assessed using effective sample size metrics (ESS). Model evidence was compared based on marginal likelihoods (mL) using a Bezier curve approximation . Statistical analyses were done in R v. 3.3.2 [−1 dry weight of PCB126) and pollution tolerance (LC50 to PCB126); these data were obtained from Nacci et al. [F. heteroclitus mitochondrial genome is fully mapped in the NCBI database; thus, SNPs were mapped to genes by direct association to the database. Protein topology analyses were done using TOPCONS [FST values were calculated in MSA with 100 000 data permutations. MSA was also used to estimate measures of genetic variation including theta (θ) and expected heterozygosity (HE).Genome estimates of nucleotide diversity (ferences ), segreg. 5.10.1 . Populatuin v. 3  with 100uin v. 3  using a  [et al. , all MIG [et al.   [Mitochondrial genomes from 192  samples  were map samples . Any seq samples . It is iples [D) ; as such3.2.K) is similar in both groups . Individual estimates of K for each population were close to the group's average with NBH (the most polluted population) showing the highest K (9.069), and HS the lowest (K = 6.052). Haplotype diversity (hd) [hd general = 0.985 ± 0.004). MtDNA nucleotide diversity (π) estimates for adapted and sensitive populations were within the standard error (s.e.) of each other . Site-specific π values showed similar diversity levels relative to the mean group π and to each other. We also report π for mitochondrial functional genes: subunits 1, 2, 3, 4 and 4 L of the NADH dehydrogenase gene (ND), subunits I, II and III of the Cytochrome oxidase gene (COX), the Cytochrome B gene (CytB), subunits 6 and 8 of the ATP-synthase gene (ATP) and non-protein-coding genes rRNA-12S and rRNA-16S. The D-loop is also shown . The D-loop is a highly variable region, and some of the variant sites were excluded from the alignment due to a high level of singletons and missing nucleotides (N) not seen in other mtDNA regions. As a result, our π estimates for the D-loop probably underestimate the real nucleotide diversity of the populations. Overall, 91 SNPs are shared between both population groups; 36 SNPs are polymorphic in the pollution-adapted populations and monomorphic in the pollution-sensitive populations, and 24 SNPs are polymorphic in pollution-sensitive populations and monomorphic in pollution-adapted ones. Pairwise comparisons between adapted and sensitive populations resulted in an FST value for mtDNA of 0.0299 (p < 0.001). Pairwise FST analyses of inter-population (between collection sites) differentiation are shown in FST values were low  and statistically non-significant. Additionally, comparison of HS versus NBH, and HS versus MA also showed statistical significance (p < 0.05). Analyses of molecular variance (AMOVA) between the pollution-adapted and pollution-sensitive populations revealed that most of the genetic variation was found within the individual sites . Other sources of genetic variance, variation among grouped sites (1%) and between the groups (2%), contributed marginally to the global variance.Estimates of mtDNA genetic diversity are shown in ity (hd)  is high 3.3.a,b). All other haplotypes radiate in a star-like fashion out from the major haplotype. This is consistent with the known historical phylogeography of Fundulus [c). The most polluted habitats, NBH and SYC, share the most haplotypes. In addition, NBH showed an excess of haplotypes containing at least one non-synonymous SNP (a). When considering the total number of segregating SNPs, NBH harbours a higher proportion of non-synonymous mutations segregating across its private haplotypes (b). PCA on haplotype frequencies among all sites is shown in figure 3c. Jointly, the first two principal axes explained 44% of the variance. The first principal component isolates the SR population from all other populations. The second principal component primarily isolates the MA population from the inhabitants of the pollution cline. Amounts of sediment pollution (PCB126), and LC50 were added to the PCA as supplementary variables. We also conducted a second PCA with the cline populations . PC 1 of this analysis (32% variation explained) strongly segregated the most polluted populations (i.e. NBH and SYC) from the rest of the cline. Factor loadings for PC 1 showed that three haplotypes had strong positive correlations with populations in the most polluted sites . Sixteen additional haplotypes showed positive correlations between 0.56 and 0.70. The supplementary variables, sediment PCB126 and LC50, showed correlations of 0.73 and 0.63, respectively.A haplotype network constructed using the infinite sites model reveals the presence of a major haplotype at high frequency across all sites except FL and SYC a,b. All Fundulus ; 75% . This signature of IBD reveals the existence of two main patches in the data: the pollution cline and MA, and SR (a). If MA is removed from the analysis (see Discussion), the statistical association of IBD strengthens . Variation partition analysis (VPA) allows estimating the proportion of mtDNA genetic variation explained by a single predictor variable controlling for the other two predictors. At broad spatial scales, geographical distance explained 14.74% of the variation, followed by sediment pollution concentration of PCB126 (1.51%) and lastly by LC50 (less than 1%). The remaining variance was residual. These results suggest that IBD drives a portion of mtDNA variation at the broad scale. At the fine scale , Mantel tests for IBD were not significant . The analysis also revealed that the spatial structure of cline populations is patchy (b), and none of the three predictor variables significantly explained mtDNA variation.We characterized correlations between genetic distance (estimated from whole mtDNA haplotypes) and predictor variables at two spatial scales: broad scale  and fine scale (the pollution cline only). At the broad scale, a Mantel test showed a marginally significant non-random association between genetic and spatial distance  for population pairs across the cline and neighbouring sites ranged from 4500 m/µ to 30 000 m/µ. The analyses showed that migration is high among proximal populations; however, it decreases substantially with respect to distal populations (SR and MA) . Migration rate estimates for all populations relative to NBH echo this pattern , correlation of migration rates and distance is not significant).We estimated migration rates assuming a stepping-stone model . For each pair of populations, we tested whether panmixis or a model with asymmetric migration between two discrete populations would better fit the data. We also estimated migration between NBH and all other populations. For all comparisons, the two-population model outperformed the panmixis model . Migration rates . The substitution in COI, however, is presumed to retain the identity of the initiator codon. Montooth et al. [COI and ND1 in Drosophila. We observed an initiation codon other than AUR (R = A or G) in the F. heteroclitus COI gene (ATC). This initiation codon has been observed in Mus [Fundulus. All amino acid changing SNPs were called with a sequencing depth of at least ten reads per site [Across all the dataset, 16 (17%) segregating SNPs caused non-synonymous substitutions in mtDNA protein-coding genes . These SNPs, however, were not consistent with the pattern of environmental pollution. Thus, there is no evidence to suggest that pollution has acted as a selective agent on the mtDNA. We observe non-synonymous substitutions occurring in genes: h et al.  identifid in Mus ; howeverper site . These aper site , predictSegregating polymorphisms were also seen in non-protein-coding regions of the mtDNA . Nine segregating, non-singleton SNPs were seen in transfer RNAs and mapped to their respective structures. One SNP in tRNA-Ala mapped to the anticodon loop region . Substitutions occurring in rRNA regions showed the highest percentage of individuals with segregating sites in SR (31.8%) followed by FL (33.3%), PA (25.0%), SYC (17.6%), HS (16.6%), MA (11.1%) and NBH (9.1%). Substitutions affecting only tRNAs showed the highest percentage of segregating sites in individuals in PA (33%) followed by FL (33%), HS (27%), NBH (22%), SYC (17.6%), MA (11.1%) and SR (4.5%).3.6.FST = 0.005, p > 0.05). Overall, the four samples (two sites at two time points) are not highly differentiated. The global FST value for one locus, FhATG-20 is significant and shows higher differentiation . Overall, pairwise FST values between different sites during the same time period (1999/2000 and 2007/2008 populations) are small and statistically non-significant . Pairwise FST value estimates between samples from the same location during different years are low and non-significant suggesting stable genetic structures at either site.Consistent with our mtDNA analysis, all microsatellite loci of WI-1999, WI-2007, NBH-2000 and NBH-2008 showed very low genetic differentiation among populations, which was not significant . Furthermore, the global FST value at FhATG-20  is not significant for pooled sites . On the other hand, when time periods are pooled, the global FST value is slightly higher and is significant . There is no sign of change in the levels of genetic diversity in the NBH (2000 and 2008) population between the time points surveyed (a). When time periods are pooled, there are a few loci that show reduced diversity in NBH (b). However, with this number of loci it is impossible to assess the significance of these outlying loci. It should be noted that the locus showing the largest diversity reduction in NBH is FhATG-20, the same locus exhibiting a significant FST value.It is unclear whether the differentiation between WI-1999 and NBH-2008 is driven by location or by time (see Discussion). To further explore this problem, independent analyses were carried out pooling the data across sites and across years. When sites are pooled, the global surveyed a. When ty in NBH b. Howeve4.πadapted = 0.064 ± 0.004%, πsensitive = 0.056 ± 0.005%; figure 3b). We also characterized population structure and connectivity among populations. This analysis revealed two different population structure dynamics depending on spatial scale. At broad spatial scales, we observed that IBD explained a portion of the population structure. However, at fine spatial scales, distance does not appear to play a significant role. Lastly, based on our analyses of eight microsatellite loci, population structure appears stable over the last decade  Is there pollution-driven selection on the mitochondrial genome across a fine geographical scale? and (ii) What is the pattern of migration among sites spanning a strong pollution gradient? Our results showed no evidence for a selective sweep of mtDNA in the polluted sites. All sites showed similar levels of differentiation at the level of genetic variation between population groups , the rate at which deleterious or mildly deleterious mutations are purged is reduced [et al. [a,b). An additional hypothesis can be considered: the high proportion of non-synonymous SNPs in NBH could be explained by increased mutation rates resulting from pollution exposure. This is a possible alternative as recent studies have shown that PCB exposure can induce mutations as well as chromosome breaks [Our analyses did not detect any mtDNA haplotype sweeping through pollution-adapted populations, thus rejecting our hypothesis for directional selection on mtDNA. A possible corollary of this hypothesis is that selection is driving multiple mtDNA haplotypes to fixation, and selective interference of these haploid, non-recombining, mtDNAs is preventing the fixation of any one haplotype. While possible, this seems unlikely because it requires that all competing mtDNA haplotypes show nearly identical fitnesses to be maintained under haploid selection . However reduced . A secon reduced . Both th [et al. . They di [et al. ), they de breaks . Testing4.2.Ne generations [et al. [Ne generations. The opposite would be true if one were to extrapolate recent migration rates from coalescent estimates. Interestingly, Samarasin et al. [Our estimates of migration among populations were conducted using MIGRATE's coalescent framework. As such, the estimates presented here represent gene flow averages over erations . However [et al.  showed tn et al.  also shon et al. ).c,d). Our analysis had stronger support for models considering each sampling locality as a discrete deme . Similarly, the analysis also showed that migration rates among the pollution cline are high, including the pollution-sensitive population (HS). However, migration rates relative to the flanking pollution-sensitive sites  are reduced . Moreover, while all migration rates were asymmetric, there were no overall trends towards immigration or emigration. As mentioned above, it is difficult to extrapolate current gene flow rates (i.e. after the onset of pollution) from coalescent estimates. However, our findings do not capture any striking differences in gene flow between pollution-adapted and pollution-sensitive sites. One possibility is that there is not enough resolution in our data to detect nuanced changes in recent gene flow relative to historical trends. However, our data support that migration is open among all demes in the pollution cline , regardless of pollutant concentration.Here we present coalescent-based migration estimates among populations within the pollution cline and flanking sites c,d. Our  reduced c,d. More4.3.et al.'s [c). These results also showed that haplotype frequencies were correlated to the amount of sediment pollution and pollution sensitivity. While suggestive, our data do not allow us to establish a causal link between mtDNA variation and pollution-driven selection. If pollution-driven selection does act on mtDNA, it is considerably weaker than selection on specific nuclear loci .F. heteroclitus' high habitat fidelity and low dispersal rates [figure 4a and Fundulus from NBH and SYC sold in Buzzards' Bay for bait may have been involved. However, a more parsimonious explanation is that the apparent similarity is inflated by the loss of haplotype information in the process of estimating genetic distances (i.e. ignoring the linked nature of SNPs in mtDNA). This explanation is supported by the shared haplotype matrix (c) and MIGRATE, which accounts for inter-SNP dependency and treats the data as haplotypes.At broad scales, our analyses showed that IBD was an adequate predictor for mtDNA variation among reference and cline populations. Overall, these results are consistent with al rates . We weree matrix c and MIGWe used microsatellite loci to characterize broad-scale changes in population structure across time. While most of our comparisons did not show statistical significance, the comparison between WI-1999 and NBH-2008 was significant. The spatial distance between the sites combined with drift across approximately three generations may be large enough to explain this observation. Testing this hypothesis would require a larger sampling effort with multiple genetic markers across time points. Overall, the microsatellite data supports stable population structure in NBH across time points.5.Ne during rapid adaptation, a rapid population expansion following a pollution-bottleneck, or a case of increased mutation rates due to exposure to pollutants. Finally, our demographic analyses suggest that IBD influences the distribution of mtDNA genetic variation at broad spatial scales. This is consistent with Fundulus' high site fidelity and low dispersal. At smaller scales (e.g. within the cline), mtDNA variation is patchy and poorly predicted by either distance among microhabitats, sediment concentrations of PCB126 or tolerance to PCB126 (LC50).Our data do not provide evidence for mtDNA pollution-mediated selection in these populations. To the contrary, mtDNA genetic variation is similar throughout all populations. Moreover, we observe fine- and broad-scale population structure between and within clean and polluted habitats based on haplotype frequencies. These differences are particularly pronounced on the proportion of haplotypes carrying non-synonymous SNPs in the most polluted habitat, NBH. We believe this is consistent with either a reduction in