Lissotriton montandoni, Lm) and introgression from its congener, the smooth newt . Two substantially differentiated groups of Lm populations likely originated from separate refugia, both located in the Eastern Carpathians. The colonization of the present range in north-western and south-western directions was accompanied by a modest loss of variation; admixture between the two groups has occurred in the middle of the Eastern Carpathians. Local, apparently recent introgression of Lv alleles into several Lm populations was detected, demonstrating increased power for admixture detection in comparison to a previous study based on a limited number of microsatellite markers. The level of introgression was higher in Lm populations classified as admixed than in syntopic populations. We discuss the possible causes and propose further tests to distinguish between alternatives. Several outlier loci were identified in tests of interspecific differentiation, suggesting genomic heterogeneity of gene flow between species.Genetic variation within species is commonly structured in a hierarchical manner which may result from superimposition of processes acting at different spatial and temporal scales. In organisms of limited dispersal ability, signatures of past subdivision are detectable for a long time. Studies of contemporary genetic structure in such taxa inform about the history of isolation, range changes and local admixture resulting from geographically restricted hybridization with related species. Here we use a set of 139 transcriptome-derived, unlinked nuclear single nucleotide polymorphisms (SNP) to assess the genetic structure of the Carpathian newt ( Most species are genetically structured, and genetic structure is often observed at multiple spatial scales Genetic variation within species is commonly structured in a hierarchical manner which may result from superimposition of processes acting at different spatial and temporal scales. For example the impact of major climatic oscillations is clearly visible in the patterns of genetic differentiation observed currently in temperate and boreal species In species with limited dispersal capabilities, signatures of past subdivision are detectable for a long time Detecting, quantifying and interpreting genetic structure requires appropriate tools. Single nucleotide polymorphisms (SNPs) are powerful markers well suited for assessing genetic structure Lissotriton montandoni, Lm), a species which has apparently survived the glacial period in the Carpathians L. vulgaris, Lv). Previous studies Lm is genetically differentiated across its range in both mitochondrial and nuclear (microsatellites) genome. Patterns of genetic differentiation and species distribution modeling performed by Zieliński et al. Lv resulted in complete mtDNA replacement in Lm, very little recent interspecific nuclear gene flow was suggested by microsatellite markers Here we investigate the genetic structure of populations of the Carpathian newt , 7 syntopic populations in which both species co-occur  and 8 populations of Lv   ; Table 1Animal samples were collected under permits: DOPozgiz-4200/II-78/3702/10/JRO provided by the Polish General Director for Environmental Protection, 03.04.12 No. 67 provided by the National Academy of Sciences of Ukraine and 3256/9.07.2010 provided by the Romanian Commission for Protection of Natural Monuments. Samples were collected with institutional animal ethics approval (number 101/2009), issued by the First Local Ethical Committee on Animal Testing at the Jagiellonian University in Krakow. Tissue samples were collected according to the requirements of these institutions: adult newts were captured by dip netting and tissue samples from tail tips were taken under anesthesia. Immediately after recovery from anesthesia, newts were released at the collection site. The sampling locations were not privately owned or protected in any way.Lm individuals sampled to encompass the genetic diversity of the species  occur in a TGM which produced an unambiguous hit to a single Xenopus gene and to not exhibit high similarity to other TGMs in the newt reference transcriptome; this criterion was applied to minimize the incidence of false “SNPs” derived from paralogous regions; ii) have a minimum sequencing depth of 15 x and minimum genotype quality of 30 phred; iii) be located at least 60 but not more than 1000 bp from the exon boundary; the latter filter was used because last exons of many genes are long and consist mostly of 3′ untranslated regions (UTR) which are poorly conserved between species; thus the length of such exons in the newt could not be reliably determined and particularly long last “exons” may be artifacts of misassembly SNPs were identified in liver transcriptomes of six  species . TranscrHE), was calculated in the R package adegenet AR) was calculated in FSTAT 2.9.3.2 HE and AR using inverse distance weighting (IDW) in ArcGIS v 10.0 . Pairwise FST values between populations and their significance were computed in Arlequin 3.5 FST matrix. Principal component analysis (PCA) was performed in R using adegenet. The significance of correlations between genetic and geographical distances was calculated using the Mantel test implemented in IBDWS FSTLm, which included only morphologically pure Lm populations and Lm&Lv comprising Lm, Lv and syntopic populations. We ran 10 analyses for each K 1-15 for Lm and 10 replicate runs for each K 1–20 for Lm&Lv dataset. In each case, the admixture model was applied and the runs consisted of 250 000 MCMC burnin steps followed by 1 000 000 post-burnin iterations. We performed inferences under the model of correlated allele frequencies for Lm, whereas the uncorrelated model was used for Lm&Lv dataset, because Lm and Lv populations were expected to be more divergent on average. To determine the most likely number of genetic clusters supported by the data, we calculated ΔK, a measure of second order rate of change in the likelihood of data Allele frequencies for each locus, tests of Hardy–Weinberg equilibrium and tests of linkage disequilibrium (LD) were calculated in GENEPOP 4.1.2 FST outliers was performed. In order to minimize the number of false positives the outlier detection was performed under a hierarchical island model Lm and for interspecific differentiation. In each case 50 000 coalescent simulations with 2 groups of 100 demes were performed to obtain the null distribution of F-statistics. We selected candidate loci based on FST or FCT values falling into the 1% upper and lower quantile as suggested by Excoffier et al. FCT allows for identification of outlier loci between the groups of populations whereas FST identifies outlier loci among populations after accounting for higher-level structure To identify markers departing significantly from the genome-wide average of differentiation among populations a scan for Lm and 112 (81.6%) in Lv (Genotyping was successful for 139 out of 192 markers (72%) and these were used for population genetic analyses  (DRYAD e%) in Lv . No sign%) in Lv . Tests fHE) ranged from 0.05  to 0.29  with a mean of 0.19 (SD = 0.07). HE was significantly higher in Lm than Lv  most likely due to ascertainment bias, as only markers known to be polymorphic in Lm were assayed. Within Lm HE was lowest in population 6, isolated in the Ukrainian Podolian Upland and highest in population 20 located in the Romanian Transylvanian Plateau, and ranged from 0.19 to 0.27 respectively, with a mean of 0.23 (SD = 0.01) . HE in syntopic populations spanned a broad range from very low  to the highest overall , most likely depending on the frequency of both species in the population (The expected heterozygosity ( = 0.01) . Within pulation .Lm populations varied from negligible (FST<0.001 P = 0.39 between 14 and 17 located in the northern part of the Romanian Carpathians), to strong (FST = 0.408 P<10−3 between populations 1 and 24 at the opposite limits of the species distribution) , and overlapped only slightly with the distribution of pairwise FST between populations from different groups  . The MDSes range . Pairwision tree .The presence of two genetic clusters is also evident from individual-based analyses.K = 2 as the most likely number of clusters in the Structure analysis , but allelic richness was higher in the southern group   and within genetic clusters   PC1 (15.8% of variance explained) separated newts from northern and southern populations . The Evaanalysis . Structuanalysis . AMOVA aanalysis . Whereas 0.0042) . As coulP<0.001) .Lv populations around the Carpathians is stronger and presumably deeper than that within Lm. A deep split between populations outside the Carpathian belt and those in the Carpathian Basin is visible in the population tree  from two populations of the nominal subspecies L. vulgaris vulgaris  and one was the isolated locality 1 in the Sudetes Mountains; the average admixture in these populations was 8.5%. No admixture of Lm genes was detected in Lv populations. The comparison of the average proportion of admixture on both genetic backgrounds in syntopic populations demonstrated that the mean admixture was very low, ca. 2% and that the proportion of admixture did not differ  between Lv and Lm backgrounds.Strong differentiation between analyses , 5a. AMOanalyses . Three oanalyses . Howeveranalyses , 6. K = together , S6. StrLm  revealed 14 FST outliers (10.0%) at the significance level of 0.01: 9 loci  showed an excess of differentiation among populations  and 5  loci were less differentiated than expected under neutrality   were identified as candidates for diversifying selection between the northern and southern Lm groups and two  as candidates for balancing selection (The scan for outliers performed in lection) . Three Felection .Lm and Lv was performed excluding syntopic populations (26–32). A total of nine (6.5%) FCT outlier loci were identified: eight  were more differentiated than expected under the neutral model and one (126) was less differentiated . Hence expansion was apparently not accompanied by severe bottlenecks and thus only a minor fraction of variation has been lost. The strongest reduction in genetic variation occurred in locality 6 in the Podolian Upland isolated from the main portion of the range. This population is a remnant of a geographically remote group of Lm populations Expansion from refugia is commonly accompanied by loss of variation L. vulgaris graecus suggests that a combination of isolation by distance, probably due to limited dispersal, and spatial clustering due to historical fragmentation and/or landscape barriers occurs in Lissotriton newts at both micro- and macroscales.Salamanders often exhibit low individual mobility and strong philopatry Lv nuclear alleles into some Lm populations. This is contrary to the findings of Zieliński et al. Lm individuals, our study did not use diagnostic markers. This could be considered a weakness if viewed from the perspective of classical studies of hybrid zones which usually employed a limited number of diagnostic markers. However, because of the widespread genomic heterogeneity of interspecific gene flow Lm. The current study demonstrates two peculiar features of Lm x Lv hybridization. First, appreciable (>3%) introgression was detectable only locally, in four of 25 sampled Lm localities. In these populations most individuals were introgressed and the average admixture of Lv genes was 8.5%. Second, in the introgressed Lm populations, admixture was stronger than in seven syntopic localities, where it was barely detectable. Thus current syntopy, even if it leads to occasional hybridization, as shown by a single putative F1 hybrid, does not necessarily cause introgression. This is somewhat surprising because a study of a Lm/Lv hybrid zone at microscale detected strong assortative mating but also found that syntopy was almost universally accompanied by some admixture Lm populations testify, nuclear introgression of Lv alleles into Lm populations extends beyond syntopy, but does not permeate into the core of the Lm range.A major finding of the present study is substantial introgression of Lv is strongly differentiated genetically Lv groups come into contact with Lm populations in the Carpathian Basin, and outside the Carpathian belt. If introgression is neutral, the observed pattern may result from expansion-related phenomena Lm would bring Lv genes onto its genetic background. A comparison of the two isolated Lm populations may be instructive in this respect. Population 1 at the western margin of the species range, probably the result of postglacial or more recent expansion, has recently introgressed Lv mtDNA and shows clear evidence of nuclear introgression. Another isolated population (6), close to the postulated refugial area of the northern Lm group and possibly surviving in situ for a long time, shows no trace of nuclear introgression. Scenarios related to the Currat et al. Lm by Zieliński et al. Local differences in the extent of introgression may be explained by several mechanisms. The introgressed populations may be simply located at the tails of local hybrid zones, and would thus be sampled entirely by chance. However other potential explanations deserve consideration. Local ecological conditions may either favor introgression or delay removal of introgressed alleles by selection Lm and Lv. Models distinguishing two groups within Lv, inside and outside of the Carpathian basin, as well as two groups within Lm can be evaluated and hypotheses regarding the timing and extent of gene flow may be tested within an Approximate Bayesian Computations framework In addition to laboratory experiments which are difficult to perform in this system due to logistic reasons, two other kinds of analyses would be informative with respect to the causes of the apparent differentiation in the extent of introgression. Examination of several transects through hybrid zones in the context of local environmental conditions and relative species abundance could be informative as demonstrated in multiple systems Lm and between Lm and Lv. Such candidate loci may signal various forms of selection acting on the markers themselves or at linked sites Lm-Lv comparison indicate heterogeneity of interspecific gene flow in nuclear protein coding genes. Dramatic discordance in the propensity for interspecific gene flow occurs between the mitochondrial and nuclear genome .Outlier loci were detected both within Lm. Two substantially differentiated groups of Lm populations likely originated from separate refugia, both located in the Eastern Carpathians. The colonization of the present range in north-western and south-western directions was accompanied by a modest loss of variation. Local introgression of Lv alleles into several Lm populations was detected. Introgression was higher in Lm populations classified as admixed than in syntopic populations. We discuss the possible causes of this discrepancy and propose further tests to distinguish between alternatives. Several outliers were identified in tests of interspecific differentiation, suggesting genomic heterogeneity of gene flow between species. The shape of genomic heterogeneity at various stages of species divergence is of major interest for the understanding of the buildup of differentiation across the genome and Lm/Lv is a promising study system in this respect.Using a panel of transcriptome-derived SNP markers, our study has demonstrated that isolation in glacial refugia and limited dispersal have been the main factors determining the genetic structure of Figure S1Expected heterozygosity. (a) interpolated geographic gradients in L. montandoni (Lm), (b) means for all populations: triangles – Lm, diamonds – syntopic, circles – Lv.(TIF)Click here for additional data file.Figure S2Histograms showing the distribution of pairwise FST between populations within the northern and southern L. montandoni groups and between groups.(TIF)Click here for additional data file.Figure S3Identification of the number of groups (K) in Structure analysis for L. montandoni. (a) Evanno et al. (2005) method; (b) means and standard deviations (SD) of the ln-likelihood of the probability of data for various values of K.(TIF)Click here for additional data file.Figure S4Interpolated geographic gradients of allelic richness in L. montandoni.(TIF)Click here for additional data file.Figure S5Isolation by distance in L. montandoni. Relationships between pairwise FST and log-geographic distances are presented for all populations and populations within northern and southern groups separately.(TIF)Click here for additional data file.Figure S6Identification of the number of groups (K) in Structure analysis for L. montandoni and L. vulgaris. (a) Evanno et al. (2005) method; (b) means and standard deviations (SD) of the ln-likelihood of the probability of data for various values of K.(TIF)Click here for additional data file.Table S1Characteristics of the single nucleotide polymorphisms (SNP) used in the present study.(XLSX)Click here for additional data file.Table S2Results of the tests of the Hardy-Weinberg proportions for all loci in all populations. Uncorrected P values are given; “-“ indicates that test was not performed due to insufficient polymorphism.(XLSX)Click here for additional data file.Table S3Pairwise FST values. Non-significant (P<0.05) values marked in red.(XLSX)Click here for additional data file.


Bellamya aeruginosa is a widely distributed Chinese freshwater snail that is heavily harvested, and its natural habitats are under severe threat due to fragmentation and loss. We were interested whether the large geographic distances between populations and habitat fragmentation have led to population differentiation and reduced genetic diversity in the species. To estimate the genetic diversity and population structure of B. aeruginosa, 277 individuals from 12 populations throughout its distribution range across China were sampled: two populations were sampled from the Yellow River system, eight populations from the Yangtze River system, and two populations from isolated plateau lakes. We used seven microsatellite loci and mitochondrial cytochrome oxidase I sequences to estimate population genetic parameters and test for demographic fluctuations. Our results showed that (1) the genetic diversity of B. aeruginosa was high for both markers in most of the studied populations and effective population sizes appear to be large, (2) only very low and mostly nonsignificant levels of genetic differentiation existed among the 12 populations, gene flow was generally high, and (3) relatively weak geographic structure was detected despite large geographic distances between populations. Further, no isolation by linear or stream distance was found among populations within the Yangtze River system and no signs of population bottlenecks were detected. Gene flow occurred even between far distant populations, possibly as a result of passive dispersal during flooding events, zoochoric dispersal, and/or anthropogenic translocations explaining the lack of stronger differentiation across large geographic distances. The high genetic diversity of B. aeruginosa and the weak population differentiation are likely the results of strong gene flow facilitated by passive dispersal and large population sizes suggesting that the species currently is not of conservation concern. The level of genetic diversity in natural populations is determined by the interplay of mutation, migration, hybridization, drift, and selection Harrison . The relFreshwater gastropods represent interesting models to study the effects of extrinsic factors on the population genetic structure due to their primarily sessile lifestyle Nekola . Many snNe)  and Yellow (N = 2) river systems and two populations from isolated plateau lakes (N = 2). For all populations, we genotyped two genetic marker systems with different evolutionary speeds: the mitochondrial COI (cytochrome oxidase I) gene and seven microsatellite loci. We used the data to estimate genetic diversity and differentiation and effective population sizes and to explore the demographic history of local populations. Specifically, we aimed to differentiate between two main competing scenarios and their potential underlying evolutionary mechanisms: (1) limited genetic divergence and high intrapopulation diversity of local populations would suggest large population sizes and good historic connectivity, (2) In contrast, low genetic diversity and strong differentiation of local populations could be the result of a sessile life style, the occurrence in lacustrine systems, large geographic distances isolating populations, and the proposed strong anthropogenic pressure (overharvesting and fragmentation).In this study, we sampled 10 populations of Bellamya aeruginosa populations were sampled from 10 interconnected lakes in the Yellow (N = 2) and Yangtze (N = 8) river systems and two isolated Plateau lakes (N = 2) in China .Genomic DNA was extracted with the DNeasy Blood and Tissue Kit  following the manufacturer's protocol and conserved at −20°C until further use. We amplified partial r et al. . PCR pror et al. . A totalh) and nucleotide diversity (π) were calculated with DNASP v. 5  over time. The appropriate substitution model was determined as HKY+I+G with jModeltest v. 2  were genotyped at seven microsatellite loci (Table S1). The PCR amplifications were performed in a total volume of 10 μL: 1× PCR buffer , 20–40 ng genomic DNA, 0.5 mmol/L of each primer, 200 mmol/L of each dNTP, 1.5 mmol/L MgCl2, and 0.25 U of Taq DNA polymerase . Thermal cycling was performed with a TProfessional Thermocycler  under the following conditions: 94°C for 5 min, 35 cycles at 94°C for 45 sec, annealing at 50–55°C depending on the marker for 30 sec (details in Table S1), 72°C for 30 sec, and a final extension at 72°C for 10 min. Forward primers were 5′‐labeled with HEX, ROX, or TAMRA (Table S1). The sizes of the fluorescently labeled PCR products were estimated according to an internal size marker (LIZ‐500) on an ABI PRISM 3700 sequencer (Applied Biosystems). Fragment lengths were scored using STRAND v. 2.3.48 .All samples (NA), the expected (HE) and observed heterozygosities (HO), FST, and the inbreeding coefficients FIS . We used LDNe as implemented in NeEstimator v. 2  was assessed assuming an admixture ancestry model with correlated allele frequencies; 20 independent runs were performed with 500,000 MCMC repetitions at each run discarding a burn‐in of 150,000 iterations. We tested K from 1 to 13 and used the ad‐hoc statistic ΔK  using Mantel tests with 10,000 randomizations as implemented in IBD v. 1.52 Bohonak . PopulatCOI sequences with a length of 709 bp, 81 of which represented unique haplotypes. The alignment contained 167 variable sites (23.6 %), 136 of which were parsimony informative. Nucleotide (π) and haplotype diversities (h) across all populations were 0.038 and 0.985, respectively. Tajima's D and Fu's Fs were not significant in any population.We generated 116 P < 0.007). Probability values for HE excess were > 0.813 for all populations except QJ (Qingjiang River) (P = 0.679) (Table NA) ranged from 5 to 25 across the seven microsatellite loci. The mean NA across all loci ranged from 11.0 for Dianchi Lake (DC) to 14.7 for Chaohu Lake (CH) (Table HO) and expected heterozygosity (HE) were overall high across all populations with mean values ranging from 0.657 to 0.782 and 0.785 to 0.864, respectively (Table P = 0.008) and QJ (P = 0.016), suggesting that most studied populations were under mutation–drift equilibrium.No evidence of scoring errors was revealed by MICRO‐CHECKER. However, the presence of null alleles was suggested for several loci (Table S2). However, no systematic distribution of null alleles across populations was found and only few populations were affected; therefore, all loci were maintained for further analyses. GENEPOP showed deviations from HWE for all populations at multiple loci even after Bonferroni correction . Most ΦST and all FST values were low and not statistically significant (P > 0.05). AMOVA of the microsatellite data revealed that 93.31 % of genetic variation was explained by intrapopulation variation, while the remaining 6.69 % (P < 0.05) explained variation among populations. For mitochondrial sequences, the amount of variance explained by differences between populations was similar (6.03 %) , BY  and HH populations  Fig. . STRUCTUr = 0.4888; P = 0.011, Fig. COI data  between 1.29 (QJ→DT) and 74.76 (LZ→QJ) (Table M = 188.47) and the lowest was for CH (M = 90.03), while the highest gene flow out of a population was from LZ (M = 251.94). Similarly, many migration rate estimates from BAYESASS were moderate to high, ranging from 0.01 to 0.237 ; the remainder varied from 0.008 to 0.009 .The effective population size estimates derived from LDBOTTLENECK analyses of the microsatellite data revealed no evidence of a recent bottleneck for most of populations except for the HH and QJ populations. No significant heterozygosity excess was detected in any locality under the TPM.The Bayesian skyline plots detected relatively stable population sizes throughout the last 2 mya for most populations Fig. . The oveB. aeruginosa supports our first scenario: we found high levels of genetic diversity and strong population admixture across the 12 studied populations of B. aeruginosa for both mitochondrial and nuclear markers despite a sessile life style and large separating geographic distances. Current population sizes appear to be mostly large, which was also supported by the high genetic diversity and past fluctuations of population sizes appear to be limited. However, the species as a whole seems to have rapidly declined during the mid‐ to Late Pleistocene and postglacially expanded. Yet, no recent bottlenecks were detected with the microsatellite data. Our findings suggest that gene flow is moderate to high among the sampling locations, even between river systems despite vast geographic distances and low active dispersal ability. The results further indicate that the species at the moment can maintain high genetic diversity despite strong harvesting pressure and increasing fragmentation. These findings may be explained by a combination of large population sizes with high standing genetic variation and long‐distance gene flow, potentially facilitated by zoochoric and anthropogenic dispersal. In the following, we discuss each of these findings in detail.Our population genetic analysis of Both marker systems revealed high genetic diversity and low levels of genetic differentiation between local populations Tables , 3. CurrBellamya in plateau lakes, while the Taku glaciation in the early Mid‐Pleistocene and the Lushan glaciation in the Late Mid‐Pleistocene (200–230 ka) ; even isolated plateau lakes receive migrants. Within the Yangtze River for which we have the largest number of samples, no strong isolation by stream distance was detected, suggesting that populations along the stream frequently exchange individuals. The absence of significant isolation by distance and weak geographic signal among populations is not uncommon in snail species  of COI gene in B. aeruginosa samples and the corresponding Fu's Fs value.Figure S2. The most likely value of K (inferred cluster) estimated using Evanno's ΔK‐method.Click here for additional data file.Table S1. Primer sequence for microsatellite markers and optional PCR conditions.Table S2. The frequencies of null alleles across seven microsatellite loci and 12 geographic locations for B. aeruginosa, as suggested by the program MICRO‐CHECKER.Click here for additional data file.


Nebria and Leistus, and using two mitochondrial genes and two nuclear genes, we evaluated the mountain–island effect on alpine carabids and tested the two proposed hypotheses with comparative phylogeographic method. Results from the phylogenetic relationships, network analysis, lineage calibration, and genetic structure indicate that the deep divergence among populations in all L. smetanai, N. formosana, and N. niitakana was subjected to long‐term isolation, a phenomenon in agreement with the nunatak hypothesis. However, genetic admixture among populations of N. uenoiana and some populations of L. nokoensis complex suggests that gene flow occurred during glaciations, as a massif de refuge depicts. The speciation event in N. niitakana is estimated to have occurred before 1.89 million years ago (Mya), while differentiation among isolated populations in N. niitakana, N. formosana, L. smetanai, and L. nokoensis complex might have taken place during 0.65–1.65 Mya. While each of the alpine carabids arriving in Taiwan during different glaciation events acquired its evolutionary history, all of them had confronted the existing mountain ranges.Taiwan, an island with three major mountain ranges, provides an ideal topography to study mountain–island effect on organisms that would be diversified in the isolation areas. Glaciations, however, might drive these organisms to lower elevations, causing gene flow among previously isolated populations. Two hypotheses have been proposed to depict the possible refugia for alpine organisms during glaciations. Nunatak hypothesis suggests that alpine species might have stayed in situ in high mountain areas during glaciations. Massif de refuge, on the other hand, proposes that alpine species might have migrated to lower ice‐free areas. By sampling five sympatric carabid species of  Mountainous Taiwan was created with continuous arc–continental collision of Eurasian and Philippine Sea plates during late Miocene . The tissue was ground in 50 μL QuickExtract solution and then centrifuged for 15 sec before incubation at 65°C for 10 min. Following 15‐sec centrifugation, the sample was transferred to 98°C for 2 min. The resultant genomic DNA was stored at −20°C.Carabids collected were stored in 95% ethanol at −20°C for DNA extraction. Genomic DNA was extracted from metatarsus or metatibia muscle of each ground beetle specimens using the BuccalAmpwingless are listed in Table S2. The PCR assay was performed in a volume of 25 μL containing 2 μL genomic DNA extract, 2.5 μL 10× Taq buffer, 0.5 μL Prime Taq DNA polymerase , 0.4 μL dNTP (25 μmol/L), and 1 μL of each primer (10 μmol/L). PCR programming conditions were 94°C for 2 min as the first denaturation followed by 35 cycles of 94°C for 30 sec, 48–55°C for 30 sec, and 72°C for 1 min, with a final extension at 72°C for 10 min. The PCR product was purified with 1% agarose gel using QIAquick Gel Extraction Kit . The resulting DNA product was sequenced in both strands using Taq dye terminator cycle sequencing kit  and an ABI 377A sequencer. Sequences of COI, 16S rDNA, wingless, and 28S rDNA for these carabids have been deposited in GenBank. The accession numbers for COI, wingless, 16S rDNA, and 28S rDNA are KT306037‐KT306186, KT306187‐KT306330, KT306331‐KT306481, and KT306482‐KT306548, respectively. The sequences of two outgroup species, that is, N. chinensis and N. ohdaiensis, were provided by Dave Kavanaugh (Table S4).Primer pairs used to amplify the mitochondrial COI and 16S rDNA and the nuclear 28S rDNA and Sequences were aligned and edited using BioEdit 7.0 software Hall . The besFST), neutrality test of Tajima's D and Fu's Fs, and the variance component of each genes were performed in Arlequin ver. 3.5 , maximum‐parsimony (MP), and Bayesian inference (BI) methods. ML trees were drawn using RAxML ver. 7.0.3 with substitution model of GTR+I+G  values of the estimated parameter traced with software Tracer v1.5 for each carabid species  based on COI and 16S rDNA was generated to reconstruct the population dynamics of each alpine carabid independently with BEAST v1.8.0 . With most FST values <0.3, the differentiation among populations of N. uenoiana and some populations of L. nokoensis is weak to mild, while high FST values could be found between the southern Yushan population and the other L. nokoensis populations (Table S5).Substantial genetic differentiation among populations of N. niitakana, N. formosana, L. smetanai, and L. nokoensis complex have high sequence variation among populations: on average of 88%, 92%, 79%, and 95% for COI, 16S rDNA, wingless, and 28S rDNA, respectively (Table wingless (83%) and COI (61%) genes, but low for 16S rDNA (13%) in N. uenoiana.Species of D and/or Fu's Fs values for most populations , while it is the southern lineage (Yushan) in L. nokoensis complex.According to outgroup comparison, the speciation events on N. formosana, N. niitakana, the northern L. nokoensis, and L. smetanai took place mainly during 1.65–0.65 Mya. For example, the divergence time between Xueshan and Nanhudashan populations of L. smetanai is 0.84 Mya and that of N. niitakana is 1.38 Mya. For N. formosana, the first divergence between Xueshan and Hehuanshan‐Yushan lineages occurred at 1.65 Mya and that between Hehuanshan and Yushan populations occurred at 0.65 Mya. For L. nokoensis complex, the diversified events within northern group occurred <1.51 Mya and the major diversification among populations of Henhuanshan, Nanhudashan, and Xueshan took place between 0.12 and 0.72 Mya. Multiple shallow lineages are observed for N. uenoiana and the earliest divergence occurred at ca. 0.17 Mya. Obviously, each carabid species must have had its own evolutionary history.Differentiation events among isolated populations of Leistus has remained relatively constant in comparison with Nebria during the past 1 million years  in the informative COI gene between Xueshan and Nanhudashan, being greater than that (ca. 0.10) in Hehuanshan to Xueshan and Nanhudashan (Table S5), indicates that Hehuanshan population might have been the possible origin each for Xueshan and Nanhudashan populations. Taking account into the lower population, identical haplotype was found between Daxueshan and Xueshan populations in two nuclear genes. Since both wingless gene and 28S rDNA show similar haplotype network pattern, we infer that the causing of the sharing haplotype is gene flow between populations, which is different from the scenario of N. formosana.However, northern populations of Nebria uenoiana distributing across a wide elevation range is the only species examined that was not affected by mountain–island effect. Lineage calibration depicting its diversification could be traced to 0.17 Mya. Thus, genetic exchange most likely occurred in the middle elevation or refuge during glaciations, or the gene flow existing among current populations was made possible with the well development of wings of this insect. Moreover, coalescent‐based EBSP data show steady population expansions during LGM and subsequent interglacial contraction (ca. 0.005 Mya).N. uenoiana. The geographical isolation of alpine‐dwelling carabids from mountain ranges represents a typical mountain–island effect which confers these carabids with different history of differentiation in Taiwan. For N. formosana, the divergent one is the northern Xueshan lineage, while it is the southern Yushan lineage in L. nokoensis complex. All alpine carabids had confronted the existing mountain ranges, and each of the them arriving in Taiwan during different glaciation events acquired its evolutionary history. While the current comparative phylogeographical data on most carabid species tend to support the Nunatak hypothesis, those on N. uenoiana and the northern group of L. nokoensis complex, with recent gene flow in populations under certain circumstances, are in agreement with the massif de refuge hypothesis.In this study, we propose the mountain‐isolation model for four codistributed carabid species in Taiwan, with an additional shallow divergence model for the 5th species None declared.KT306037‐KT306186 for COI gene, KT306187‐KT306330 for wingless gene, KT306331‐KT306481 for 16S rDNA, and KT306482‐KT306548 for 28S rDNA.DNA sequences: Genbank accession numbers Table S1. Individuals of each carabid population.Table S2. Forward (F) and reverse (R) PCR primers of each gene for carabids.Table S3. The best‐fit evolutionary models examined from jModelTest.Table S4. Number of sequences for each gene of five carabid species.Table S5.FST values among populations of each Leistus and Nebria species.Table S6. Proportional divergences among populations of each Leistus and Nebria species.Click here for additional data file.


Salvelinus namaycush) from 72 unstocked and stocked lakes. Results showed an increase in genetic diversity and a twofold decrease in the extent of genetic differentiation among stocked populations when compared to unstocked. Stocked populations were characterized by significant admixture at both population and individual levels. Moreover, levels of admixture in stocked populations were strongly correlated with stocking intensity and a threshold value of total homogenization between source and stocked populations was identified. Our results also suggest that under certain scenarios, the genetic impacts of stocking could be of short duration. Overall, our study emphasizes the important alteration of the genetic integrity of stocked populations and the need to better understand determinants of admixture to optimize stocking strategies and to conserve the genetic integrity of wild populations.Stocking represents the most important management tool worldwide to increase and sustain commercial and recreational fisheries in a context of overexploitation. Genetic impacts of this practice have been investigated in many studies, which examined population and individual admixture, but few have investigated determinants of these processes. Here, we addressed these questions from the genotyping at 19 microsatellite loci of 3341 adult lake trout ( Various anthropogenic pressures, such as overexploitation, habitats modifications and non-native wild or domesticated individuals' translocations, may have major impacts on the genetic makeup and evolutionary trajectory of wild populations, possibly resulting in demographic decline  populations from Québec, Canada. Lake trout is a freshwater fish native to North America and inhabiting cold-water lakes. It is long living (up to 49 years) and becomes sexually mature between 7 and 13 years and is iteroparous , 40 were unstocked lakes (n = 1600) and 22 were stocked lakes (n = 971). Of the 10 source lakes, two were never stocked, whereas eight were stocked with local and/or nonlocal individuals. Among lakes sampled between 1974 and 1983, three were never stocked and one was stocked with juveniles produced with its own broodstock after 1962. These samples were used to validate the temporal stability of genetic characteristics within populations never stocked with non-native individuals as contemporary samples were also collected as described above.The stocking history of each stocked lake is recorded by the provincial government since 1900 in a central database. For each stocking event, a standardized stocking form is filed, compiled in the database and carefully verified to detect potential errors. Although the database is reliable, we performed additional validation of the data for the stocked lakes used in this study for further improvements. Lakes were categorized as ‘unstocked’ when no stocking was recorded and as ‘stocked’ when at least one stocking event was documented. The mean number of stocking events in stocked lakes was 18 (range 5–50). A source lake was a lake where broodstock was collected and used to produce juveniles in captivity, which were released in wild populations, usually at age 1+. Of the 72 sampled lakes, 10 were source lakes (2) using a modified version of Aljanabi and Martinez  following a modified version of the manufacturer's Bench Protocol for animal tissues (spin-column protocol). Namely, we incubated samples with proteinase K at 37°C for 3 days. After having discarded flow-through (buffer AW2), we performed a second centrifugation for 1 min at 20 000 g. We then heated up buffer AE at 56°C and used 75 μL of it to perform a first elution. We repeated the elution with a second 75 μL warm AE buffer.DNA was extracted from adipose fin and pelvic fin clip  were analyzed at 19 microsatellite loci using Qiagen Multiplex PCR Kit (Qiagen inc.) . Genescan 500 LIZ  was used as a standard to determine allele sizes, which were scored using genemapper 4.0 (Applied Biosystems Inc).Individuals collected between 1997 and 2011  were estimated using fstat 2.9.3 (Goudet AR) adjusted for the smallest sample size (n = 15) was calculated using HP-Rare 1.0 ] for unstocked and stocked lakes. Strength of the correlation and significance were assessed with Pearson's product-moment correlation coefficient. Expected and observed heterozygosities  were obtained with genetix 4.05  was estimated using the linkage disequilibrium method implemented in LDNe  and between NE and AR. Strength of the correlations and significance were assessed with Pearson's product-moment correlation coefficient.The software 3 Goudet . AllelicFST measures with fstat 2.9.3 .We quantified the extent of genetic differentiation between each pair of populations using pairwise 3 Goudet . We testamova) implemented in arlequin 3.5 (Excoffier and Lischer amovas were performed. The first amova was performed with unstocked populations (n = 42) grouped by 10 regions . The second amova was performed with stocked populations (n = 30) grouped by a subset of five regions where stocking occurred  as the other five did not contain any stocked populations. The third amova was performed with these same five regions but with only the unstocked populations (n = 16) for strict comparison with the above-mentioned amova.We assessed the distribution of genetic diversity among administrative regions, among populations within regions, and within populations using analyses of molecular variance  with k genetic clusters from 1 to the number of lakes plus 3 (number of lakes varied from 9 to 42 according to the group of lakes considered), and with 15 replicates for each k. The first group was composed of all unstocked lakes only. The second to the sixth groups each represented one of the five stocked administrative regions, composed of unstocked lakes, stocked lakes, and all known source lakes used for stocking within each region. The last group was composed of the four lakes with historical and contemporary samples.Individual clustering was achieved using the Bayesian method implemented in Structure run started with a burn-in period of 50 000 followed by 300 000 Markov Chain Monte Carlo (MCMC) steps. For each lake group considered, we selected the best k according to the variation of likelihood  of the local cluster were, respectively, >0.70, <0.30, and [0.30 and 0.70]. For statistical analyses, stocked and unstocked lakes were separated into distinct groups. A chi-square test was then used to test whether differences in proportions of local, admixed, and nonlocal individuals between the unstocked and the stocked groups were significant. This test was repeated for unstocked and stocked groups within each of the five stocked regions. Chi-square was also used to test whether differences in the proportion of these individuals were significant among stocked as well as unstocked groups between regions.To further investigate the impact of stocking, we quantified proportions of fish belonging to local clusters, nonlocal clusters, or to a category of individuals putatively admixed between local and nonlocal populations and representing putative hybrids. For this analysis, we used lakes sampled within the five stocked regions and excluded source lakes. Following Vähä and Primmer , individq-membership) in two ways using R [R Development Core Team (2012)]. Firstly, we applied a logistic regression model to investigate the link between stocking intensity and the membership of stocked populations to the local cluster . Unstocked populations were included in the regression as they were used to assess local q-membership when no stocking was documented. We attributed a value of ‘1’ to populations with a local q-membership >0.50 and a value of ‘0’ to populations with a local q-membership ≤0.50 as few intermediate values were found (see Results section). Secondly, we examined the link between the number of stocked fish per hectare and the membership of stocked populations to their source(s) cluster (source q-membership) as well as the link between the number of stocking events and the source q-membership using Spearman's rank test correlations. For these analyses, source q-membership was used, as many sources could have been used for each stocked lake.We investigated the effects of stocking intensity on population admixture . For this analysis, we could not find pairs of source and stocked populations with similar number of stocking events over the 40 years period. We used Spearman's rank test correlation to assess significance of the correlations.Lastly, we assessed the effect of the time spent (in years) since the last stocking event on the populations' fstat revealed significant FIS values. However, micro-checker showed that only seven of these 72 significant FIS were associated with null alleles. At the population level, six of the 72 FIS tests were significant. Of these, one was associated with the potential presence of null alleles (#71) and two corresponded to stocked populations (#10 and 11). For the historical samples (collected between 1974 and 1983), six of 70 permutation tests yielded significant FIS values of which five were associated with null alleles for five different loci. At the population level, one of five FIS was significant and associated with the potential presence of null alleles (#59).Population genetic diversity indices for each population are shown in Table AR was 11.96 over all loci and populations, while mean AR per population was 7.29 and ranged from 3.00 to 11.54. AR was significantly higher in stocked (mean AR = 8.86 ranging from 5.77 to 11.15) compared unstocked populations (mean AR = 6.16 ranging from 3.00 to 11.54) , but not among stocked populations . Average HE was 0.695 over all populations ranging from 0.415 to 0.856. As observed for AR, HE was significantly higher among stocked populations (mean HE = 0.774 ranging from 0.651 to 0.856) than among unstocked ones (mean HE = 0.639 ranging from 0.4147 to 0.836) . NE varied from 2 to 2509 among unstocked populations . We detected a significant positive correlation between NE and lake ln(LakeArea) , and between NE and AR .All 19 loci were moderately to highly polymorphic with the number of alleles per locus ranging from 8 to 56 with an average of 32. Over all loci and populations, a total of 613 alleles were identified. Global FST among the 42 unstocked populations was more than twice of that observed among the 30 stocked populations {0.227, (CI [0.197–0.260]) vs. 0.102 (CI [0.082–0.123]), P < 0.0001}. Pairwise FST values ranged from 0.025 to 0.531 among unstocked populations and from −0.016 to 0.298 among stocked populations  than stocked FSC = 0.041 (CI [0.033–0.050])  as compared to FCT = 0.064  = 991, P < 0.0001; Fig χ2(2) = 258, P < 0.0001; Estrie: χ2(2) = 163, P < 0.0001; Lanaudière: χ2(2) = 159, P < 0.0001; Laurentides: χ2(2) = 245, P < 0.0001 and Outaouais: χ2(2) = 213, P < 0.0001; Fig χ2(8) = 8.66, P = 0.372), we did observe differences among regions for the stocked populations (χ2(8) = 311, P < 0.0001). In particular, while almost all individuals were assigned to a nonlocal cluster in stocked populations from Estrie, Lanaudière and Bas-Saint-Laurent regions, a noticeable proportion of local fish were detected in stocked populations from Outaouais and Laurentides regions.Admixtures analyses also revealed that stocking had a profound impact on the genetic integrity of lake trout populations. Considering the whole dataset, the proportion of fish assigned to the local cluster, a nonlocal cluster or a putatively admixed category differed between unstocked and stocked lakes  . With <20 fish stocked per hectare, the contributions of source populations were small (source q-membership = 0.05 in average). According to the locally weighted scatterplot smoothing (LOESS), the source q-membership reached 0.5 with an average of 45 fish per hectare being stocked. However, the contribution of source populations was very variable depending on the pairs of stocked and source populations.Logistic regressions showed that populations' membership to local cluster sharply decreased with the increase of stocking intensity Fig. C,D. Withsource q-membership, for each pair of source and stocked population  18 years following the last stocking event.Finally, there was a negative correlation between time elapsed since last stocking event and stocked populations' Our main objective was to investigate the impacts of stocking on the distribution of genetic diversity within and among wild lake trout populations over a very large geographic range. Our results demonstrate that stocking resulted in an increase in neutral genetic diversity in stocked populations compared with unstocked ones. Given that stocking practices has traditionally been executed at the administrative regional scale, we observed a decrease in differentiation among populations within regions and an increase in regional genetic differences due to stocking. While unstocked populations were largely composed of local and nonadmixed individuals, stocked populations exhibited variable admixture rates with stocking sources. Furthermore, this study provides a rare clear link between stocking intensity and admixture rates  in unstocked lakes was strongly correlated with lake size (R2 = 0.41). As lake trout carrying capacity is proportional to the lake area  was more than two times lower than the global diversity (AR = 11.75), which is typical of a nonmigratory species where populations are isolated from one another  where stocked populations with a domestic strain also showed a higher genetic diversity than unstocked ones , further indicating a homogenization of the genetic diversity among stocked populations rather than an increase of the global genetic diversity. These results overall confirm that stocking fish from wild but nonlocal origins can significantly modify the extent of genetic diversity of wild stocked populations by increasing local allelic richness through the addition of nonlocal alleles.The increase of genetic diversity in stocked compared with unstocked lakes as well as the breakdown of the correlation between genetic diversity and lake area for stocked populations reflects the introduction of new alleles from nonlocal populations through stocking. Similar results were reported for brook char (FST = 0.23) and consistent with other studies on lake trout  compared with unstocked populations indicates a strong genetic homogenization effect induced by stocking at the regional scale. This tendency of genetic homogenization among stocked populations has also been observed in previous studies in several salmonids  were assigned to the local clusters. These results reinforce the evidence that pronounced genetic drift and the very limited potential for migration among lakes have shaped the distribution of the contemporary genetic diversity in those lake trout populations. These results are concordant with those reported by McCracken et al.  and most of the individuals were assigned to nonlocal clusters or to the admixed category, while a smaller proportion of trout were assigned to the local cluster. These results demonstrate that stocking with nonlocal fish have caused a genetic displacement of the local gene pool. The occurrence of admixed individuals further indicates that stocked lake trout reproduced with local fish, potentially threatening the local genetic background through introgressive hybridization, as reported in other studies  resulted in significant admixture and potential displacement of local gene pool. When stocking intensity increased up to 86 fish per hectare or up to 18 stocking events, all populations were subjected to a total displacement of the local gene pool and therefore to a complete and most probably irreversible loss of the local genetic diversity. These results are in accordance with the few studies which documented stocking intensity to be correlated with the reduction of the genetic integrity in salmonids populations (Eldridge and Naish Few studies provided clear outcomes about the potential resilience of the original genetic diversity of wild populations after the cessation of stocking (but see Perrier et al. This study demonstrates that stocking profoundly altered the genetic integrity of wild lake trout populations, but that this alteration could be short-lived in some cases with relatively low stocking intensity. Our results on neutral genetic diversity showed genetic introgression to be strongly linked to stocking intensity, however, rates of introgression between different loci under selection could be highly variable as found for other stocked salmonids (Hansen et al.


Sylvilagus transitionalis), an early successional habitat specialist of conservation concern. We evaluated local population structure and measures of genetic diversity of a geographically isolated population of cottontails in the northeastern United States. We also conducted a multiscale landscape genetic analysis, in which we assessed genetic discontinuities relative to the landscape and developed several resistance models to test hypotheses about landscape features that promote or inhibit cottontail dispersal within and across the local populations. Bayesian clustering identified four genetically distinct populations, with very little migration among them, and additional substructure within one of those populations. These populations had private alleles, low genetic diversity, critically low effective population sizes (3.2–36.7), and evidence of recent genetic bottlenecks. Major highways and a river were found to limit cottontail dispersal and to separate populations. The habitat along roadsides, railroad beds, and utility corridors, on the other hand, was found to facilitate cottontail movement among patches. The relative importance of dispersal barriers and facilitators on gene flow varied among populations in relation to landscape composition, demonstrating the complexity and context dependency of factors influencing gene flow and highlighting the importance of replication and scale in landscape genetic studies. Our findings provide information for the design of restoration landscapes for the New England cottontail and also highlight the dual influence of roads, as both barriers and facilitators of dispersal for an early successional habitat specialist in a fragmented landscape.Landscape features of anthropogenic or natural origin can influence organisms' dispersal patterns and the connectivity of populations. Understanding these relationships is of broad interest in ecology and evolutionary biology and provides key insights for habitat conservation planning at the landscape scale. This knowledge is germane to restoration efforts for the New England cottontail ( Understanding how landscape features influence the connectivity and genetic variation of natural populations is of central importance in ecology, evolution, and conservation biology. Connectivity remains one of the most difficult parameters to measure, yet it is a critical issue to address in landscape conservation  of early successional habitats has been modified by a loss of natural disturbance regimes, land use change, and anthropogenic landscape modifications. These habitats are on the decline in the northeastern United States, along with many species that rely on them Brooks . ConsequSylvilagus transitionalis; Fig. One of the many shrubland obligate species of high conservation priority in the northeastern United States is the New England cottontail  would facilitate gene flow. Our results provide key information for the design of restoration landscapes that enhance connectivity for the New England cottontail and thereby likely also benefit other species that rely on early successional habitats. Our findings also illustrate the complexity of natural and anthropogenic factors influencing gene flow of a habitat specialist in a fragmented landscape.The objectives of our study were threefold: (1) to assess local population genetic structure and diversity of New England cottontails in southern Maine and coastal New Hampshire; (2) to identify landscape features that are influential in structuring populations through promoting or inhibiting connectivity within and among these populations; and (3) to test hypotheses about the influence of landscape features (identified in #2) on gene flow. Specifically, we evaluated the effects of geographic distance, roads, waterbodies, and linear features comprised of early successional habitat, such as utility lines and roadsides, on gene flow. We expected to find fine-scale population structure resulting from the separation of populations by fragmentation and/or dispersal barriers. We hypothesized that landscape features have a stronger influence on genetic variation within and among populations than geographic distance alone. We also predicted that roads and waterbodies would function as dispersal barriers, while linear shrubby habitat features  in areas of recent occurrence and coarser grains (4–8 km) as the likelihood of encountering a New England cottontail decreased. Surveys were centered around grid points where we searched up to three suitable (densely shrubby) habitat patches within an approximate 1 km radius around each grid point if possible, although not all grid points had nearby suitable habitat (Fenderson Sylvilagus floridanus) and the snowshoe hare (Lepus americanus) in portions of their range, the species of origin of the pellets was determined using a combination of two diagnostic RFLP tests of the mitochondrial DNA, using the restriction enzymes BfaI , with minor modifications of the manufacturer's instructions as described in Kovach et al. . As New ropout . Samples from unique individuals were then genotyped at three additional loci determined to be polymorphic in this study , and alleles were binned in reference to a positive control with the program Allelogram 2.2 , to ensure consistency of allele calls across multiple electrophoretic runs.New England cottontail samples were amplified with fluorescent dye-labeled primers and multiplex protocols at 11 microsatellite loci Table , to screicrochecker  from 1–7 using a burn-in of 100,000 and run length of 500,000, with the no admixture and independent allele frequencies model  (Structure) or the average deviance information criterion (DIC) of each K plotted against K (Tess), and from evaluation of the bar plots. Individual population memberships were averaged using Clumpp 1.1.2  of each genetic cluster was calculated with two single sample methods: a linkage disequilibrium method performed in ldne . The variables of interest were the six classes of road, defined by traffic volume, and hypothesized to have increasing barrier effect with increasing traffic volume. (2) The surficial water model similarly evaluated the dispersal-limiting effects of waterbodies . Variables included the six Strahler stream order classes, hypothesized to have increasing barrier effect with increasing stream width; all other waterbodies without stream order information were grouped with the lowest stream order category. (3) The facilitators model assessed the effects of linear strips of shrubby habitat as facilitators of dispersal, by assigning these features reduced costs relative to the background matrix. Facilitator variable costs were based on expert opinion , which considered railroads, class 3–6 road edges, class 1–2 road edges, and powerlines, in increasing order of hypothesized facilitating effect. In addition, we tested a null model of straight Euclidean distance. GIS data sources and additional details of methodology can be found in Appendix We developed models for three feature classes: 1) A roads model tested the hypothesized barrier effects of roads by assigning them  A roads For each of the three feature classes , we developed four types of cost models – binary, linear, exponential, and logarithmic – to evaluate the relative dispersal cost of the variables in each feature class. In the binary model, all feature variable costs were equal, but higher  or lower (for the facilitator model) than the background cost. In the linear, exponential, and logarithmic models, the feature variable costs were ranked according to their hypothesized influence on dispersal (described above). Costs varied relative to one another in a linear, exponential, and logarithmic relationship, respectively, with increasingly higher costs given in the two types of barrier models and reduced costs in facilitator models on the variables hypothesized to have greater influence on dispersal . We compared the Mantel r values for the four cost models for each of the three feature classes to evaluate which cost model exhibited the best linear relationship with genetic distance within each population.To evaluate the relationship between gene flow and the three landscape feature classes, we first used Mantel tests Mantel  to corre Rousset  genetic r for each feature class, using 10,000 permutations and the Spearman correlation with the ecodist package in R. The relative influence of each feature class on genetic variation was further elucidated using the hierarchical partitioning method of Chevan and Sutherland  a large cluster of individuals from Cape Elizabeth . Further, the individuals with shared ancestry between the Jetport and Kittery West were sampled northeast of the river in Maine. Given the large geographic distance (48 km) between the Jetport and the closest patch of individuals in Kittery West today, we considered these findings to reflect a historical connection between these populations and determined it more biologically meaningful to view them as separate clusters with respect to current occupancy patterns. That is, despite evidence for their recent connectivity, cottontails in these populations are functionally separate populations today with genetic drift acting independently within each population. Lack of current migrants detected between these two populations (see assignment test results below) further supported this separation.The Bayesian clustering methods detected hierarchical population genetic structure Figs  and 5. Fure Fig. . For Testructure and Tess on just the Kittery West individuals, using the same parameters as before, up to K = 4. We found support for additional substructure within Kittery West, comprising two populations: the individuals sampled in Maine, northeast of the river (KW-ME), and those individuals sampled from Seacoast New Hampshire, west of the river  and for K = 5 (keeping separate the two subdivisions in Kittery West) where we deemed it relevant.To test for finer-scale structure, we conducted an additional analysis with both Sicrochecker analyses found three loci with null allele frequencies >10% in at least one population: Sol03 in Cape Elizabeth (11.2%), Sfl11 in Kittery East (14%), and Sfl8 in Cape Elizabeth and Kittery West . No null alleles were detected in KW-ME or KW-NH. Sol03 and Sfl8 were out of Hardy–Weinberg equilibrium in the Cape Elizabeth population; all remaining loci and populations exhibited HWE, lending support to the genetic cluster designations. As null alleles have minor impacts on genetic distance measures , and the largest differences occurred in comparisons of KW-NH and the other populations , and only six individuals were cross-assigned to other populations with relatively high probability (>75%). Only two individuals were identified as migrants by both Geneclass and Structure. One was an individual sampled in Kittery East that assigned to KW-NH, and the other was sampled in KW-ME and assigned to KW-NH. Five other individuals were assumed to have admixed ancestry based on meeting at least two of the following criteria: (1) >50% Geneclass assignment probability to a cluster other than that of geographic origin; (2) identified as a putative first-generation migrant with Geneclass migrant detection; (3) <50% Structure resident probability; and/or (4) >10% Structure immigrant probability. Three additional individuals from Cape Elizabeth were cross-assigned to the Jetport with >85% probability in Geneclass; however, they had >85% resident probability in Structure. Due to the proximity of the two populations, we also considered them as potentially admixed.The two Kittery West subpopulations were separated for assignment tests and migrant detection. The Gottleneck method under the I.A.M. and T.P.M. mutation models, with the Wilcoxon one-tailed probability test. Kittery East and KW-ME also had significant heterozygosity excess under the I.A.M. model, and KW-ME had a shifted allelic mode distribution as well. The M-ratio method also detected a significant genetic bottleneck in KW-ME.Effective population sizes for each cluster ranged from only 3.2 in the Jetport to 36.7 in Cape Elizabeth ; however, all confidence intervals overlapped  were significant across all populations and within each population, except KW-NH, although they explained a small amount of the total genetic variation (0.3–10%). For the study area as a whole, only the road variable had a significant positive association with genetic distance, and Euclidean distance had a significant, but negative, association Table . For theHabitat loss and fragmentation can alter the genetic structure and diversity of natural populations through a disruption of gene flow and metapopulation processes  among all pairs of populations. The presence of private alleles in each population further suggests that rapid genetic drift is occurring in the absence of dispersal. The distances separating populations greatly exceed the estimated mean dispersal distances of New England cottontails  and heterozygosity (Ho = 0.223–0.287), was reduced in Maine and New Hampshire relative to geographic areas in the core of the species' range (Ar = 3.4–4.0 and Ho = 0.371–0.492 for eastern Connecticut/Rhode Island and western Connecticut/New York), while common ancestry estimates  were increased (0.19 in Maine/New Hampshire compared to 0.09–0.12). Genetic diversity was similarly low across the four populations identified in this study, with slightly reduced allelic richness and heterozygosity in the Jetport relative to the other populations. The reduced genetic diversity in the Jetport is consistent with the origin of these 19 individuals from a single habitat patch in an isolated area. Genetic diversity has been found to have important effects in determining population dynamics , while the M-ratio test is best for detecting more historic or longer-duration bottlenecks , only facilitating habitat was important in explaining gene flow. In Kittery East, which is the most fragmented population, comprised of two disjunct clusters of individuals separated by 20 km and where remnant patches are small  varied by population. Teasing apart these influences is a potentially important avenue for future research. Additionally, although our analyses focused on shrubland habitats, future studies should investigate the potential facilitating effects of other types of early successional habitats, such as tall grasslands and hayfields, and fully evaluate the role of other habitats and land-cover features in influencing cottontail dispersal.We were able to evaluate the roads-as-dispersal-facilitators hypothesis, in part, through our landscape resistance modeling, in which the facilitator model accounted for the facilitating effects of roadsides and other linear thicket conduits. The facilitator models were significant in most of the within-population analyses and explained a larger portion of the genetic variation than the barrier effects of roads, surficial water, or geographic distance within populations, except for Kittery East, which showed a pronounced pattern of isolation by distance. The potential facilitating effects of linear shrub-lined conduits were further illustrated by the Bayesian clustering results of genetic similarity of the Jetport and Kittery West populations, separated by a distance of 48 km. This genetic similarity likely reflects recent historical connectivity. A major powerline runs parallel to and on the west side of the interstate between these two populations, and cottontails occupied habitat patches within this intervening area as recently as 2000–2003  in this region, which extended their range into southern New Hampshire in the late 1960s , suggesting that cottontails do disperse, at least occasionally, across the river. Although rivers pose barriers to the dispersal of many small- and medium-sized mammals  in sustaining gene flow and the role of major highways and waterways in impeding dispersal. We also found evidence that anthropogenic connections, such as underpasses and possibly culverts, may be effective in facilitating dispersal across interstate highways.Management to create additional suitable habitat is critical for restoration of cottontail populations in this region. This habitat creation has been the dominant focus of a recent conservation initiative. The current goals of the conservation strategy for the New England Cottontail (Fuller and Tur


Aphidius ervi. We report evidences of a high gene flow among parasitoid populations on different aphid hosts and geographic locations. The high gene flow among parasitoid populations was found to be largely male mediated, suggested by significant differences in the distribution of full-sib and paternal half-sib dyads of parasitoid populations.Host recognition and use in female parasitoids strongly relies on host fidelity, a plastic behavior which can significantly restrict the host preferences of parasitoids, thus reducing the gene flow between parasitoid populations attacking different insect hosts. However, the effect of migrant males on the genetic differentiation of populations has been frequently ignored in parasitoids, despite its known impact on gene flow between populations. Hence, we studied the extent of gene flow mediated by female and male parasitoids by assessing sibship relationships among parasitoids within and between populations, and its impact on geographic and host-associated differentiation in the aphid parasitoid  In Hymenopteran parasitoids, host choice strongly relies on host fidelity, a plastic behavior which can significantly restrict the host preferences of parasitoids, resulting in a lower dispersion and gene flow between populations associated to certain hosts  three different aphid species (interspecific level), including the cereal aphids Sitobion avenae Fabricius and Rhopalosiphum padi Linnaeus, and the pea aphid A. pisum; and (2) three different host races of A. pisum (intraspecific level). Only weak signals of genetic differentiation were found, both at the interspecific and intraspecific levels. Therefore, to estimate and compare the extent of female and male-mediated gene flow between parasitoid populations, a sibship reconstruction was performed.Consequently, our goal was to estimate the extension which male and female gene flow influences genetic differentiation between different populations in the parasitoid A. ervi in Chile were introduced from France during the mid-1970s, as part of a cereal aphid biocontrol program mainly to control the grain aphid S. avenae, and is presently one of the best examples of biocontrol of S. avenae and A. pisum  and host fidelity in parasitoid females on both S. avenae and A. pisum complex   , only diploid females were used for genotyping to ease population genetic analyses and sibship reconstructions  , isolating single sequence repeats (SSR) from an enriched library. The procedure was carried out through the Ecomicro Consortium , 2 mmol/L MgCl2, 0.2 mmol/L of each dNTP, 0.25 mmol/L of reverse primer, 0.25 mmol/L of M13 primer, 0.25 mmol/L of forward primer, and 0.5 U of Taq polymerase . The term “parasitoid population” is used here operationally to describe a group of parasitoid individuals based on their ecological (different hosts), spatial (different regions), and temporal (different seasons) distributions in the field. Allelic richness was computed and standardized by the multiple random reduction method (Leberg n = 12), with the package standArich v.1.0 in R  of 1000 individuals and 10 of drift generations (t) to achieve expected FST values <0.005. The FST (fixation index) was estimated to determine the degree of genetic differentiation at the population level; an unbiased estimator of FST, the Hedrick's standardized GST (FST and k) containing the different multilocus genotypes of A. ervi identified, as well as to compute the coefficient of ancestry for each multilocus genotype to the inferred different clusters, we performed a Bayesian assignment analysis using STRUCTURE v. 2.3.4  with the highest posterior probability after 10 replicates for each k (between 1 and 10) was determined. The model was tested by performing 100,000 runs with 10,000 burn-in periods before each run. Finally, we assessed the most probable number of clusters using the log of the posterior probability and the average rate of change (delta k) for each value of k, using the method proposed by Evanno et al.  without prior knowledge of the parental genotypes was carried out using the full-likelihood method implemented in COLONY for haplodiploid species  and R. padi (PT); Fig.A. pisum and S. avenae -R. padi (PI); Fig.S. avenae and R. padi were treated as a single population for the study of the distribution of sibships, because parasitoids were sampled on both aphid species in a same field and time. To limit the chance of taking individuals from more than two different generations (the method assumes a single generation), only individuals sampled in the same month were included. In addition, only genotypes from populations sampled during the 2011/2012 season were used in the analyses, as genotypes from different populations were not sampled within the same month in the season 2010/2011. In the analyses, we assumed a model of monogamous females  and polygamous males  without inbreeding, since our results did not show any evidence of inbreeding (see Results). Thus, full-sib and paternal half-sib relationships were estimated. This type of reproductive strategy has been reported for A. ervi (He and Wang n = 10) with a long length of run  showed significant deviations from HWE due to homozygote excess. All the other parasitoid populations were found to be in HWE  and with a low risk of false significances (α < 0.05), according to the POWSIM analyses   and from A. pisum-alfalfa race in the Los Ríos Region   in a similar proportion (membership coefficient), thus supporting the lack of genetic structure described above using AMOVA  was for k = 3  . Similar < 0.05) . The BayMOVA Fig.. The hig = 3 Fig. and B; hA. ervi females from different populations sampled on A. pisum alfalfa and pea races, S. avenae and R. padi. The sibship analyses identified a total of 20 full-sib dyads, 96 half-sib dyads, and 9754 nonsibship dyads among the 141 multilocus genotypes of A. ervi analyzed from Los Ríos Region (southern). In the Maule Region , seven full-sib dyads, 49 half-sib dyads, and 4600 nonsibship dyads were observed among the 97 multilocus genotypes analyzed. The results show that the full-sib frequency was higher within (17 full-sib dyads) than between parasitoid populations (three full-sib dyads) in Los Ríos Region, as well as in the Maule Region, where the full-sib frequency was higher within (six full-sib dyads) than between populations (only one full-sib dyad)  and Maule   was lower than the paternal half-sib frequency observed between the populations associated with different aphid species   of  APP-SA) . This wa APP-SA) .r = 0.4; df = 14; P value = 0.08), including comparisons between the two regions  and the geographic distance between parasitoid populations  in a smaller scale study (between 160–240 km) in North America, using a different set of microsatellites. In addition, other several studies on aphid parasitoids have shown a lack of host-associated genetic differentiation , which could be influenced by insufficient time for host-associated selective agents resulting in adaptive divergence in these parasitoid populations  A male-biased sex ratio  could limit the gene flow from parasitoids immigrating from smaller hosts  due to competitive advantages of larger males. This suggests that the natal host of males should influence their ability to mate with females coming from neighboring populations on different aphid hosts (Henry A. pisum (APP and APA) (the larger host) compared with the higher frequency of paternal half-sib dyads observed between A. pisum and S. avenae  (APP-SA or APA-SA), even when the geographic distances between samples from different aphid species (APP-SA or APA-SA) are greater than between samples from distinct host races (APP-APA) .Regarding the higher paternal half-sibs between than within parasitoid populations, several interacting factors could contribute to a greater dispersion of  Godfray ; (3) A r Godfray ; (4) The Godfray  or host  Godfray . Therefo Godfray . Indeed, Godfray  reportedes Henry . In Aphi Godfray . Hence, ts Henry . This coPatterns of sex-biased dispersal have been frequently observed among certain birds, mammals, and hymenopteran social insects  Hedrick . HoweverA. ervi. Interestingly, the pattern of dispersal and gene flow between parasitoid populations seems to be asymmetrical for males and females, suggesting that females should have a rather restricted dispersal between populations, while males would be the main drivers of gene flow between parasitoid populations. Male-driven gene flow could represent a significant factor impeding the formation of host-associated genetic differentiation and local host adaptation in Aphidius parasitoids. Finally, more studies focused on sex-biased dispersal in parasitoid species using controlled experiments to examine the potential of parasitoid males as a source of dispersal and gene flow between different hosts are needed to confirm the dispersal pattern observed in this study and its effect on host-associated genetic differentiation and host adaptation in parasitoid species.The present study reports evidence of a high gene flow among parasitoid populations on different aphid hosts and geographic regions, resulting in a lack of genetic differentiation in the natural populations of


Wuchereria bancrofti. It is earmarked for elimination by the year 2020 through the Global Program for the Elimination of LF (GPELF). In Ghana, mass treatment has been on-going since the year 2000. Earlier studies have revealed differing epidemiology of LF in the North and South of Ghana. This study was therefore aimed at understanding the possible impacts of W. bancrofti diversity on the epidemiology and control of LF in Ghana.Lymphatic filariasis is a debilitating disease caused by the filarial worm W. bancrofti samples was sequenced and analyzed. The test sequences were grouped into infrapopulations, and pairwise differences (π) and mutation rates (θ) were computed. The amount of variance within and among populations was also computed using the AMOVA. The evolutionary history was inferred using the Maximum Parsimony method.The Mitochondrial, Cytochrome C Oxidase I gene of Seven samples from the South and 15 samples from the North were sequenced, and submitted to GenBank with accession numbers GQ479497- GQ479518. The results revealed higher mutation frequencies in the southern population, compared to the northern population. Haplotype analyses revealed a total of 11 haplotypes (Hap) in all the 22 DNA sequences, with high genetic variation and polymorphisms within the southern samples.W. bancrofti populations in Ghana, differences that might explain the observed epidemiology of LF. Further studies are however required for an in-depth understanding of LF epidemiology and control.This study showed that there is considerable genetic variability within  Onchocerca volvulus [Wuchereria bancrofti. It is earmarked for elimination by the year 2020, and since the year 2000 there have been yearly mass treatment of endemic communities with Ivermectin and Albendazole. Mass Drug Administration (MDA) coverage for LF increased from three million people treated in 12 countries in 2000, to nearly 950 million in 53 countries in 2011 [W. bancrofti affect the epidemiology of LF is required in different settings.The geographic strains of parasites are important in disease pathogenicity as observed with the forest and savanna strains of olvulus . Thus, aIn Ghana, studies on LF have shown differences in disease prevalence and multiplicity of symptoms in two geographically distinct regions : the NorW. bancrofti populations. Two different genetic variants of the parasite, have been reported, with high genetic divergence and gene flow in different geoclimatic regions in India [W. bancrofti that may affect the success of MDA programs. This study reports on initial findings of genetically different W. bancrofti strains in Ghana.Few studies have pointed to genetic and morphological variations in in India , 6. In vin India , which aW. bancrofti populations in Ghana, sequence variations in the mitochondrial (mt) gene Cytochrome C Oxidase Subunit I (COI) were analyzed. The COI and MtDNA have been useful in differentiating closely related species, and as a marker for taxonomic and population genetic studies [W. bancroftiwere dissected out from infective Anopheles mosquitoes collected during two entomological studies conducted independently in the Bongo[To study the  studies –10. W. bthe Bongo and the W. bancrofti was done as described by Ramzy and colleagues [W. bancroftifrom GenBank (Accession numbers CD455366.1 and AM 749236.1) and Filaria martis (GenBank Accession number AJ544880.1) were included in phylogenetic construction with the latter serving as the outgroup.Parasite genomic DNA was extracted using the DNeasy Tissue Kit following the manufacturer's protocol . Molecular identification of lleagues . For seqlleagues . All PCRlleagues  and Megalleagues . The COIThe test sequences were grouped into infrapopulations according to their collection sites. i.e. northern or southern. Aligned sequences were further analyzed in DnaSP v5  for pairThe evolutionary history was inferred using the Maximum Parsimony method . The perSeven samples from Gomoa District (in the South) and 15 samples from Bongo District (in the North) were sequenced. The sequences have been submitted to GenBank with accession numbers GQ479497- GQ479518 in 2009. The similarity index between the Northern and Southern consensus sequences was calculated to be 38.3%. The mean evolutionary diversity between the two groups was 0.314 (SE = 0.028) while the mean evolutionary diversity for the entire population was 0.363 (SE = 0.038). The mean composition distance between the Northern samples was 0.090 while that between the Southern samples was 2.817. The mean composition distance between the two populations was 0.704. In addition, we computed the mutation frequency between the populations . The resF. martis as an outgroup (F. martis as an outgroup in Tajima′ relative rate test [2 test statistic was 7.44 (P = 0.00637) at 0.05 confidence interval, rejecting the null hypothesis of equal rates between lineages.The evolutionary history was inferred using the Maximum Parsimony method . The resoutgroup  reveals ate test . The X2 Haplotype analyses revealed a total of 11 haplotypes (Hap) in all the 22 DNA sequences; 6 from the northern infrapopulation and 6 from the southern. A single haplotype (Hap_3) was shared between the two populations . ApproxiAmong the 69 loci used in the analyses, 58 polymorphic sites were observed between populations. The southern infrapopulation was more polymorphic than the northern infrapopulation (62 vrs 54 polymorphic sites). The measure of polymorphism is further emphasized by comparatively higher mean pairwise differences (π) in the southern population (30.81 +/- 15.37) than the northern (10.60 +/- 5.12). For example, for Hap_3 which is common to both populations, there seem to be a high number of pairwise differences (>20) when compared with the other haplotypes present in the southern intrapopulation (Hap_1- Hap_6) than in the northern intrapopulation (Hap_7-Hap_11) .We tested the significance of these mutations in the two populations under the neutral theory. Under Tajima's test for selective neutrality, the southern population has a positive value  while the northern population has a negative value .The AMOVA analysis showed that 87.2% of the variation observed is within population (intrapopulation) than between the populations (interpopulation). Therefore, the northern and southern populations are less genetically differentiated .W. bancrofti in Ghana, thus adding to the very few studies that aimed at understanding the genetic heterogeneity of W. bancrofti [The data from this initial study indicates that the Southern samples are more distant. This data does provide relevant information about the possible route of entry of the parasite into Ghana and its subsequent spread. Consequently, because only anecdotal evidence of the parasites existence and prevalence in Ghana exists prior to 1990, this information is of great importance. This study, despite the small number of samples analyzed, does reveal some level of genetic variability in ncrofti , 6, 22.The genetic differences observed in this study may be attributed to environmental selection pressures. This may explain the epidemiological and field observations of LF in Ghana. High prevalence of LF in Northern Ghana  could beW. bancrofti is transmitted by Anopheles species, including most endemic areas in Africa [O. volvulus [The current LF control strategy is based on the assumption that MDA can be used alone in areas where n Africa . This stn Africa . Howevern Africa . We posin Africa . Also, tolvulus . FurtherW. bancrofti can make a vector a more or less efficient one. In a susceptibility study [Culex quinquefasciatus strains from Liberia had a low susceptibility to W. bancrofti from Liberia, while the same strain had a high susceptibility to W. bancrofti from Sri Lanka. Consequently, the study concluded that the Liberian and Sri Lankan strains of W. bancrofti differed in their ability to infect specific mosquito strains and therefore confirms our suggestion that the geographic strain of W. bancrofti can improve vector competence. The same reasons may explain the different epidemiologies of LF in East and West Africa, as to why Culex quinquefasciatus is not a vector of LF in West Africa, but is a very efficient very in urban areas in East Africa [The findings of this study may also suggest that the geographic strains of ty study , Culex qt Africa , 30. HowW. bancrofti populations. This will enable the determination of profound conclusions on W. bancrofti diversity. The availability of the complete mitochondrial genome sequence of W. bancrofti [W. bancrofti diversity as well as vector-parasite co-adaptations. Until more information, regarding the impact of W. bancrofti diversity on disease and treatment outcomes, becomes available, it is recommended that MDA be supplemented with vector control in order to ensure effective control of the parasite, in working towards the LF elimination goals of 2020.In order to further explore the results produced in this study, we recommended that further studies with a much larger sample size and more detailed, population analyses be conducted on the diversity of ncrofti  will enhW. bancrofti populations in Ghana, differences that might explain the observed epidemiology of LF. Further studies are however required for an in-depth understanding of LF epidemiology and control.This study showed that there is considerable genetic variability within


Heterodera schachtii on a wild host plant species, the sea beet (Beta vulgaris spp. maritima), the wild ancestor of cultivated beets. Our analysis of the variation of eight microsatellite loci across four study sites showed that (i) wild H. schachtii populations displayed fine‐scaled genetic structure with no evidence of substantial levels of gene flow beyond the scale of the host plant, and comparisons with simulations indicated that (ii) genetic drift substantially affected the residual signals of isolation‐by‐distance processes, leading to departures from migration–drift equilibrium. In contrast to what can be suspected for (crop) field populations, this showed that wild cyst nematodes have very low dispersal capabilities and are strongly disconnected from each other. Our results provide some key elements for designing pest control strategies, such as decreasing passive dispersal events to limit the spread of virulence among field nematode populations.Studying wild pathogen populations in natural ecosystems offers the opportunity to better understand the evolutionary dynamics of biotic diseases in crops and to enhance pest control strategies. We used simulations and genetic markers to investigate the spatial and temporal population genetic structure of wild populations of the beet cyst nematode  Distances separating the four beaches  ranged from 300 m to 150 km  and manual examination of filtrates. Cysts were stored at 4°C in moistened sand until molecular characterization.Soil samples were collected around roots of 2.2Heterodera species, we used restriction profiles of the ITS sequence for species identification. DNA extraction, PCR amplification of ITS sequence and digestion of PCR products were performed as described in Amiri, Subbotin, and Moens . Allele sizes were identified using the automatic calling and binning procedure of GeneMapper v4.1 (Applied Biosystems) and completed by a manual examination of irregular results. Samples with dubious genotypes were reamplified.As a soil sample can contain cysts from different nd Moens . Polymory et al. . Microsa2.32.3.1H. schachtii were a priori defined at the scale of a single host plant because active dispersal of H. schachtii is considered to be spatially restricted and because it is very difficult to perform fine‐scaled spatial sampling over the root system of the host plant. However, we assessed the scale of population boundaries using three different analyses. We first used a spatial principal component analysis (sPCA) to investigate the spatial distribution of genetic diversity within each surveyed beach using the R package adegenet . The two‐first principal component scores were simultaneously represented into a channel of color to draw a comprehensive synthetic representation of sPCA scores, as described in Menozzi, Piazza, and Cavalli‐Sforza  in all the subsequent analyses. Analyses were performed on the whole 2012 dataset (n = 40 populations), and 34 of these populations were resampled in 2013. Jan et al. (n = 34) and one dataset that was restricted to populations that produced enough generations between 2012 and 2013 to detect substantial temporal genetic variation (Table n = 20) and will include results from the unrestricted dataset (n = 34) when they provide useful additional information.Results allowed us to define populations of n et al.  identifi2.3.2FIS values for all populations on each beach. Statistical significance of FIS values was assessed using 10,000 permutations of alleles among individuals, adjusted for multiple tests with Bonferroni corrections, as implemented in the software FSTAT version 2.9.3  and allelic richness (Ar) using FSTAT. Allelic richness was estimated using the rarefaction method as described in El Mousadik and Petit (Hardy–Weinberg (HW) equilibrium is required in population assignment‐based methods (see below). Therefore, single and multilocus departures from HW equilibrium were tested by estimating  Goudet, . Similarnd Petit .2.3.3FST and performed regression analyses as described in Rousset . In 2013, three loci in Montfarville and Granville Sud, four loci in Saint Léonard, and seven loci in Granville Nord showed significant departures from HWE. To assess the influence of loci departing from HWE on results, assignment tests were performed with and without these loci for populations sampled in 2012. Results did not show any difference in the distribution of detected migrants over distance among populations (data not shown). As a result, we considered results from assignment tests considering all loci in 2012 and 2013 in subsequent analyses. All analyses computed on empirical datasets were performed separately for the different beaches.2.3.5H. schachtii populations, and (ii) because we did not have any representation of the root systems which may bring populations closer or farther apart than what could be expected from the spatial distribution of plants. In this case, a square was the simplest experimental design to investigate dispersal occurring among the closest populations, that is among adjacent populations whatever the geographical distance among them. Assuming random mating within each simulated population, we used a two‐dimensional stepping‐stone migration model because it reflects the spatial positions of host sea beet plants, and it entails that migration events only occur among adjacent host plants, in accordance with the restricted dispersal capabilities in H. schachtii. We explored four different scenarios by varying effective sizes and migration rates. Effective sizes Ne were set at 100 and 400 individuals, and migration rates m at 0.04 and 0.1, and 0.1 and 0.025, respectively, to explore the behavior of assignment tests in situations that correspond to Nem = 4 and Nem = 10, which are the two most extreme values for the product Nem we observed in the four beaches. The mutation rate was fixed at 5 × 10−4 mutation/locus/generation , given the mutation rate observed in nematodes  to generate distributions of IBD slopes, means, and variances of pairwise FST values that were compared with what we observed in 2013. All simulations, data handling, and testing were performed with R.However, because drift effects accumulate with time and because our sampling period covered between four and ten nematode generations only . In the same way, spatial genetic structure was only detected among individuals sharing the same host plant in Granville Nord and Montfarville in 2012 and 2013, and up to 80 or 55 cm in Granville Sud (in 2012) and in Saint Léonard (in 2012 and 2013), respectively . Beyond this level, average kinship estimates did not depart from spatial randomness. These results suggested a very short‐distance spatial autocorrelation with a lack of detectable IBD within the four studied beaches for both sampling years. For 82% of the 68 tested datasets using Bayesian genetic clustering, 3.2He) ranged from 0 to 0.582. The overall average FIS was significant in 2012 (FIS = 0.041) and in 2013 (FIS = 0.153). Some loci showed significant departures from HW equilibrium, which represented 12% and 15% of the 320 and 272 single‐locus tests performed among loci over all populations in 2012 and 2013, respectively. Among these tests, 8% and 15% (4% and 0%) of FIS values were significant (positive or negative) in 2012 and 2013, respectively. These values were not associated with a particular locus or population, suggesting spurious effects of genetic drift and/or population genetic substructuring. As a result, 30% and 65% of populations exhibited significant multilocus FIS values ranging from −0.307 to 0.391 and from 0.099 to 0.362 in 2012 and 2013, respectively  and in 2013 .Only 1.5% and 1.8% of the genetic variance could be attributed to differences between host plant patches in 2012 and 2013, respectively. Population differentiation explained by host plant patch membership was low, or virtually absent, and marginally significant only for the 2012 dataset. In contrast, populations were significantly different among beaches and host plants in 2012 .We detected 11 potential migrants in 2012 and 1 in 2013 over the whole empirical dataset. We obtained similar results considering the 34 populations sampled in 2013 with 3 migrants detected over the four beaches. Simulations showed that the type I error rate  largely exceeded 5%. It was 48% and 59% for 3.5FST values did not change between the two sampling sessions . A similar pattern was observed in Montfarville with mean and variance of pairwise FST that fall outside the 95% confidence interval for Ne ≤ 100 individuals. Only Granville Sud showed a mean and variance FST value that lay outside the lower confidence interval for all effective sizes , suggesting that genetic drift was not the only evolutionary process acting on population genetic structure on this beach.Isolation by distance patterns differed among sampled beaches, but they remained quite stable between 2012 and 2013 . Overall, simulations of the evolution of allelic frequencies under pure drift are consistent with observed patterns of population genetic structure, at least for effective population sizes that are in the range of what has been estimated for these populations  migrants detected in our empirical dataset were probably false positives. It is also worth mentioning that even if they are true migrants, they may not all contribute to maintain IBD, depending on their origin . This small number of detected migrants may be related to the low genetic variability of the microsatellite markers used, which is known to limit the statistical power of assignment tests  observed in wild H. schachtii populations  would isolate avirulent from virulent populations and (ii) reduce the effective population size of field nematode populations. The influence of genetic drift would be favored within populations and may lighten the selective pressure imposed by sugar beet cultivars and thus decrease the ability of nematode populations to overcome resistance over large spatial scales. Such confinement strategies have already been strongly advocated by several authors (Burdon & Thrall, 5H. schachtii were characterized by a nonequilibrium population structure, weak levels of gene flow beyond the scale of the host plant, and a non‐negligible impact of genetic drift. This pattern appeared stable over a short period of time, suggesting no isolated disturbance. A wild population of H. schachtii appears thus to be defined under the host plant scale, which suggests that human activities strongly influence passive dispersal among field nematode populations. Thus, the management of durable crops’ genetic protection against telluric pathogens may gain from developing methods that combine passive dispersal limitation with other methods that help reduce parasite effective population sizes. Finally, this study illustrates how worthy would be data on the genetic structure of wild and field populations of other plant‐parasitic nematodes species which are currently still lacking.This study used temporal sampling to investigate the genetic structure of wild populations of the beet cyst nematode. Wild populations of http://dx.doi.org/10.5061/dryad.8g5n6.Data for this study are available from the Dryad Digital Repository:  Click here for additional data file. Click here for additional data file. Click here for additional data file.