Rheum officinale Baill., an important but endangered medicinal herb, is endemic to China. Inter-simple sequence repeat (ISSR) markers were employed to investigate the genetic diversity and differentiation of 12 populations of R. officinale. Thirteen selected primers yielded 189 bright and discernible bands, with an average of 14.54 per primer. The genetic diversity was low at the population level, but pretty high at the species level  by POPGENE analysis. Analysis of molecular variance (AMOVA) showed that the genetic variation was found mainly among populations (74.38%), in line with the limited gene flow (Nm = 0.2766) among populations. Mantel test revealed a significant correlation between genetic and geographic distances , indicating the role of geographic isolation in shaping the present population genetic structure. Both Bayesian analysis and UPGMA cluster analysis demonstrated the similar results. Our results imply that the conservation efforts should aim to preserve all the extant populations of this endangered species, and cultivation is proposed in this study. To estimate accurately of the genetic diversity of a species is an important element in establishing conservation programs –3, becauRheum officinale Baill. (Polygonaceae) is a perennial herb, the dried roots and rhizomes of which are called rhubarb (Da Huang in Chinese). Rhubarb is a widely used traditional Chinese medicine having many pharmacological actions, such as purgation, anti-inflammatory, antibacterial, antipyretic, and anticancer effects [R. palmatum L. and R. tanguticum Maxim. ex Balf. [R. tanguticum has the best pharmacological effect and the most limited distribution in Qinghai, Gansu, Sichuan and Ningxia provinces. Compared with R. tanguticum, R. officinale has a weaker pharmacological effect and wider distribution in western Hubei, western Henan, southern Shaanxi, northern Sichuan, southern Chongqing, northern Guizhou, southeastern of Gansu and northwestern of Yunnan provinces. The distribution of R. palmatum is overlapped with the other two species [R. tanguticum has become endangered and was listed in the China higher plants endangered list [R. officinale face great pressure exacerbated by the reduction in the individual of R. tanguticum. In addition to the increasing medicinal usage of R. officinale, the usage of R. officinale has recently been extended to a functional food and plant protecting agent [R. officinale is limited to altitudes ranging from 1100 m to 4600 m, whereby its altitudinal range does not exceed 600 m on any mountain, and it grows generally at the forest edge of the hills and rarely in the forests or in the valleys near the rivers. Because of the deterioration of the habitat of R. officinale, the individuals of this species are decreasing annually, thus the wild resources of it are more easily destroyed. Therefore, it can be predicted that the next original medicinal rhubarb plant which will be endangered will be R. officinale. To date, previous studies of R. officinale have mainly focused on its distribution [R. tanguticum had been studied by a few researchers [R. officinale remains unknown. In order to conserve and select excellent germplasm for the cultivation in R. officinale, the study on the genetic diversity for this species is becoming necessary and timely. effects –8. As deex Balf. . The threx Balf.  and endeex Balf. . As the  species ,12. Becared list ,14. The ng agent . The habribution , componeribution ,18 and pribution ,20. Althearchers ,14, the Of the various molecular markers, ISSR (inter-simple sequence repeat) has a few advantages because ISSR primers anneal directly to simple sequence repeat and thus, unlike SSR markers, no prior knowledge of target sequences is required for ISSR ,22. AlsoR. officinale populations sampled from all over its distribution. The major objectives of this study were to (1) predict the genetic diversity of the populations of R. officinale; (2) assess the genetic variation within and among populations; and (3) provide basic information for future conservation and management programs in the cultivation of this important medicinal species.In the present study, ISSR markers were employed to assess the genetic diversity within and among R. officinale  for this species was 95.24% (PPB) ranged from 4.00% to 44.57%, with an average of 29.14%. The average effective number of alleles per locus was 1.1740. Assuming Hardy-Weinberg equilibrium, Nei’s gene diversity (H) varied between 0.0139 and 0.1614, with an average of 0.1014, and Shannon’s information index (I) ranged from 0.0213 to 0.2400, with an average of 0.1514. The values of H and I showed a similar trend to PPB. However, the H and I values equalled 0.3341 and 0.5000 respectively at the species level, demonstrating a relatively high level of genetic diversity  and 74.38% (Φst), both of which indicated that the genetic differentiation was found mainly among populations. A significant (P < 0.001) genetic difference was found among and within populations (Nm) was measured to be 0.2766 individual per generation between populations, suggesting that gene exchange between populations was very low.The result of AMOVA showed that the percentages of genetic variation among populations were 64.38%  to 0.4732 (between Pop7 and Pop9) . The AMOVA analysis also showed that 32.89% of total genetic variability occurred among the three geographic regions (K = 3). These groupings were entirely consistent with those of the UPGMA clustering results.POPGENE analysis revealed genetic distances between populations of nd Pop9) . The UPG regions . In the  regions , the higD test [D = 0.513, P = 0.7187). Fu’s Fs statistic [. Thus, no clear signal of demographic expansion by Fu’s Fs test and Tajima’s D test was revealed for all the populations together. Fu’s Fs tests were significantly negative for the three groups  though Tajima’s D tests were positive for Group I and Group II, and negative for Group III (P > 0.05).Tajima’s D test  was positatistic  was negaR. officinale species was PPB = 95.24% and H = 0.3341, higher than the average values of perennial herbaceous  and of species with endemic distribution  [R. officinale was similar to that of R. tanguticum  [R. officinale maintained a higher genetic diversity at the species level. However, in contrast, the genetic diversity at the population level was pretty low .The results of the present study showed that the genetic diversity of the  et al.) . The preRheum is anthophilous [R. officinale have wings, so they are more easily dispersed by wind than other species of Polygonaceae. In addition, R. officinale is a long-living herbaceous and it can grow more than 20 years and produce large numbers of seeds every year. The germination rate of R. officinale is high [Although many studies have demonstrated that endangered and endemic species tend to possess low levels of genetic diversity based on ISSR data ,35, someophilous . On the  is high . Therefo is high ,41,42.PPB = 44.57%, H = 0.1614, R. officinale. In contrast, genetic diversity of the Pop6 population from Mt. Jinfo in Chongqing was obviously lower than other populations. The reason might be that there are only five individuals in this population. In contrast with Shennongjia National Nature Reserve, Mt. Jinfo is a famous tourism area, and human activities frequently happen in this area. Moreover, this area is now a forest fragment surrounded by agricultural lands. Fragmentation may increase levels of inbreeding and/or genetic drift [Of all the studied populations, the Pop2 population had the highest genetic diversity  and AMOVA (Φst = 0.7438), which is similar to the higher genetic differentiation in endangered and endemic species in Megacodon stylophorus (Gentianaceae) [Rhodiola alsia (Crassulaceae) [Torreya jackii [Φst) is 0.807, 0.703 and 0.670, respectively. However, the present study showed an opposite finding to the previous studies of R. tanguticum [et al. [Gst) and 0.290 (Φst), and that from Chen et al. were lower  [R. tanguticum were collected only from Qinghai province in their studies. In fact, R. tanguticum was also distributed in Gansu, Sichuan and Ningxia provinces [R. officinale in the present study covered the entire distribution. As Pfeifer and Jetschke [vs. Pop11) and 591.854 km, respectively. R. officinale is outcrossing and its seeds are dispersed by wind. Therefore, large geographic barriers, such as Mt. Qinling and Mt. Daba and the human activities between populations greatly hindered gene flow via seed and pollen dispersal among populations. Typically, when Nm < 1, differential selection might be very strong, and population differentiation might be maintained [R. officinale, Nm estimated from Gst was only 0.2766 and that is far below 1, indicating the gene flow among R. officinale populations with discontinuous distributions was limited and might enhance the genetic differentiation among populations. Moreover, the Mantel test revealed a significant correlation between genetic and geographic distances , displaying a clear isolation of populations by geographic distances in shaping the present genetic structure of R. officinale. This genetic structure was further confirmed by the topology of UPGMA  , Rhodiolulaceae)  and Torrnguticum ,14. Hu e 0.2118) . The rearovinces . The samJetschke  reportedintained . In R. oof UPGMA  and the of UPGMA . On the ulations .R. officinale, whereas populations from central and eastern Mt. Qinling and eastern Mt. Daba are in the eastern part of the distribution of R. officinale. This finding was consistent with the results of the Bayesian analyses, which was clearly identified the same three main group clusters. Hence, the present genetic structure could be partly explained by the isolation-by-distance model [Fs tests.In the UPGMA tree, populations were mainly divided into three geographic groups . Group Ice model , as indiR. officinale, the genetic diversity of populations which were collected from southwestern part of its distribution  was lower than that of the populations from the central  and northeastern of its distribution . It is well known that China’s topography is divided into three terraces from the west to the east: Mt. Hengduan lies in the first terrace which mainly includes the Qinghai-Tibet Plateau, with the altitude higher than 3000 m; the second terrace refers to the eastern and northern areas out of the Qinghai-Tibet Plateau, with an average altitude of lower than 3000 m; the third terrace is mainly hills and plains in the east, with an average altitude of lower than 500 m. R. officinale is distributed in the first and the second terrace. Populations Pop9 to Pop12 are located in Mt. Hengduan which belongs to the first terrace, and the altitudes of those populations are higher than 3400 m. The other populations are located in the central and the northeastern area of the species’ distribution in the second terrace, with an altitude of lower than 2900 m. Compared with the second terrace, the first terrace is the youngest orogeny of the mountains in Neozoic era, and the genetic diversity of the populations located in this area is low. The reason may be that accompanying with the uplifts of Mt. Hengduan, the distribution of the species extends to the higher altitude, which might cause the disjunctive distribution of R. officinale. This disjunctive distribution pattern of R. officinale may be another reason for the present genetic structure. These areas with lower genetic diversity are not the suitable habitat for the growth of the species.Combined with the geographic distribution pattern of R. officinale. The results reported here revealed low genetic diversity at population level and high genetic diversity at species level in R. officinale. High genetic differentiation that occurred among populations and might be due to limited gene flow and genetic drift. In general, this species is not genetically depauperate. The main factor responsible for this threatened species may be recent over-collection of the medicinal organs from the field, rather than a lack of overall genetic diversity. Therefore, the exploitation of wild resources should be forbidden. Considering the high genetic differentiation of R. officinale, preservation of any population would be insufficient to conserve all the variation in the species. Thus, the priority must be to protect all the existing populations in situ, especially those extant populations with high levels of genetic variation of different regions such as Pop1, Pop2 and Pop5, we suggest that their habitats be protected and the exploitation of wild resources be prevented. If ex situ conservation is required, samples should be collected from as many populations as possible from the whole distribution, and populations with small sizes  should receive more attention. On the other hand, to meet the bulk commercial demand for this traditional medicinal plant, cultivation facilities can be established as an alternative source of raw materials. Therefore, the high genetic diversity of the materials  should be used in cultivation in order to reduce the inbreeding depression.The primary objective in nature conservation is to preserve as much as possible of the evolutionary potential of species through maintaining as much genetic diversity as possible . The maiR. officinale, including Henan, Hubei, Shaanxi, Sichuan, Chongqing, Guizhou and Yunnan provinces, China. 16–20  fresh leaves were collected randomly in each population, depending on accessibility and population size. Each population was positioned by a GPS and the detailed locations of the studied populations are listed in Twelve populations were sampled throughout the distribution of Total DNA was extracted from the silica gel-dried leaves using the modified 2× CTAB procedure . The quaR. officinale  agarose gels, in 1× TBE Buffer at 110 V for 1.5 h and stained with ethidium bromide (0.5 μg/mL). Gels with amplification fragments were visualized and photographed in UV light by using Bio-Rad Gel Documentation System . DL2000 ladder  was used as DNA molecular weight.One hundred ISSR primers synthesized by Shanghai Sangon Biological Engineering Technology & Service (China), according to the primer set published by University of British Columbia, Canada (UBC set No.9) were used for amplification to standardize the PCR conditions. Thirteen of 100 ISSR primers produced clear, reproducible and relatively high polymorphism bands were selected for all samples of ficinale . The effficinale . PCR proPPB), observed number of alleles (Na), the effective number of alleles (Ne), Nei’s gene diversity (H) [I) [GST) [Nm) were calculated using the computer program POPGENE version 1.32 [Nm among populations was computed using the formula of Nm =0.5(1 − GST)/GST [D test [Fs test [D and Fu’s Fs are significantly negative [The amplified fragments, with the same mobility according to their molecular weight (bp), were scored in terms of a binary code as present (1) or absent (0). Only those consistently reproducible bands were scored, and smeared and weak bands were excluded. Genetic parameters including the percentage of polymorphic bands (sity (H) , Shannon (H) [I) , Nei’s g (H) [I) , Nei’s gI) [GST)  and geneion 1.32 . An estiGST)/GST . The obtGST)/GST . In addiGST)/GST  were genGST)/GST . The sigGST)/GST  (computi [D test  and Fu’s[Fs test . The demK) in a sample and to assign individuals to one or more of these populations (K). The number of genetically distinct clusters (K) was set to vary from 1 to 12 . The model was run for eight independent simulations for each K, used a burn-in length of 50,000 and a run length of 100,000 iterations. Following the program’s dominant marker settings, the “no admixture” model was used, and uncorrelated allele frequencies among populations were assumed. The most likely number of clusters was estimated according to the model value (ΔK) based on the second order rate of change, with respect to K, of the likelihood function, following the procedure described by Evanno et al. [A Bayesian analysis of ISSR population structure was performed on the entire data set using the program STRUCTURE (version 2.3)  to deteco et al. .R. officinale was high at the species level, while the genetic diversity was low at the population level. High genetic differentiation was found mainly among populations, which may be attributed to geographic isolation by the limited gene flow and genetic drift. Cluster analysis using the UPGMA method grouped all populations into three geographic groups. Based on these findings, strategies are proposed for the conservation and cultivation of the species.In summary, our results indicated that the genetic diversity of


Pan paniscus) inhabit regions south of the Congo River including all areas between its southerly tributaries. To investigate the genetic diversity and evolutionary relationship among bonobo populations, we sequenced mitochondrial DNA from 376 fecal samples collected in seven study populations located within the eastern and western limits of the species’ range. In 136 effective samples from different individuals (range: 7–37 per population), we distinguished 54 haplotypes in six clades , which included a newly identified clade (D). MtDNA haplotypes were regionally clustered; 83 percent of haplotypes were locality-specific. The distribution of haplotypes across populations and the genetic diversity within populations thus showed highly geographical patterns. Using population distance measures, seven populations were categorized in three clusters: the east, central, and west cohorts. Although further elucidation of historical changes in the geological setting is required, the geographical patterns of genetic diversity seem to be shaped by paleoenvironmental changes during the Pleistocene. The present day riverine barriers appeared to have a weak effect on gene flow among populations, except for the Lomami River, which separates the TL2 population from the others. The central cohort preserves a high genetic diversity, and two unique clades of haplotypes were found in the Wamba/Iyondji populations in the central cohort and in the TL2 population in the eastern cohort respectively. This knowledge may contribute to the planning of bonobo conservation.Bonobos ( Pan paniscus) live on the left bank of the Congo Basin and are separated from other Pan populations by the Congo River. The monophyletic origin of bonobos in great apes is supported by recent molecular phylogenetic studies Pan troglodytes) has been estimated to be about 1 million years ago (Ma) Bonobos  consisting of three selected blocks of flanking positions. Consequently, we distinguished 54 mtDNA haplotypes in all the samples. MtDNA haplotypes were locally clustered in the bonobo samples from the Democratic Republic of the Congo (DRC), in which 45 haplotypes (83%) were locality-specific (autoapomorphic) and only 9 (17%) were shared (synapomorphic) by two or three populations . The proClustering analyses revealed six groups of haplotypes (haplogroups) in this study. Three of these groups were named A, B, and C clades in previous studies The results of clustering suggested that the observed clades were evolutionarily related to each other, with a substantial number of nucleotide substitutions, in which the mean number of pairwise haplotype differences between the clades (36.03±7.69) was 4.7 times larger than that within each clade (7.74±2.61) .The unique haplotypes of the C clade have been reported previously, but their geographical distribution in the wild was not identified 3 to E5” We named the sole clade consisting of autoapomorphs in TL2 as D clade. Their related sequences have previously been reported . The Malebo, TL2, and Wamba populations had relatively lower diversity. The Wamba population revealed the smallest estimate of haplotype diversity (0.694), suggesting a decline in the variety of haplotypes in this population. The Malebo and TL2 populations, inhabiting the western and eastern periphery of the species’ distribution, respectively, also showed lower estimates of the mean number of pairwise differences and nucleotide diversity than other study populations. In contrast, populations in the central region (except for the Wamba population) were characterized by abundant and diverse mtDNA variations.The diversity of mtDNA in terms of haplotype diversity, mean number of pairwise differences, and nucleotide diversity varied among populations . AlthougThe genetic diversity of populations usually declines from the center of a geographical range to the periphery ST) genetic distances and the statistical test results are presented in ST distance = 0.111, p = 0.09), Salonga vs. Lac Tumba, Lomako, Wamba, Iyondji , and Lomako vs. Iyondji . We constructed a population tree using the unweighted pair group method with arithmetic mean (UPGMA) using net pairwise FST distances to find the proximity of mtDNA variations among study populations. The results revealed three clusters of bonobos in the DRC, corresponding to the Malebo and Lac Tumba cohort in the west region; the Lomako, Wamba, Iyondji, and Salonga cohort in the central region; and TL2 as the sole cohort in the east region  was larger than those observed between west and central (0.4281) and between west and east (0.4731). Based on the genetic distances, the east region could be regarded as being more distantly related to the central than the west. This conspicuous feature of the genetic relationships among the three population cohorts gives serious cause for reconsidering the hypothesis that the riverine barrier to individual migration was a significant factor in the evolution of this species. Genetic assessment of the population structure using analysis of molecular variance (AMOVA) revealed a slight difference in the total variation partition between the two population categories: we found 40.8% of the mtDNA variation among the seven study populations and 48.0% variation among the three cohorts . TherefoST) among the populations showed significant coefficients of correlation with all the geographical indices . The genetic distance  and the number of tributaries showed a significant correlation with one population . Although not statistically significant, the TL2 population consistently showed negative coefficients in the comparison, which suggests that the factors influencing the genetic distance between TL2 and other populations differed from those influencing the other six populations. When TL2 was excluded from the calculations, statistically significant correlation coefficients were noted in five populations for straight distance, none for detoured distance, and only one population  for the number of tributaries  based on 21 pairs  for singThe riverine barrier effect was highlighted for gene flow among bonobo populations in a previous study, and the Lomami River, separating the TL2 population from others, was considered the sole barrier to migration An alternative explanation for the observed differentiation in bonobo populations is that the genetic differentiation and historical fragmentation may have been caused by the locations of refugia during the Pleistocene. Several studies have suggested that the location of forest refugia in the Congo Basin at the Last Glacial Maximum  was in the central parts of the southern Congo Basin Regarding the Lomami River, neither the detoured distance nor the number of tributaries showed a positive correlation coefficient with genetic distance from the TL2 population . This obPresent-day rivers as barriers to gene flow could not fully explain the genetic structure of bonobo populations confirmed in this study. The geographical pattern of the bonobo genetic structure seems to have formed over hundreds of thousands of years. After bonobos and chimpanzees diverged about 1 Ma In this study, we classified the bonobo populations in the DRC into three cohorts in different localities . Strong In the conservation of great apes, it is important to prioritize areas with high genetic diversity and to preserve unique haplotypes. Therefore, the current study showing the distribution of haplotypes in a broad bonobo habitat will hopefully contribute to the planning of bonobo conservation.DNA sampling was performed at natural sites in bonobo habitats in the DRC from July 2010 to March 2012. We collected fecal samples of wild bonobos from seven distinct populations in the DRC . Basic iWhen we found feces under nests, we estimated the freshness of the nest (most were less than a day old), the number of nests, and latitude and longitude using a global positioning system (GPS). For well-habituated groups, main parties were followed from nest to nest and feces were collected when bonobos defecated during direct observation. The sampling never interacted or interfered with bonobos because samples were obtained non-invasively under the nested tree or directly from the nest after leaving of the host.We also estimated the size  and hardness  of the feces to check health status and to estimate the recovery rate of the mtDNA. To estimate genetic diversity within a population, we collected fecal samples from two or more groups for each population. The sampling procedure was as follows. First, a dry cotton swab was rolled on the surface of the fecal sample as extensively as possible. Second, the end of the cotton swab was washed in lysis buffer to shake the feces off the cotton swab. This swabbing procedure was performed at least three times to collect cells. Third, each fecal sample was turned over and steps 1 and 2 of the collection process were repeated using the other side of the cotton swab. Fourth, the tube caps were fastened and the sample number was marked on each tube.The Scientific Authority for CITES and National Scientific Committee for the Worldwide Heritage of UNESCO in DRC has confirmed that we can publish the results obtained from the fecal samples of bonobos carried out from DRC as far as we have research permission that includes the permission to use those samples. Research Permissions during this study were issued by following authorities: 024/ICCN/BP-MA/2010 (for TL2), 051/ICCN/DG/ADG/KV/2011 (for Lomako), 1577/ICCN/ADG/ANG/DG/2008  were given by the Institut Congolais pour la Conservation de la Nature (ICCN). MIN.RS/SG/002/2010 (for Iyondji), MIN.RS/SG/003/2010 (for Wamba), 008//MINRS/CREF/MAB/DG/01MNIK/2011 (for Lac Tumba) were given by Ministère de la Recherche Scientifique (MIN). 001/CREF/2012  was given by the Centre de Recherche en Ecologie et Foresterie (CREF).A total of 376 fecal samples were collected for DNA study in the Democratic Republic of Congo between July 2010 and February 2012. DNA extraction was performed using a proprietary procedure combining a sampling lysis buffer A complete sequence of mtDNA noncoding region was determined from each fecal sample. A DNA fragment spanning the target region was amplified and sequenced using the seven primers listed in Haplotypes were defined by multiple alignments with ClustalX ver. 2.1 ST distance The mtDNA diversity within populations was estimated in terms of haplotype (gene) diversity, mean number of pairwise difference, and nucleotide diversity According to the riverine barrier hypothesis, the genetic similarity between populations separated by a river should be higher in the headwaters (where the river is narrower) than in its lower parts ST), a normal distribution was not rejected. . Correlations were tested using Pearson’s correlation test. A generalized linear model (GLM) was used for calculations of AIC to estimate whether tributaries of the Congo River influenced genetic distances.The analyses were performed with R and JMP . For the dataset of genetic distance (pairwise FTable S1Summary of DNA experiments.(TIF)Click here for additional data file.Table S2Comparison of six clades of haplotypes withmean number of pairwise haplotype differences. Mean number of pairwise haplotype differences was compared within and between clades shown in (TIF)Click here for additional data file.Table S3Comparison of population distances with results of test for their statistical significance. Values below the diagonal indicate estimates of population pairwise FST calculated assuming Tamura-Nei mutation model. Values above the diagonal indicate P values of permutaion test  for the null hypothesis of FST = 0 by the software Arlequin version 2.000 .(TIF)Click here for additional data file.


Studies of the temporal patterns of population genetic structure assist in evaluating the consequences of demographic and environmental changes on population stability and persistence. In this study, we evaluated the level of temporal genetic variation in 16 anadromous and 2 freshwater salmon populations from the Western White Sea Basin (Russia) using samples collected between 1995 and 2008. To assess whether the genetic stability was affected by human activity, we also evaluated the effect of fishing pressure on the temporal genetic variation in this region.We found that the genetic structure of salmon populations in this region was relatively stable over a period of 1.5 to 2.5 generations. However, the level of temporal variation varied among geographical regions: anadromous salmon of the Kola Peninsula exhibited a higher stability compared to that of the anadromous and freshwater salmon from the Karelian White Sea coast. This discrepancy was most likely attributed to the higher census, and therefore effective, population sizes of the populations inhabiting the rivers of the Kola Peninsula compared to salmon of the Karelian White Sea coast. Importantly, changes in the genetic diversity observed in a few anadromous populations were best explained by the increased level of fishing pressure in these populations rather than environmental variation or the negative effects of hatchery escapees. The observed population genetic patterns of isolation by distance remained consistent among earlier and more recent samples, which support the stability of the genetic structure over the period studied.Given the increasing level of fishing pressure in the Western White Sea Basin and the higher level of temporal variation in populations exhibiting small census and effective population sizes, further genetic monitoring in this region is recommended, particularly on populations from the Karelian rivers. Most empirical studies of genetic structure in natural populations use a single sampling time point, assuming that the genetic pattern is stable over time . HoweverSalmo salar L.), show great variation in philopatry (homing) and dispersal (straying) [Salmonids, particularly Atlantic salmon (traying) , which mtraying) , which ctraying) ,10-12. Htraying) . From a traying) ,15. Moretraying) , such astraying) , stockintraying) ,19.Studies of temporal variation in Atlantic salmon based on neutral markers involve mostly North American ,10,20,21Atlantic salmon populations of the Western White Sea (particularly of the Kola Peninsula) are generally considered to be stable and less affected by human activities . This reHere, we characterised the level of temporal genetic variation in 16 anadromous and 2 freshwater Atlantic salmon populations spawning in the rivers of the Western White Sea Basin. We subsequently evaluated the effect of the fishing pressure on the temporal genetic variation in this region. Our specific aim was to determine the level of genetic stability in salmon populations in the Western White Sea, to assess whether the genetic stability was affected by the increasing level of the fishing pressure and, on the basis of the obtained results, to provide management recommendations for conservation.HE = 0.45; mean AR = 3.80) to relatively high in the anadromous populations of the Kola Peninsula  (Table FST) exhibited the opposite pattern. The highest genetic differentiation was observed among the freshwater populations of the Western White Sea Basin (FST = 0.199), and the lowest was found in the anadromous populations of the Kola Peninsula (FST = 0.012). Five populations  were found to deviate from Hardy-Weinberg equilibrium after correcting for multiple (significance) tests. However, these results were treated as negligible due to the occurrences of both heterozygote deficiency and excess at a few loci  among the temporal samples within each river (FST = 0.012 ± 0.005), which was nearly 7 times lower than that between the spatial samples (FST = 0.082 ± 0.004). Pairwise genetic differentiation (FST) among rivers was not significant in 121 out of 612 tests, all of which involved anadromous populations of the Kola Peninsula  was 4.8%, which is close to the intended value of 5%. Given that the lowest significant FST value observed in our data was 0.0015, it is therefore likely that small but significant FST values detected in our study reflect the true level of genetic differentiation. Furthermore, the null hypothesis of genetic homogeneity was rejected using both χ2 and Fisher’s approaches  [Power analyses tests ,40 demonh tests) .P < 0.01-0.05) and expected heterozygosity (Wilcoxon signed-rank test P < 0.05) per locus between earlier and more recent samples were observed in 6 and 1 populations, respectively, out of 18. However, after sequential Bonferroni correction, none of them remained significant. Correlation of the microsatellite allele frequencies between earlier and more recent samples was significant in all cases and varied from 0.79 to 0.98 (P < 0.001). Among anadromous salmon the highest correlation level was observed in populations of the Kola Peninsula (Pearson’s r = 0.93-0.97), and the lowest correlation level was found in the populations of the Karelian White Sea coast (Pearson’s r = 0.79-0.90). The allelic frequencies of the Karelian freshwater salmon of the Pisto and Kamennaya Rivers demonstrated correlation coefficients of 0.87 and 0.98, respectively.Differences in allelic richness  Kola Peninsula, 2) Karelian White Sea coast, 3) Lake Onega and 4) Lake Ladoga, whereas 5) freshwater populations of the Western White Sea Basin, (Pisto and Kamennaya) were the most distanced from other groups  and 2005-2008   .A negative association between the level of temporal stability of allele frequencies and fishing pressure was also evident. The fishing pressure index  and higher correlations of allele frequencies  between the temporal samples in comparison with the Karelian White Sea coast anadromous populations . Overall, the temporal variation within the sampling sites observed in the Western White Sea Basin over a period of approximately 1-1.5 generations (for the River Ponoi–approximately 2.5 generations) was relatively minor compared to the spatial differences between the two. This pattern is typical for salmonids, and several studies have demonstrated the temporal stability of the genetic structure of anadromous and freshwater populations e.g., [The level of temporal stability varied among the Atlantic salmon populations of the Western White Sea Basin. A small but significant proportion of variation explained by the temporal component was observed among 8 populations (7 anadromous and 1 freshwater), whereas the genetic composition of 10 populations was temporally stable. The lowest proportion of the temporal component observed in the anadromous populations of the Kola Peninsula (0.00%-0.86%) was most likely attributed to their higher census and effective population sizes compared to salmon from the Karelian White Sea coast , in whicns e.g., ,28,43,44r1995-2001 =-0.60, P1995-2001 < 0.01 and r2005-2008 =-0.51, P2005-2008 < 0.05). These associations were more clearly manifested in populations with small census and effective population sizes, although the effect was observed across census size classes. Moreover, populations demonstrating a significant level of temporal variation in the genetic composition were more affected by fishing pressure compared to the populations with non-significant genetic changes over time . These associations remained negative, albeit non-significant, when including only populations of the Kola Peninsula, indicating that populations of the western White Sea basin are important contributors to this trend. The observed associations between human activities and genetic variation support the notion of a higher fishing pressure on the populations of the Karelian White Sea coast than on the populations of the Kola Peninsula [2. In contrast, in the Karelian White Sea coast, the human population density was 7 times higher at 1.92/km2 (http://www.gks.ru).However, the effects of migration and genetic drift in shaping the genetic structure of salmon populations in this region may be also influenced by environmental and, in particular, anthropogenic factors. We observed a significant decrease in the genetic diversity of salmon populations with increasing levels of fishing pressure . However, due to compensation of sufficiently large census and effective population sizes of most Atlantic salmon populations in the Western White Sea Basin, the effects of such changes may take a larger number of generations to be detectable ,48. Consr2 = 0.15-0.17), providing support for gene flow overpowering genetic drift . This mOverall, a significant isolation by distance signal among the anadromous populations in the Western White Sea Basin was consistent with previous observations reported in other studies on salmonid populations and particularly in anadromous Atlantic salmon populations ,54-58. MIn general, a higher level of temporal stability of Atlantic salmon population structure was observed in the relatively pristine area of the Kola Peninsula, whereas populations inhabiting the rivers located in more populated area (Republic of Karelia) demonstrated greater temporal variation. Considering the negative influence of fishing pressure on the genetic structure and diversity of salmon observed in this region, conservation measures should be a key component of stock management strategies. Given that the temporal variation was more clearly manifested in populations with small census and effective population sizes the protection and genetic monitoring of such populations is recommended, and particular attention should be paid to the Karelian rivers.2, and samples from different time points were collected from within 4 km of the previous sampling location, except for Pisto (12 km) and Varzuga (10 km). Protocols for DNA extraction, PCR and 14 microsatellite loci genotyping have been previously described by Tonteri et al. [The samples  were collected from Atlantic salmon 1+ - 3+ parr between 1995-2001 and 2005-2008 in 16 salmon rivers distributed along the Kola Peninsula and the Karelian White Sea coast as well as in 2 freshwater rivers in Karelia  and between-population fixation indices (θ). The simulated Fisher’s exact test [GenePop 4.0 [Micro-Checker 2.2.3 [The basic descriptive statistics for each population and locus  were obtained using tat 2.93 . In additat 2.93  within-pact test  implemenePop 4.0  was usedePop 4.0  implemener 2.2.3 .FST) was obtained after 12600 permutations using Fstat 2.93 [Pca-Gen 1.2 [DA genetic distances [Populations 1.2.3 [Arlequin 3.5 [HE) and allelic richness (AR) per locus between temporal samples of each population were assessed using a non-parametric Wilcoxon signed-rank test.The significance of genetic differentiation between populations , leading to FST as low as 0.0005. The most polymorphic locus Ssa404 was excluded from the analysis, due to software limitations allowing ≤ 50 alleles per locus. Significance estimates were based on 1000 independent simulations. We also estimated the α error (type I) by performing a simulation of no divergence among samples . Additionally, the hypothesis of no difference at any locus using the actual genotype data was tested applying χ2 and Fisher’s approaches implemented in the computer software package CHIFISH 1.3 [POWSIM v4.1 ,40 was uFISH 1.3 ).The level of fishing pressure Table  was estiGenAlEx 6 [FST/(1-FST). To confirm the consistency of the migration pattern over time, the test was performed separately for earlier (1995-2001) and more recent (2005-2008) samples. In addition, Mantel’s test (9999 random permutations) was performed to compare the consistency of the pairwise FST values between the earlier and recent samples of 16 anadromous populations in the Western White Sea Basin.The effect of a fishing pressure on the genetic diversity of salmon populations in the region was tested using the SAS ver. 9.2 program , which applied a partial correlation between the allelic richness and the estimated level of fishing pressure while controlling for the estimated census size. In addition, the relationship between the level of temporal stability of the allelic frequencies in a population and the fishing pressure (corrected for the estimated census size of a population) was examined by applying a non-parametric Mann–Whitney U-test. Mantel’s test was implemented using enAlEx 6  and was The authors declare that they have no competing interests.MO performed the laboratory and data analysis, contributed to the study design and drafted the manuscript. CP designed the study, significantly contributed to the data analysis and the writing of the manuscript and assisted with collection of biological samples. AV and JL took part in designing the study, contributed to revisions of the manuscript and collected biological samples. All authors read and approved the final manuscript.Microsatellite diversity indices of the 32 studied Atlantic salmon populations and the results of the Hardy-Weinberg equilibrium test. The year of sampling is indicated after population code. N–number of individuals; A–average number of alleles in a population; HO–observed heterozygosity; HE–expected heterozygosity; HWE–the P value of the Hardy-Weinberg equilibrium test. The P values over all populations and loci have been corrected for multiple significant tests.Click here for fileEstimation of null allele frequencies (Brookfield 1) across loci and populations.Click here for fileFigure S1. The relationships between genetic (FST/(1-FST) and geographic distances for the anadromous populations of the White Sea Basin (dashed line) ; and the Kola Peninsula (solid line) , sampled in (a) 1995-2001 and (b) 2005-2008. The relationships between Kola, Kola and Karelian White Sea coast, and Karelian White Sea populations are presented as open triangles, closed diamonds and open cirlces, respectively. Figure S2. Box-plot showing the difference in fishing pressure (corrected for population census size) on populations of the Kola Peninsula with significant  and non-significant  genetic variation between the temporal samples . Horizontal line, open rectangle, whiskers, and open circle indicate the median, 25th and 75th quartiles, non-outlier range and an outlier, respectively. Fishing pressure was corrected for population census size by dividing the mean fishing pressure for the two sampling years by the estimated census size class of each population.Estimated census size and the evaluation of anthropogenic pressure in the rives of the Western White Sea basin. Click here for filePairwise genetic distances (FST) among Atlantic salmon populations in the basin of the White Sea based on microsatellite data as measured with FST. Salmon populations of the Kola Peninsula are shaded in grey.Click here for file


Parachondrostoma toxostoma) at the river basin scale. Our results revealed low levels of genetic diversity and weak effective population sizes  in all populations. We further detected severe bottlenecks dating back to the last centuries (200–800 years ago), which may explain the differentiation of certain populations. The demographic survey revealed a general decrease in the spatial distribution and abundance of P. toxostoma over the last three decades. We conclude that demo-genetic approaches are essential for (1) identifying populations for which both evolutionary and ecological extinction risks are high; and (2) proposing conservation plans targeted toward these at risk populations, and accounting for the evolutionary history of populations. We suggest that demo-genetic approaches should be the norm in conservation practices.Prioritizing and making efficient conservation plans for threatened populations requires information at both evolutionary and ecological timescales. Nevertheless, few studies integrate multidisciplinary approaches, mainly because of the difficulty for conservationists to assess simultaneously the evolutionary and ecological status of populations. Here, we sought to demonstrate how combining genetic and demographic analyses allows prioritizing and initiating conservation plans. To do so, we combined snapshot microsatellite data and a 30-year-long demographic survey on a threatened freshwater fish species (Parachondrostoma toxostoma) at the river basin scale for conservation purposes. Genetic diversity and effective population sizes are very low, probably due to the strong genetic bottlenecks detected in this study. The species spatial distribution and abundance also decreased during the last decades.We combined genetic and demographic data from a threatened freshwater fish species ( Prioritizing and making appropriate plans to manage and conserve threatened species is a complex task. Global changes simultaneously affect multiple facets of individual species, making predictions difficult  (Storz and Beaumont Ne and census population size (Nc) is notoriously difficult to assess  can be detected even in the absence of demographic bottlenecks  which is considered vulnerable throughout its restricted native range  detect and quantify both contemporary and past Ne , as well as to date main changes in Ne following the last glacial maximum . In parallel, we used a demographic survey performed at the same spatial scale over the last three decades to (3) identify temporal trends in species abundance at the Garonne river basin scale; and (4) assess the current spatial distribution of the species and changes in the distribution over the last three decades.In this study, we attempt to demonstrate how combining PGSs and DMPs provides baseline information for prioritizing and initiating management and conservation plans. We focused on an endangered freshwater fish species . This highlights the urge for conservation actions directed toward the Garonne drainage in order to preserve the P. toxostoma species.Crivelli . The ranP. toxostoma at 76 sites. Two hundred and 30 individuals of P. toxostoma were sampled at sixteen sites . A small fragment of pelvic fin was collected and stored in 90% ethanol. Individuals were all released alive at their sampling site.Ninety-two sampling sites belonging to 34 rivers of the Garonne river basin were investigated using electrofishing in 2010 and 2011 . We did not catch en sites , Fig. 1.P. toxostoma . PCRs were carried out under conditions described by Dubut et al.  at the “Génopole Toulouse Midi-Pyrénées” (France). Allele sizes were scored using the software GENEMAPPER® v.4.0 (Applied Biosystems).We used a salt-extraction protocol to extract genomic DNA from pelvic fins  and expected (He) heterozygosity over loci, as well as Ho and He per loci per site were estimated using ARLEQUIN 3.5  in our dataset  of N1 increased or decreased exponentially to its current size N0  over a time interval of Ta years. This method uses all the information contained in the data and lognormal priors to infer the parameters of the model Ф = {N0, N1, Ta, θ}, where θ = 4N0 μ and μ is the mutation rate. The posterior probability density of Ф is assessed via MCMC algorithms. Microsatellite loci are assumed to be independent and to evolve under a strict SMM. For each river-scale analysis, we performed four independent runs of 5 × 109 steps, considering different starting values and means for priors and hyperpriors for each run . Negative values of this ratio indicate that the population has experienced a decrease in effective population size, while positive values characterize demographic expansions. This approach was also used to estimate a current Ne at the Garonne river basin scale. To do so, we ran MSVAR by pooling all individuals from all rivers in a single analysis. At such a scale, estimates of current Ne were compared to those estimated using the linkage disequilibrium-based approach implemented in LDNe  assess the current spatial distribution of this species in the Garonne river basin; and (3) investigate whether the spatial distribution of this species in the Garonne river basin has declined or expanded over the last three decades.We used the surveillance monitoring database of the French National Agency for Water and Aquatic Environments  to carry out demographic trend and species distribution analyses. This database includes an extensive spatiotemporal set of monitoring surveys of French freshwater fish populations, representative of all fish assemblages and covering varying degrees of anthropogenic disturbances  were directly comparable across years. It is noteworthy that (1) this database and the genetic database have been gathered during independent research projects; and (2) P. toxostoma is relatively rare in this area , which both explain why demographic and genetic data are not available for all sites . To account for potential sampling bias when comparing spatial distributions over time based on datasets not originally collected for this purpose  was then provided by the least-squares means intercepts of the contemporary period-group effect. Temporal trends analyses and spatial distribution models have been developed under the R statistical software 2.13.0 , and we failed to detect significant linkage disequilibrium between pairs of loci (Table S4).He and Ho values across loci within rivers were moderately low , as well as mean number of alleles and allelic richness estimates  and SAV/BAR .The ten runs of the Bayesian clustering analysis were convergent. The rs K = 3 . Most ofrs K = 3 . Overallectively . All butnificant . The str10 (N0/N1) ratio, ranged between −0.705 (ELL) and −1.345  were similar across rivers, with medians ranging from 7 (HER) to 63 individuals (SAL). Concerning ancestral population sizes (N1), median values ranged from 5286 (LOU) to 9155 individuals . On the contrary, the MSVAR analyses revealed significant signals of bottleneck in all rivers  in the whole drainage, whereas LDNe provided a global estimate of 74.6 individuals (95% CI: 54.4–104.6).The analysis performed at the Garonne river scale confirmed the low estimates of current P < 0.05; S < 0), one population (COU) showed a significant positive trend  whereas the remaining six populations  showed no significant trend in abundance (P < 0.001) negative trend indicating a global decrease in the abundance of P. toxostoma populations in the Garonne river basin.Five out of the twelve populations  showed a significant negative trend (P < 0.01) with respect to the whole river basin, and of 13.1% of P. toxostoma's 1980–1992 distribution  of the total river basin stream length in 1980–1992  and 20.9on Figs. , 5. The  SE of thon Figs. .P. toxostoma populations have experienced significant decreases in effective population size (Ne), with reductions of more than 99% of their prebottleneck long-term Ne. We further showed that: (1) in all populations, bottlenecks started 192–727 years ago, and are hence relatively recent ; and (2) all populations show extremely low current Ne. Attempting to identify the causes of such bottlenecks would be highly speculative without further data and analyses. If natural causes  cannot be ruled out, anthropogenic causes are also likely , Paz-Vinas et al. , and the strongest bottlenecks. Altogether, this indicates that these populations may be discriminated from others (1) because gene flow between these populations and others are weak; and/or (2) because genetic drift and inbreeding were particularly high in these populations, causing divergence from other populations in the Garonne river basin.Finally, our PGS also highlighted that P. toxostoma populations from the Garonne river basin. Overall, these results clearly indicate that long-term management should integrate the fact that the evolutionary potential of the species in this geographic area may be weak.To summarize, PGS provided a precise description of the current genetic state of P. toxostoma populations that occurred in the last three decades. Evidence of a demographic decrease was further supported by comparing the P. toxostoma occurrence at the basin scale between two periods (1980–1992 and 2003–2009). This analysis revealed a significant decrease in the distribution range of P. toxostoma, representing 13.1% of the 1980–1992's distribution. These results confirm that over the range of the species, there is a decreasing trend in abundance  until severe and recent (approximately 800 to 200 years ago) demographic collapses entailed Ne of less than a few hundred (sometimes less than a dozen) individuals. This means that very small numbers of effective breeders are currently sustaining populations in the Garonne river basin. This history led to genetically impoverished P. toxostoma populations in the Garonne river basin. Although most populations are genetically homogeneous, these demographic collapses also led to local differentiation in the Garonne river basin. In a more recent timeframe , we showed that this species experienced a global decrease in census size (Nc) over the entire Garonne river basin, although that some populations remained demographically stable or even increased locally. This recent decrease in Nc was accompanied by a significant reduction of its spatial distribution over the Garonne river basin. Because both Ne and Nc are reduced in these populations, P. toxostoma in the Garonne river basin is confronted with a combination of ecological and evolutionary extinction risks, which reinforces its status of vulnerable species in the IUCN red list, and supports the implementation of conservation plans.The history of Ne; and (2) being subjected to a significant and recent decrease in Nc. For instance, we identified the Hers River as a priority population as both genetic and demographic indices are weak. In this case, we propose conservation strategies involving a program of stocking from broodstock stemming from healthy populations, combined with the restoration of habitat and connectivity with other rivers. Healthy populations are those with stable Nc and higher Ne (such as the Petite Barguelonne and Louge rivers). In the second case, only one of the two metrics is available at the sampling site level. In this case, prioritizing conservation plans is less straightforward. For instance, some populations  were subjected to a sharp decrease in Nc in recent years, however, no data are yet available regarding genetic diversity and Ne dynamics. In this case, managers can conduct a genetic monitoring of these populations to help clarify the populations’ status. On the other hand, some populations  have low Ne and low genetic diversity, but lack temporal data regarding Nc. In this case, it is impossible to get the temporal trend of the populations. Thus, invoking the precautionary principle, we propose considering these populations as conservation priority.Our results illustrate how combining genetic and demographic approaches is useful to target and to prioritize conservation and management plans for endangered populations. A main weakness of our study resides in the few number of sampling points common to both temporal trend and genetic analyses. However, this fact may well be the standard for most studies focusing on rare and threatened species. We therefore provide recommendations considering two cases. In the first case, both demographic and genetic are available at the sampling site level. In this case, combining genetic and demographic approaches allows identifying priority populations as those (1) having the lowest genetic diversity and To conclude, we showed how combining analyses based on point genetic studies (PGSs) and DMPs  reveal complementary information underlying different processes operating at different timescales. Demo-genetic approaches allow (1) identification of “at risk” populations; (2) prioritizing conservation and management actions; and (3) proposing plans that account for the evolutionary history and potential of populations. We hence argue that demo-genetic approaches should be the norm in conservation practices. Indeed, these surveys would allow not only prioritizing and initiation of conservation plans (this study), but would also allow the evaluation of dispersal and connectivity through the use of genetic-based inference methods (Broquet and Petit


Culex pipiens complex are important vectors of disease. This study was conducted to genetically characterize Cx. pipiens complex populations in the state of Colorado, USA, and to determine the number of genetic clusters represented by the data. Thirteen populations located among four major river basins were sampled  using a panel of 14 microsatellites. The lowest-elevation sites had the highest Expected Heterozygosity (HE) values (range 0.54–0.65). AMOVA results indicated the presence of statistically significant amounts of variation within each level when populations were analyzed as one group or when they were grouped either by river basin or by their position on the east or west side of the Rocky Mountains. Most pairwise FST values were significant via permutation test (range 0–0.10), with the highest values from comparisons with Lamar, in southeast CO. A neighbor joining tree based on Cavalli–Sforza and Edwards’s chord distances was consistent with the geographic locations of populations, as well as with the AMOVA results. There was a significant isolation by distance effect, and the cluster analysis resolved five groups. Individuals were also assayed with an additional microsatellite marker, Cxpq78, proposed to be monomorphic in Cx. pipiens but polymorphic in the closely related but biologically distinct species Cx. quinquefasciatus. Low frequencies (≤3%) of Cx. quinquefasciatus alleles for this marker were noted, and mostly confined to populations along the Interstate 25 corridor. Pueblo was distinct in that it had 10% Cx. quinquefasciatus alleles, mostly of one allele size. The degree of population genetic structure observed in this study is in contrast with that of Cx. tarsalis, the other major vector of WNV in the western U.S., and likely reflects the two species’ different dispersal strategies.Mosquitoes such as those in the  Culex pipiens complex of mosquitoes consists of Cx. pipiens L., Cx. quinquefasciatus Say, their hybrids, and an autogenous form of Cx. pipiens, Cx. pipiens form molestus Forskål. All taxa are considered efficient vectors of arboviruses such as West Nile virus Cx. pipiens and Cx. quinquefasciatus is the inability of Cx. quinquefasciatus to diapause, which limits its northward spread. The hybrid zone in the U.S. is nevertheless extensive, indicating that a high degree of gene flow has occurred since these species were introduced Cx. pipiens complex mosquitoes to the New World, see In the new world, the Cx. pipiens complex mosquitoes. Also influencing their distribution is a preference for larval sites with organically-enriched stagnant water, which makes these organisms well-adapted to coexist with humans in urban and suburban habitats Cx. pipiens, or specimens that diapause in winter, and pure Cx. quinquefasciatus specimens have not been collected in the state. However, ephemeral summertime introductions of Cx. quinquefasciatus along transportation corridors likely occur and may result in limited hybridization.In this study, we use a combination of microsatellite markers that we recently developed Culex mosquitoes. For example, Reisen et al. Cx. tarsalis vector competence could be attributable to genetic factors, because other sources of variation had been accounted for. In addition, Kilpatrick et al. Cx. pipiens complex mosquitoes that became infected with WNV versus those that did not. Richards et al. Cx. quinquefasciatus vector competence have not been adequately explored and thus could account for such variability. With regard to other mosquito species, Lambrechts et al. Aedes aegypti was likely a function of interactions on a genetic level between vector and virus. Bataille et al. Ae. taeniorhynchus, resulting in genetic divergence and site-mediated disease transmission dynamics.Population genetic studies of disease vectors are useful for their ability to detect and quantify genetic structure in a system. The presence of genetic structure indicates that some barriers to panmixia exist, which can lead to adaptation to local habitats. Such adaptation may play a role in the observed variation in vector competence among populations of Cx. pipiens complex mosquitoes in the central U.S. found a significant IBD effect among the 14 populations sampled, which were separated by an average distance of 112 km Isolation by distance (IBD) is the tendency for populations to diverge genetically with linear distance. Previous work by our lab on Cx. pipiens populations in Colorado. In addition, this study sought to determine whether the new set of markers, used in combination with previously-published markers, would allow finer scale resolution of genetic differences among populations of closely-related individuals.The main objective of this study was to quantify the genetic diversity and differentiation among Cx. pipiens complex mosquitoes  with a copper BB and 0.5 ml of the diluent BA-1 Cx. pipiens and Cx. quinquefasciatus, and effective at discriminating between these two closely-related species Microsatellite analysis was performed on each individual using a panel of 16 microsatellite loci that was divided into two multiplexes . This stCx. pipiens (fixed at three TCG repeats and 208 bp) and polymorphic in Cx. quinquefasciatus  using Nei’s unbiased estimate Allele frequencies were analyzed by the program Microchecker ST values, with the significance of each value determined by permutation test. The SeqBoot program of Phylip Several methods were employed to examine the degree of genetic structure in the study populations. First, Arlequin was used to generate between-population FK from 1–10 with 50,000 burn-in iterations and 100,000 data collecting steps. The log likelihood values (LnP(D)) were averaged to determine which value of K was associated with the highest likelihood value. The program Distruct Structure was used to determine the most likely number of genetic clusters represented by the data. Ten runs with the default settings  were run for each value of ST values (converted to FST/(1-FST) as per Rousset To determine whether there was an isolation by distance (IBD) effect, GENEPOP was used to regress the matrix of linearized FAfter Bonferroni correction, there were 35 instances of HW disequilibrium (out of 182 tests) and all instances were due to an excess of homozygotes. Twenty-two of the departures were due to loci Cxpq68 and Cxpq69, so both loci were excluded from further analyses. The remaining 13 instances were distributed among six of the remaining 14 loci, and ranged from 1–4 instances per locus . Pueblo,E) values were fairly consistent across populations and ranged from 0.542 in Evans to 0.655 in Lamar  corridor. Pueblo had the largest percentage (10%) of Cx. quinquefasciatus alleles, mostly of one size (226 bp).The results of the Cxpq78 assay indicated that all of the populations on the western side of the mountains were fixed for this locus at 208 bp. In addition, three populations in the northeastern part of the state  were also fixed at 208 bp. Several populations  had a low percentage (≤3%) of ST value was modest but statistically significant  indicating detectable genetic structuring in this system. Pairwise FST values between populations ranged from zero to 0.10 and most comparisons were statistically significant  amounts of genetic variation are attributable to grouping the populations by river basin  but the same FCT values (0.03 for grouping populations either by river basin or by side of the mountains).The overall F P<0.05; . Compariparisons . The AMOP<0.0001; r2 = 0.21) indicating a positive relationship between genetic differentiation and linear distance , which are the two lowest-elevation sites and located on the eastern plains. This observation suggests there may be environmental factors that reduce genetic diversity of Cx. pipiens complex populations. For example, lower elevation sites may experience comparatively fewer climatic extremes, which could allow for a greater variety of successful genotypes in those areas. Conversely, it could be that weather conditions at the higher elevation sites reduce a greater percentage of diapausing populations compared to lower elevation sites, resulting in populations with moderately lower genetic diversity.Our results indicate that genetic diversity is fairly consistent across populations, with no sites or groups of sites showing strikingly larger or smaller values. This is perhaps due in part to the scale at which populations were sampled, which is smaller than similar studies of O < HE, indicating an excess of homozygotes. In several populations, including Lamar, Pueblo, Denver, Evans, Fort Collins and Platteville, several of the differences were statistically significant and resulted in departures from HWE. One possible explanation for the observed homozygote excess is the Wahlund Effect It is interesting to note that all of the differences between observed and expected heterozygosity within populations in this study were such that HCx. quinquefasciatus alleles at the Cxpq78 locus in some of the study populations suggests that Colorado is a site of limited gene flow between the two species in the Cx. pipiens complex. The presence of Cx. quinquefasciatus alleles at low frequencies in populations close to the I-25 corridor offers a possible mechanism for their movement, which may occur by anthropogenic means. A similar scenario was proposed for the movement of Aedes aegyptii in the state of Arizona, USA, because local conditions made observed dispersal patterns unlikely by natural means Cx. quinquefasciatus alleles, Pueblo, has some of the warmest temperatures in the state Cx. quinquefasciatus alleles detected in any of the populations west of the Rocky Mountains. This may be due to high elevation areas and dry conditions of western Colorado, which would impede dispersal through those areas. In addition, the road system on the west side of the mountains is such that there is no major north-south highway through the area, reducing chances of human transport.The detection of Cx. pipiens populations in Colorado are not panmictic. For example, most of the pairwise FST comparisons were significant . Epidemiological work conducted on WNV in Colorado has included mapping the locations of disease cases Cx. tarsalis, most of the shaded counties in Cx. pipiens complex mosquitoes Cx. tarsalis and Cx. pipiens, will prove more realistic.Recent studies on Cx. pipiens populations in Colorado, and suggest our work as an example of how genetic data can complement epidemiological data in characterizing a disease vector. Future studies that incorporate population genetics, and epidemiological data on human disease will lead to comprehensive models of disease transmission.Since dispersal and demographic changes are difficult to track in small organisms such as mosquito vectors, population genetics analyses can be employed to inform researchers and disease modelers about these epidemiologically important characteristics. In our study, we performed such analyses for Figure S1Incidence map of West Nile virus neuroinvasive disease in Colorado, USA 2003–2010. Map shows collection sites and West Nile virus neuroinvasive incidence rates by county.(TIF)Click here for additional data file.Table S1Culex pipiens complex populations in this study.Genetic diversity values for 14 Colorado (XLSX)Click here for additional data file.Table S2ST values between pairs of Culex pipiens complex populations in Colorado.Pairwise F(XLSX)Click here for additional data file.


Phragmites australis (common reed) in the Yellow River Delta (YRD), China, where a mosaic of habitat patches varying in soil salinity was detected. We demonstrated that, despite their close geographic proximity, the common reed populations in the YRD significantly diverged at six microsatellite loci, exhibiting a strong association of genetic variation with habitat heterogeneity. Genetic distances among populations were best explained as a function of environmental difference, rather than geographical distance. Although the level of genetic divergence among populations was relatively low (F’ST = 0.073), weak but significant genetic differentiation, as well as the concordance between ecological and genetic landscapes, suggests spatial structuring of genotypes in relation to patchy habitats. These findings not only provided insights into the population dynamics of common reed in changing environments, but also demonstrated the feasibility of using habitat patches in a mosaic landscape as test systems to identify appropriate genetic sources for ecological restoration.Determination of spatial genetic structure (SGS) in natural populations is important for both theoretical aspects of evolutionary genetics and their application in species conservation and ecological restoration. In this study, we examined genetic diversity within and among the natural populations of a cosmopolitan grass  Spatial configuration of suitable environments for organisms is often patchily structured at various scales, from biogeographic regions to local environments within a landscape Numerous studies have revealed the role of environmental patchiness in generating spatial genetic structure (SGS) in natural populations 2 of new land created each year The Yellow River Delta (YRD) lies in the eastern coastal area of China, which is formed by sediment deposition of the Yellow River Phragmites australis, is one of the dominant species in the YRD region, acting as an ecosystem engineer in the restoration of the YRD ecosystem Common reed, Populations occupying adjacent but contrasting habitats in the YRD present distinct advantages for assessing the effects of spatial environmental heterogeneity in relation to soil salinity on population genetic dynamics of the reed. In this study, we examined the level of genetic variation within and among the reed populations in the YRD, using microsatellite  markers. By exploring the correlation between genetic diversity and environmental heterogeneity, we sought to determine whether patchy habitats have structured patchily distributed populations in this area, to assess the effect of the spatial arrangement of habitat patches on the genetic structure of common reed in the YRD. We also aimed to address the feasibility of using patchy habitats as test systems to evaluate the potential for plants to adapt dynamically to changing environments, which is vitally important for selecting appropriate plant materials for ecological restoration 2 in the YRD (2. At each site 3–6 soil samples were collected. The soil samples were taken to the laboratory for measuring saturated paste conductivity (ECe) by using 1/5 diluted extracts  of 1∶5 soil-water extract) This study was conducted over an area of approximately 6622 km the YRD . Local-sSince the YRD has been exploited on a large scale, with many areas in this ecoregion being converted to agricultural or other land uses, a total of 27 sites across the YRD region, with relatively little human disturbance and more than 30 visibly separated patches of common reed, were selected for sampling. The location information and soil salinity of each site are shown in Total genomic DNA was extracted following the CTAB extraction protocol Ao) and allelic phenotypes (Po) were counted. We compared multilocus allele phenotypes found within and among populations to identify samples with identical genetic phenotypes. Repeated phenotypes within populations were assumed to result from asexual reproduction (ramets of a single genet.) and thus excluded from analyses of genetic diversity and differentiation because repeated sampling of a single clonal individual can unduly influence estimates of the distribution of genetic variation H’) based on the average number of unshared alleles between pairs of individuals. Genetic differences between populations were measured with F’ST based on the proportion of genetic variance among populations relative to the total genetic diversity. The Bayesian method, implemented in HICKORY version 1.1 hs) and the level of genetic differentiation among populations (θII). Computations were carried out using the default values, as recommended in the manual Due to the polyploid nature of the common reed, several microsatellite DNA alleles might simultaneously occur at a single locus. Even if only two alleles were detected at a single locus, the allelic configurations might also be greatly variable among individuals as each allele can be present in more than one copy. Considering the difficulties in assessing the actual genotype of each individual based on band intensity and accurately estimating the number of copies of an allele in heterozygous individuals, the banding patterns observed at each polymorphic locus were recorded as ‘allelic phenotypes’ Several complementary approaches were used to examine the correlations between genetic patterns, geographic distances, and soil property . We first examined the effects of geographical location and habitat type on the levels of genetic variation in each population by regression analysis of genetic diversity characteristics  and their associations with latitude, longitude and soil salinity using SigmaStat 3.5 .K = 1–7) using the admixture model with correlated allele frequencies. We performed 5 independent runs for each K value with 100 000 burn-ins and 100 000 iterations after burn-ins. The number of population groups best fitting our data set was defined by ΔK as suggested by Evanno et al. We then tested the correlation between genetic and geographic distances using the Mantel test Finally, we conducted a spatial analysis to estimate the association between each allele and soil salinity using the program SAM Ao) varied from 5 (PaGT4) to 26 (PaGT14), with an average of 11 alleles. The number of allele phenotypes at a single locus (Po) ranged between 19 (PaGT11) and 228 (PaGT14) (Ao and Po for each population are shown in H’) ranged from 1.11 to 2.01  . Two ind to 2.01 . The oveAo) , the observed number of allele phenotypes (Po) , and the within-population genetic diversity statistics (H’)  over six microsatellite loci    . We alsohabitats , which w = 0.57) , indicatP(D) and ΔK values, two clusters (K = 2) best fit the dataset, indicating that two genetically distinctive population groups existed in common reed populations. The clustering of individuals into two groups based on genetic landscapes suggested a division of sample sites into saline and non-saline habitats. Grouping of individuals by geographical location (populations), however, showed high levels of population admixture, as most populations consisted of individuals from different clusters (According to Lnclusters .−06 (corresponding to a 99% confidence level including Bonferroni correction) (PaGT9) frequency and the soil salinity of sampling sites, with the frequency of the 203(PaGT9) homozygote increasing from 3.4% for the lowest saline population (YJNH) to 69.0% for the highest saline population (YJ124)   . BecauseP<0.001) .F’ST = 0.073), weak but significant genetic differentiation, as well as the concordance between ecological and genetic landscapes, suggested some degree of population structuring of the common reed in the YRD.Despite their close geographic proximity, the common reed populations in the YRD significantly diverged in overall genetic diversity within population, and in allele frequencies at six microsatellite loci. The YRD common reed populations exhibited a strong association of genetic variation with environmental heterogeneity, i.e. the salinity differences of different habitats, independent of geographical distance. Although the level of genetic divergence among populations was relatively low  showing a significantly higher frequency in saline habitats than in other sites. The genetic distances between reed populations in the YRD were best explained as a function of environmental differences, rather than geographical distance. Both reduction in genetic diversity and the increase in allele frequency could arise as results of chance for sexual reproduction involving a limited number of genotypes during range expansion and subsequent limitation in seed dispersal. However, these patterns of genetic variation not only occurred at several separate sites in the YRD, but also covariated with environmental salinity. In addition, the large population sizes of common reed at our study sites and the high levels of gene flow among populations should greatly reduce the likelihood of genetic surfing during range expansion. Therefore, genetic divergence among reed populations in the YRD is unlikely to be driven by strictly neutral processes. The correspondence between ecological and genetic landscapes may be indicative of the potential role of environmental variables in driving population divergence Spatial variation in the environment may affect genetic variation in populations living there de facto evidence of adaptive differentiation, it is efficient to identify subtle population structure and concomitant environmental variation representative of a potential selection gradient, to facilitate a further analysis and test of adaptation Correlations between phenotype and environment may be mirrored at the level of individual genetic polymorphisms. A powerful way to detect the footprint of selection in natural situations is to associate allele frequency with environmental variations. A number of previous studies have shown that there is a correlation between genetic diversity and environmental heterogeneity in common reed populations Figure S1Correlation between soil salinity and the heterozygosity of each population (hs) estimated with Hickory v1.1.(TIF)Click here for additional data file.Figure S2Comparisons of genetic diversity among the common reed populations from different salinity environments.Ao: observed number of alleles; Po: observed number of allele phenotypes; H’: allele phenotype diversity statistic based on the average number of unshared alleles between pairs of individuals.(TIF)Click here for additional data file.Table S1Genetic characteristics of the common reed populations from YRD based on six microsatellite loci.(XLSX)Click here for additional data file.Table S2Comparisons of genetic diversity among common reed populations from different salinity environments based on six microsatellite loci.(XLSX)Click here for additional data file.Table S3Mantel tests for the correlation between geographical and genetic distances.(XLSX)Click here for additional data file.Table S4Results of the spatial analysis using the program SAM, with significance level of (a) 5.05E-05; and (b) 5.05E-06 (corresponding to a 99% confidence level including Bonferroni correction).(XLSX)Click here for additional data file.