Aedes (Stegomyia) aegypti (L.), the main vector of dengue virus, is being investigated in areas where a novel dengue suppression program is to be implemented. The aim of the program is to release and establish mosquito populations with impaired virus transmission capabilities. To model effects of the release and devise protocols for its implementation, information about the genetic structure of populations at a range of spatial scales is required.The genetic population structure of Aedes aegypti resting indoors was sampled at four different times of year from houses within the five villages. Genetic markers were used to screen the mosquitoes: two Exon Primed Intron Crossing (EPIC) markers and five microsatellite markers. The raw allele size was determined using several statistical software packages to analyze the population structure of the mosquito. Estimates of effective population size for each village were low, but there was no evidence of genetic isolation by geographic distance.This study investigates a potential release site in the Hua Sam Rong Subdistrict of Plaeng Yao District, Chachoengsao Province, in eastern Thailand which comprises a complex of five villages within a 10 km radius. The presence of temporary genetic structure is possibly caused by genetic drift due to large contributions of adults from a few breeding containers. This suggests that the introduction of mosquitoes into an area needs to proceed through multiple releases and targeting of sites where mosquitoes are emerging in large numbers. Aedes (Stegomyia) aegypti (L.), the main vector of dengue virus, is vital in designing dengue suppression programs. To design a release of dengue resistant mosquitoes, we require information about population structure at a range of spatial scales. This study looked at a small-scale complex of five villages at four sampling periods and mosquitoes from individual houses within the five villages. Genetic markers were used to screen the field-collected mosquitoes in order to characterize population genetic structure. Our results indicated that the effective population size of Ae. aegypti in each village was low. Genetic structure was apparent at local spatial scales, but there was no evidence of genetic isolation by geographic distance. The temporary genetic structure observed may be caused by related individuals emerging from a few productive containers in each village. Our findings could be applied in an effective dengue suppression program by planning multiple releases of dengue resistant mosquitoes in targeted households of each village where large numbers of adult mosquitoes have emerged from identified productive breeding containers instead of making a release in one area and expecting rapid spread throughout the complex.Knowledge about population structure of  Aedes (Stegomyia) aegypti (L.) may have been present in Thailand in the 19th century, its spread from major urban centers and commercial transport routes to rural villages is thought to have occurred in the last 50 years Ae. aegypti at different spatial scales and at different densities of human settlement determine the nature of spread of dengue virus and are also important in modeling the effects of potential control strategies.Though Ae. aegypti with strains of the bacterium, Wolbachia pipientis, has been shown to reduce vector competence of the mosquito for dengue virus Wolbachia-infected Ae. aegypti in northern Queensland, Australia have demonstrated the feasibility of spreading a Wolbachia infection through the wild population in a localised area Wolbachia on dengue suppression and, if successful, will be adopted as an area-wide dengue control strategy.Artificial infection of Wolbachia-infected mosquitoes . It is already known that collections of Ae. aegypti taken from four widely spaced samples in Chiang Mai Province in Thailand were highly differentiated  when five microsatellite markers were employed Ae. aegypti in mainland Southeast Asian countries revealed genetic structure at all spatial scales including those at a distance of less than 500 m Ae. aegypti was demonstrated by mark-release-recapture experiments in which a majority of mosquitoes did not move from their release house or the one adjacent, while those released outdoors moved a maximum of 512 m Detailed knowledge of population genetic structure can be translated into practical information for designing the logistics of a field release of 2. The village complex is a potential release site for Wolbachia-infected mosquitoes that could resist dengue virus infection, so it is important to find out what patterns of mosquito movement and population size occur within and between these specific villages at different times of the year. The implications of the patterns identified will be factored into strategies for release and establishment of Wolbachia-mediated dengue resistant mosquitoes. These mosquitoes are intended to replace the natural population of Ae. aegypti at a target release site and then be spread throughout the country thereby reducing the opportunity for transmission of dengue virus in Thailand.The current study aims to collect population genetic information from within a complex of five villages in Thailand contained within an area of 314 kmAe. aegypti mosquitoes were collected from a complex of five villages: one central village (Village 11) and four outer villages  within a radius of 10 km in the Hua Sam Rong Subdistrict of Plaeng Yao District, Chachoengsao Province, in eastern Thailand , March 2008 (hot-dry season), June 2008 (wet season) and September 2008 (wet season) . The samAedes aegypti, by Population Replacement Using Wolbachia-Infected Mosquito Strain” (COA. No. MU-IRB 2011/227).This study was approved by the Institutional Review Board of Mahidol University at Salaya, Nakhon Pathom, Thailand under the project entitled: Control of the Dengue Vector, 33P]-ATP, 0.4 µM reverse primer, 2.0 mM MgCl2, 0.1 mM dNTPs, 0.5 mg/ml purified bovine serum albumin , 1 µl of 10× PCR amplification buffer, and 0.4 units of Taq polymerase .Genomic DNA of individual mosquitoes was extracted using the Holmes and Bonner method Ae. aegypti from the five villages due to their consistent performance under our laboratory conditions: two Exon Primed Intron Crossing (EPIC) markers; Rps20b, RpL30a Seven markers were used to screen FST with significance determined using permutations were obtained using FSTAT version 2.9.3 FIS were also estimated with FSTAT. Correction for multiple comparisons was made using False Discovery Rate procedures A global estimate (with 95% confidence limits) HO) and expected (HE) heterozygosity were estimated using GenAlEx version 6 FST transformation [FST/(1−FST)] with the natural log of geographical distance Observed , among populations within groups  and within samples.Analysis of molecular variation (AMOVA) was undertaken in Arlequin v3.11 K were not consistent, then the estimate with the highest average posterior probability was used.A factorial correspondence analysis was run in Genetix v4.03 Ne) for mosquitoes in the five village sample. Approximate generation time of one month was assumed for this analysis. The initial sample from each village (Gen 0 – Dec 2007) was compared with the final sample from the same village (Gen 9 – Sep 2008). Waples' Ne. Using widely spaced temporal samples to estimate Ne reduces bias associated with sampling in species with overlapping generations The temporal method of Waples r was estimated for samples in 50–100 m size classes for each village on each sampling occasion using GenAlEx r was tested in GenAlEx by random permutation of individuals around each geographic location to create a distribution under the assumption of no spatial structure.Spatial analysis looks for patches of genetic correlation by comparing pairs of individuals within distance classes. To look at spatial autocorrelation within a village, the autocorrelation co-efficient Ritland's FIS, ranged from 0.01  to 0.14 (Village 1 Jun 2008) (FIS were significant: Village 11 (Dec 2007 and Sep 2008) and Village 1 (June 2008) . Application of a further FDR graphically sharpened method of correction showed significant P-values for Village 3 (Dec 2007), Village 2  and Village 11 (Mar 2008) , indicating that inbreeding is a common occurrence.Null alleles over all loci were suspected in populations from Village 3 and Village 6 in June 2008 due to a DNA amplification problem, so results from these samples were not included in the analysis. Estimates of allelic richness ranged from 3.21 (Village 1 – Sep 2008) to 4.13 (Village 11 – Dec 2007), but there were no apparent seasonal or spatial trends . Allele un 2008) . After aFST over all populations was 0.037  indicating that there was some genetic structure in the dataset as a whole (i.e. FST>0). The AMOVA was significant for each of the variance components at each level of the hierarchical model: among villages , among temporal samples within villages  and within sampling occasions , suggesting both spatial and temporal differentiation of mosquito populations. There was no significant correlation between genetic distance and geographic distance  at the small spatial scale of this study.The estimate of K = 1).Analysis of genetic and spatial structure with Geneland showed that the genotypes for the December 2007 sample fall into two clusters, one comprising the samples from the central village (11) and the second cluster containing the samples from the four surrounding villages (data not shown). For each of the other sampling occasions within a season , the complete dataset comprised only one cluster  in the five villages were low and ranged from 92.7 to 221.5 (Estimates of effective population size (to 221.5 . ApproxiP = 0.048), suggesting a decrease in relatedness with increasing distance although R2 values for the negative relationships were low (0.0001 to 0.012)  . The higThe Hua Sam Rong Subdistrict of Plaeng Yao District, Chachoengsao Province, in eastern Thailand is a potential release site for mosquitoes that have a reduced capacity to transmit dengue virus. Information about mosquito movement within this Subdistrict in Village 6 has been collected in mark-release-recapture studies In general terms, there was evidence for genetic structure  in the dataset as a whole, though it did not follow a pattern of genetic isolation by geographic distance. Our results confirm the finding of Hlaing et al. Ae. aegypti between villages which would be expected under the second scenario, i.e. a widespread outbreak and genetic homogenization. Based on estimates of pairwise FST, samples from Villages 11, 1 and 2 show within-village seasonal differences which could also indicate sweeps of mosquitoes moving through at least part of the village complex in different seasons. The assignment of samples from Village 11 in December 2007 to a different Geneland cluster from all other villages suggests a local outbreak effect as proposed in the first scenario. Samples from Village 1 in December 2007 are differentiated from all others according to pairwise comparisons of FST which is evidence of local structure which Geneland did not characterize. Both Villages 3 and 6, show no seasonal within-village patterns of differentiation in pairwise FST. However, when spatial characteristics are taken into account by Geneland, samples from Village 3 are assigned to two seasonal-based clusters. Similarly, samples from Village 6 comprise three clusters based on spatial and seasonal characteristics.Based on the clusters assigned by Geneland for each collection month , there was no genetic differentiation of Larval abundance in the Subdistrict is highest in the wet season (May–October) and dengue transmission is also most common at this time e estimates obtained here. However it is known that a majority of mosquito larvae do not become adults Ae. aegypti from Bangkok Ae. aegypti in Thailand has been described as low Ae. aegypti has also been estimated as <100% in the field, for example, female insemination rates in 9 m3 field cages were 65–85% Larval abundance in houses in Thai villages can be high; for instance Strickman and Kittayapong NeAe. aegypti, which have overlapping generations. However, the bias can be reduced by sampling consecutive age cohorts, an option not possible in this study, or by sampling over long time intervals Ne appears realistic. In this case, estimates of Ne are low and are indicative of low genetic variability  as well as spatial isolation. This means that release of Wolbachia-infected mosquitoes should occur within each village of the complex rather than making a release in one area and expecting rapid spread throughout the complex.The temporal method for estimation of Ae. aegypti by humans Ne) showed Villages 2 and 6 as having the highest numbers, though 95% confidence intervals overlapped with estimates for the other villages.The disjunctive nature of population structure over small and large distances has been attributed to transport of Ae. aegypti? Initial releases will depend on movement patterns at the local spatial scale. In the five-village complex we found weak and haphazard patterns of spatial autocorrelation suggesting that, also at this scale, natural dispersal may be influenced by human transport of Ae. aegypti. In combination with short distance natural dispersal limited mainly to within a house or an adjacent house, multiple intensive releases are envisaged for putting the dengue resistant mosquitoes into a village complex in Thailand. With this type of population structure, successful Wolbachia invasions may depend on fine scale monitoring of infection frequencies, so that strategies can be implemented locally to counter areas where uninfected individuals may persist. Because villages form relatively isolated units, it is also possible that any evolutionary changes in the mosquito nuclear genome or viral genome in response to Wolbachia may remain relatively contained.What information do these findings give us to assist with release and establishment of the dengue resistant strain of


FST = 0.19). Moreover, the utility of gSSRs, EST-SSRs, and the combined sets of SSRs was also evaluated in assessing genetic diversity and population structure in flax. Six outlier loci were identified by at least two neutrality tests showing footprints of balancing selection. After removing the outlier loci, the STRUCTURE analysis and the dendrogram topology of EST-SSRs improved. Conversely, gSSRs and combined SSRs results did not change significantly, possibly as a consequence of the higher number of neutral loci assessed. Taken together, the genetic structure analyses established the superiority of gSSRs to determine the genetic relationships among flax accessions, although the combined SSRs produced the best results. Genetic diversity parameters did not differ statistically (P > 0.05) between gSSRs and EST-SSRs, an observation partially explained by the similar number of repeat motifs. Our study provides new insights into the ability of gSSRs and EST-SSRs to measure genetic diversity and structure in flax and confirms the importance of testing for the occurrence of outlier loci to properly assess natural and breeding populations, particularly in studies considering only few loci.Genomic microsatellites (gSSRs) and expressed sequence tag-derived SSRs (EST-SSRs) have gained wide application for elucidating genetic diversity and population structure in plants. Both marker systems are assumed to be selectively neutral when making demographic inferences, but this assumption is rarely tested. In this study, three neutrality tests were assessed for identifying outlier loci among 150 SSRs (85 gSSRs and 65 EST-SSRs) that likely influence estimates of population structure in three differentiated flax sub-populations (The online version of this article (doi:10.1007/s11105-013-0568-1) contains supplementary material, which is available to authorized users. FST  and expressed sequence tag-derived simple sequence repeats (EST-SSRs) facilitating the measurement of genetic variation on a genomic scale , a globally important crop because of its seed oil, stem fiber, and functional compounds, is one of the oldest domesticated plants utilized by humans, possibly for as long as 30,000 years , South American (n = 22), and North American (n = 28) from 16 countries was included  and estimated using the rarefaction method implemented in HP-RARE v.1.2 . Allele number, alleles per locus, major allele frequency, expected heterozygosity, and population specific FST-based tests (inter-population differentiation) were assessed. The coalescent-based simulation method of Beaumont and Nichols  determined by an initial run with 100,000 simulations, the distribution of neutral FST (depicted by curves around the assessed loci) was computed using putatively neutral loci with 100,000 simulations and a bisection approximation algorithm . The analysis is based on a logistic regression to decompose FST into a β component  and a locus specific α component . Departure from neutrality at a given locus is assumed when the locus-specific component is necessary to explain the observed pattern of diversity. If α > 0, there is indication of positive selection, if α < 0, balancing selection is invoked. For each locus, the probability of being under selection is then inferred using the Bayes factor (BF). Based on Jeffreys’ )2 − 1] / [(1 / (1 − Hpop2))2 − 1] in two populations, where H is the expected heterozygosity  ratio of gene diversity [, RepBase-Green plant repeat  databases. A cutoff E-value < 10−15 was used to infer putative homology and assign functional annotation.The likely functions of the outlier candidates were investigated based on similarity comparisons. Nucleotide-nucleotide (BLASTn) and translated queries versus protein database (BLASTx) were used to identify candidate genes and protein function. Queries were conducted against the NCBI-nt and NCBI-nr ) estimates and the ad hoc statistic ∆k for each K were calculated  for each accession was calculated by averaging the 30 runs of the best K for each SSR group. The similarity analysis was based on the Bray–Curtis similarity index to construct UPGMA dendrograms as implemented in the PAleontological STatistics (PAST) software  analyses to compare the utility of the gSSRs, EST-SSRs, and combined SSRs in assessing population structure. The Bayesian analysis was carried out using the program STRUCTURE , which ranged from 0.77 to 0.81(Table FST = 0.30) followed by the North American (FST = 0.19) and the South American (FST = 0.14). The South American and North American sub-populations presented higher allele numbers, alleles per locus, expected heterozygosity, allelic richness, numbers of private alleles, and PIC values than the South Asian sub-population, with the South American sub-population capturing the highest overall diversity . The major allele frequency was the same for both SSR groups . The expected heterozygosity was 0.346 and 0.351 for gSSRs and EST-SSRs, respectively (P = 0.855). The mean PIC value was also similar for gSSRs (0.298) and EST-SSRs (0.300) (P = 0.837).Within the three reference sub-populations, genomic and EST-SSRs amplified 233 and 175 alleles, respectively. The mean number of alleles per locus was 2.70 and 2.73 for gSSRs and EST-SSRs, respectively  were consistently identified as outliers through 10 independent iterations (FDR < 0.05) including three gSSR loci  and three EST-SSR loci   and its reduced overall genetic diversity , the lnP(D) increased with increasing value of K but did not show evidence of a maximum for any of the SSR classes  again increased with increasing value of ely Fig. . The ΔK The UPGMA dendrograms displayed by the three groups of SSR loci revealed different population clustering patterns . An improvement was observed in the dendrogram topology rather than in the average bootstrap values accounted for by the 62 putative neutral EST-SSR loci . A reduction in sub-clustering was observed, and the topology was similar to that accounted for by the combined SSR loci. Finally, for the 144 combined neutral SSRs, the cophenetic correlation value was 0.82 and the average bootstrap value was 37.7 %, not statistically significant as compared to the 150 combined SSR loci . The dendrogram topologies and genetic relationships were largely similar between both groups of combined SSR loci. Taken together, these data suggest an improvement in dendrogram topology as a result of using neutral markers for EST-SSRs only. Combined SSRs, whether in whole or neutral sets, resulted in a greater degree of genetic resolution compared to any of the separate sets, likely because of the larger number of neutral data points.Removal of the putative outlier loci resulted in a cophenetic correlation value of 0.76 and an average bootstrap value of 29.1 %  which may be one of the factors that influenced similar levels of genetic diversity detected  as selective loci would tend to show high FST values. In our study, however, the neutral FST distribution was 0.203 implying that this factor could affect the efficiency of LOSITAN and Bayescan in detecting positive selection. On the other hand, under balancing selection, a high neutral FST distribution would be more favorable for detecting selective loci. Bayescan failed also in identifying outliers affected by balancing selection. Comparisons of FST outlier tests indicated that Bayescan has the lowest type I error but also has limited power in detecting balancing selection  and strong population structure   response to UV-B radiation  Table  consiste9) Table . For exa9) Table . Organis9) Table . Chromat9) Table . Recent Genetic structure studies are paramount to the characterization of natural populations and germplasm collections and to assist breeding decisions. An important challenge is the choice of suitable molecular markers that reflect unbiased demographic processes. Genomic SSRs and EST-SSRs have been used and compared for genetic studies in other plant and animal systems Below is the link to the electronic supplementary material.


Avicennia germinans for 11 microsatellite loci and 940 Rhizophora mangle for six microsatellite loci and subsampled two non-coding cpDNA regions in order to understand population structure, and gene flow within and among four major estuaries on the Caribbean and Pacific coasts of Panama.Mangroves are ecologically important and highly threatened forest communities. Observational and genetic evidence has confirmed the long distance dispersal capacity of water-dispersed mangrove seeds, but less is known about the relative importance of pollen vs. seed gene flow in connecting populations. We analyzed 980 A. germinans and 0.8 in R. mangle) and strong patterns of spatial genetic structure within estuaries, although A. germinans had greater genetic structure in nuclear and cpDNA markers (7 demes > 4 demes and Sp= 0.02 > 0.002), and much greater cpDNA diversity (Hd= 0.8 > 0.2) than R. mangle. The Central American Isthmus serves as an exceptionally strong barrier to gene flow, with high levels nuclear (FST= 0.3-0.5) and plastid (FST= 0.5-0.8) genetic differentiation observed within each species between coasts and no shared cpDNA haplotypes between species on each coast. Finally, evidence of low ratios of pollen to seed dispersal (r = −0.6 in A. germinans and 7.7 in R. mangle), coupled with the strong observed structure in nuclear and plastid DNA among most estuaries, suggests low levels of gene flow in these mangrove species.Both species showed similar rates of outcrossing (t= 0.7 in We conclude that gene dispersal in mangroves is usually limited within estuaries and that coastal geomorphology and rare long distance dispersal events could also influence levels of structure. Mangrove communities are composed of phylogenetically unrelated species, each adapted in different ways to the coastal environment where high salinity, diurnal patterns of submergence, wave action, and frequent disturbance create high stress environments,2. MangrIn most trees, it is generally assumed that rates of pollen gene dispersal are greater, and often much greater, than rates of gene flow via seed. However, several lines of evidence suggest that mangrove species are capable of frequent long distance seed dispersal (LDD) on scales of many km that may exceed rates of gene flow via pollen. For example, exceptionally high levels of gene flow have been reported between West Africa and South America at scales > 6,000 km,13. In aAvicennia germinans, Avicenniaceae) and the red mangrove , across the four main estuaries of Panama within a scale up to 300 km along same coastline , whereas R. mangle is characterized by a simultaneous wind (anemophily) and entomophilous pollination, termed ambophilous pollination against the logarithm of the distance, Sp = − bl10km/(1 − FA) where the regression slope, bl10km, is less than 10 km and FA is the average kinship coefficient between individuals belonging to the first distance class . This first distance class included all pairs of neighbors − 2(1/GST mat − 1)/(1/GST mat − 1) . In addition, the same F-statistics based on microsatellite and cpDNA variations were used to test the null hypothesis mseed = mpollen comparing the expected maternal FST predicted from microsatellite variation  vs. the observed maternal FST estimated as GST from actual cpDNA variation. Under this procedure, the null hypothesis is rejected if confidence intervals (± 2SE) of observed and expected values fail to overlap and  and PCR ngrove)  followiotocols ,65,66] w,66 wPCR CGAC-3’), primerER 2.2.3.Click here for fileBayesian genetic assignment of Avicennia germinans (black mangrove) from two Caribbean (Bocas del Toro and Costa Arriba) and two Pacific (Montijo Gulf and San Miguel Gulf) estuaries in Panama based on STRUCTURE ver. 2.2 and GENELAND ver. 2.0.12. The true K for each procedure after simulations is indicated.Click here for fileBayesian genetic assignment of Rhizophora mangle (Red mangrove) from two Caribbean (Bocas del Toro and Costa Arriba) and two Pacific (Montijo Gulf and San Miguel Gulf) estuaries in Panama based on STRUCTURE ver. 2.2, INSTRUCT and GENELAND. 2.0.12. The true K for each procedure after simulations is indicated. In addition, INSTRUCT was used to help to simultaneously infer the selfing rates of this mixed mating species and the demic structure on both sides of the Isthmus.Click here for file


P < 0.011). This pattern is not due to precopulatory mate choice for genetically dissimilar mates (P < 0.600), but instead results from postcopulatory selection for gametes that are genetically dissimilar . The long-term implication is that heterozygosity has slowly increased in calves born throughout the study period, as opposed to the slight decline that was expected. Therefore, this mechanism represents a natural means through which small populations can mitigate the loss of genetic diversity over time.Although small populations are expected to lose genetic diversity through genetic drift and inbreeding, a number of mechanisms exist that could minimize this genetic decline. Examples include mate choice for unrelated mates and fertilization patterns biased toward genetically dissimilar gametes. Both processes have been widely documented, but the long-term implications have received little attention. Here, we combined over 25 years of field data with high-resolution genetic data to assess the long-term impacts of biased fertilization patterns in the endangered North Atlantic right whale. Offspring have higher levels of microsatellite heterozygosity than expected from this gene pool (effect size = 0.326,  Randomly mating closed populations are expected to lose genetic diversity over time through genetic drift and inbreeding Fisher . SpecifiExamples of such mechanisms include both pre- and postcopulatory strategies. Precopulatory strategies  for reducing the loss of genetic diversity typically involve mechanisms to avoid inbreeding, such as natal dispersal , and few data are available regarding the subsequent long-term/evolutionary implications. As a result, future progress in this field will rely on longer term studies of wild populations to identify the long-term implications of these processes in nature  to test hypotheses regarding the impact of mate choice and genetic incompatibility on patterns of reproductive success in this endangered species.Conceptually, it seems likely that the impacts of these processes will become larger as population size decreases. In large populations there will be a large number of mates and gametes to choose from. Thus, most mates or gametes chosen at random will meet the criteria of unrelated, dissimilar, and/or compatible (whichever mechanism[s] is acting in the particular population). However, as population size declines, the number of mates or gametes that meet the criteria will also decline, resulting in mate choice/compatibility having an increasing impact on patterns of reproductive success. Consequently, the ability to detect and study such patterns should be higher for small populations. Here, we use over 25 years of data from the North Atlantic right whale  sib , indicating that both provide reliable means of individualization for this species . Because all subsequent analyses (and interpretation) are based on the paternity assignments, this approach ensures that the results obtained were robust to different strategies of paternity assignment.All subsequent analyses were conducted using each of these data sets  region of all mother–father–offspring triads was also analyzed to aid our assessment of reproductive patterns Gillett . This red, d = (μ1 − μ2)/√[(σ12 + σ22)/2]  precopulatory mate choice for genetically dissimilar (or unrelated) mates; (2) genetic incompatibility based on fetal loss resulting from a breakdown in self-/non–self-recognition; and (3) genetic incompatibility based on heterozygosity.Randomization processes were used to test if individuals show mate choice preferences for genetically dissimilar mates, where relatedness was used as a proxy for genetic similarity. The relatedness of observed mating pairs was calculated using the method of Li et al. , with eaFL), observed offspring should represent those fertilizations where the zygote disproportionately inherited paternal alleles that resulted in a fetal genotype dissimilar from that of the mother. Whereas under the hypothesis of genetic incompatibility based on heterozygosity (AIHET), observed offspring should represent those fertilizations where the zygote disproportionately inherited paternal alleles that differed from the alleles inherited from the mother. Although these two processes of genetic incompatibility have similarities, they result in different predictions for genetic signatures in surviving offspring, as depicted in Figure Each of the two hypotheses of genetic incompatibility results in expectations of how allele inheritance in observed (surviving) offspring should differ from Mendelian expectations. Under the hypothesis of fetal loss based on self-/non–self-recognition . The observed allele inheritance patterns were then compared to expected values to test if alleles were inherited in a pattern consistent with either of the two hypotheses of mate incompatibility. These analyses were conducted using the program STORM.To assess if any observed biases in allele inheritance were due to genome-wide effects or due to a strong signal from one or a few loci, each locus was tested independently for differences between observed and expected allele inheritance patterns, and critical alpha values to delineate statistical significance were adjusted using a Bonferroni correction for multiple tests Hochberg .P-value was estimated based on the number of simulated data sets that had a trend line as high, or higher, than the observed data.To compare observed changes in heterozygosity of microsatellite loci over time with those expected without a bias in fertilization/pregnancy success, the observed mating pairs for each year were kept constant, and one offspring was generated for each based on Mendelian inheritance. This process generated the observed number of offspring for each year, from the assigned parents, but with genetic characteristics based solely on Mendelian inheritance. This process was repeated 1000 times to generate heterozygosity values expected for the offspring in each year of the study. The trend line for observed heterozygosity over time was then compared to that obtained with the simulated data to test if the observed trend is different than expected without biased fertilization/pregnancy patterns. The cervus, with 112 paternities being assigned . Paternity assignments were similar using the 95% criterion in assigned . There wP < 0.011) . This excess of heterozygous offspring does not appear to result from precopulatory mate choice for genetically dissimilar mates because the relatedness of mating pairs was not significantly lower than expected values if mate choice is random with respect to relatedness  . However, offspring did inherit paternal alleles different than those inherited from the mother more often than expected , as predicted by the hypothesis of genetic incompatibility based on heterozygosity  (P < 0.685), or for either biased pattern of allele inheritance (n = 8), and therefore these analyses will be more informative in the future as more such pedigrees become available.At the MHC, offspring did not have significantly higher heterozygosity than expected given the gene pool  . There weritance . Howevereritance . When theritance . HoweverP < 0.05) . In this population, reproductive success is limited to individuals that are particularly heterozygous, which has the long-term effect of maintaining heterozygosity over generations despite an increase in the amount of inbreeding  or biased mortality of zygotes  suggest that both mechanisms are feasible in this species.Lastly, the question remains of how either of the hypothesized mechanisms could maintain genome-wide heterozygosity. Although mechanisms have been identified for maintaining heterozygosity at the specific loci expressed on the surface of sperm and/or at the maternal–fetal interface . It is widely documented that pathogens provide strong selection pressures on the MHC, often in ways that lead to heterozygote advantage, resulting in the ability to recognize and respond to a wider range of pathogens  can result in biased paternity assignment toward males that are particularly more/less heterozygous and more/less related to the mother – depending on the allele frequency distributions –  were our analysis of mate choice, where we tested if mates are particularly genetically dissimilar. If our exclusion-based paternity assignment was biased in the manner suggested, mothers and assigned fathers would be falsely inferred to be related  regardless of which paternity assignments were used. These data indicate that our subsequent analyses are not the result of biases resulting from paternity assignment methods.Second, Wang  showed tgiven the assigned parents. These analyses were based on comparing the observed dissimilarity of maternally and paternally inherited alleles to expected values generated by simulating offspring under Mendelian inheritance from the assigned parents. This approach means that, even if paternity was biased toward heterozygous males, it would not artificially inflate such an analysis. For example, if paternity was biased toward heterozygous males, it would be more likely for offspring to inherit differing maternal and paternal alleles, which would artificially inflate our “expected” values of allele inheritance to which we compared the observed data . Thus, because all analyses are based on assigned parents, they are essentially “standardized,” where the observed and expected data are calculated from the same paternity assignments, and would therefore be similarly affected, which serves to eliminate any potential artifacts that could result from biased paternity assignment.Third, our subsequent analyses were based on assessing allele inheritance patterns lower heterozygosity values. As expected from this figure, there is not a statistically significant difference between the means of these two groups .Lastly, if our primary finding that offspring are more heterozygous than expected from this gene pool is an artifact of biased paternity assignments, then calves with fathers assigned should be more heterozygous than calves without fathers assigned. Figure Combined, these data show that the results and interpretations we have made are not an artifact of biases in paternity assignment methods.


When faced with rapidly changing environments, wildlife species are left to adapt, disperse or disappear. Consequently, there is value in investigating the connectivity of populations of species inhabiting different environments in order to evaluate dispersal as a potential strategy for persistence in the face of climate change. Here, we begin to investigate the processes that shape genetic variation within American pika populations from the northern periphery of their range, the central Coast Mountains of British Columbia, Canada. At these latitudes, pikas inhabit sharp elevation gradients ranging from sea level to 1500 m, providing an excellent system for studying the effects of local environmental conditions on pika population genetic structure and gene flow. We found low levels of neutral genetic variation compared to previous studies from more southerly latitudes, consistent with the relatively recent post-glacial colonization of the study location. Moreover, significant levels of inbreeding and marked genetic structure were detected within and among sites. Although low levels of recent gene flow were revealed among elevations within a transect, potentially admixed individuals and first generation migrants were identified using discriminant analysis of principal components between populations separated by less than five kilometers at the same elevations. There was no evidence for historical population decline, yet there was signal for recent demographic contractions, possibly resulting from environmental stochasticity. Correlative analyses revealed an association between patterns of genetic variation and annual heat-to-moisture ratio, mean annual precipitation, precipitation as snow and mean maximum summer temperature. Changes in climatic regimes forecasted for the region may thus potentially increase the rate of population extirpation by further reducing dispersal between sites. Consequently, American pika may have to rely on local adaptations or phenotypic plasticity in order to survive predicted climate changes, although additional studies are required to investigate the evolutionary potential of this climate change sensitive species. Perhaps one of the largest challenges facing wildlife will be coping with climate change Species that have successfully established populations along a continuous range of elevations may represent ideal systems in which to study the synergistic effects of genetic drift, inbreeding and natural selection on the extent and distribution of genetic variation as environmental conditions (e.g. temperature) change rapidly over short distances Ochotona princeps) is a small lagomorph discontinuously distributed in mountainous areas throughout western North America from central British Columbia (BC) and Alberta, Canada, south to the Sierra Nevada in California and east to New Mexico, USA. Pikas are restricted to talus slopes and broken rock debris in proximity to meadows that provide their food O. princeps to the position of a model mammalian species for studies of metapopulation dynamics, island biogeography and source-sink dynamics The American pika (O. princeps may represent an excellent system in which to study the relative importance of stochastic (genetic drift) versus deterministic  processes in shaping genetic variation within a climate change-sensitive species.Recent studies have examined American pika phylogeography in the context of climate change since the late Pleistocene O. princeps populations found along three elevation gradients in the central Coast Mountains of British Columbia, Canada, ranging from sea level to greater than 1500 m. Specific objectives include: 1) investigating the extent and distribution of genetic variation within and among populations; 2) quantifying gene flow among populations along continuous, altitudinally distributed transects as well as disjunctly among transects; 3) evaluating the degree to which patterns of genetic variation correlate with observed environmental variation, and 4) reconstructing population demographic histories.In the present study, we begin to address these questions by sampling O. princeps from sea level to tree line and the presence of an extensive network of roads connecting the bottom of the valley to higher elevations. In this study area, talus slopes are highly fragmented and scattered throughout the landscape at relatively larger distances from each other . Samples were collected in sites B, C, D and E in 2008, 2009 and 2010, from site A1 in 2008 and 2009, and from sites A2, F, G, H and I in 2010. A total of 288 geo-referenced individual hair snares were set up across these ten sites  and a modified version of the manufacturer's protocol as demonstrated by Henry et al.We previously determined that DNA extracted from 15–20 hairs per sample yielded DNA of sufficient quality and quantity for downstream assays 2, 200 μM dNTPs, 10 µg bovine serum albumin  and 0.5 U AmpliTaq Gold® DNA polymerase (Applied Biosystems). All forward primers were 5′-tailed with an M13 sequence [5′-TCCCAGTCACGACGT -3′] to facilitate automated genotyping. Specifically, the M13-tailed forward primer was used in combination with an M13 primer of the same sequence 5′-labeled with one of four fluorescent dyes . Two people (Philippe Henry and Zijian Sim) called alleles independently and incongruent calls were repeated from the PCR stage.Cycling parameters were optimised using a touchdown cycling program  using PO, HEH) and the number of alleles (aN) calculated in Arlequin 3.5.1.2 RA) based on a rarefaction index accounting for differences in sample sizes as implemented in Fstat 2.94 ISF) was also calculated for each site and its deviation from zero was assessed using 100,000 permutations between loci using Fstat 2.94 Within population genetic variation was quantified using observed and expected heterozygosity . This method makes use of gametic disequilibrium information in a Bayesian inferential framework to estimate recent (last two generations) migration rates from one population into another. This approach has one major assumption, namely that the loci used are in linkage equilibrium, but it does not require that populations are in HWE.To estimate rates and direction of recent migration events between each sample site, we used the Bayesian method implemented in BstF and the environmental variables using mantel.rtest function of the R package ade4 stF) with population geographical isolation climateBC 3.1 climateBC. In order to remove redundant information from this large number of variables, we performed a principal component analysis (PCA) and calculated correlation coefficients between each pair of variables using the R packages ade4TkGUI cmdret al.a priori do not affect the species) were removed from further analyses.To test for associations between local environmental conditions and observed population genetic structure, we conducted Mantel tests to characterize the association between pairwise stF values and relates them to environmental variables of interest as implemented in Geste 2 7 (128) models. The method evaluates the posterior probabilities of each factor and their combinations in shaping the observed population genetic structure using reversible jump Markov chain Monte Carlo (MCMC). For example, the model that compares only genetic differentiation and geographic isolation can be viewed as a null model for isolation by distance, while other models can incorporate more complex scenarios. We followed the approach of Gaggiotti et al.este using all seven factors and then performed a second round of analyses using the three factors with the highest cumulative posterior probabilities from the first round of analyses.Additionally, we applied a hierarchical Bayesian method that estimates local ottleneck 1.2.02 M-ratio test using M_p_val.exe and critical_M.exeet al.M-ratio test, we used a TPM mutation model with 10% multi-state change, assuming a marker mutation rate μ of 5×10−4 and a pre-bottleneck eN ranging from 500 to 12,500 resulting in a value of θ (4 eN μ) ranging from 1 to 25 and 3.5 bases steps for multi-step mutations. We used both approaches since the heterozygosity excess and mode shift test have been suggested to reflect recent demographic contractions while M-ratio reflect historical contractions Genetic signatures of demographic contraction were assessed within each site using three different approaches: 1) the heterozygote excess test and 2) the mode-shift test, both implemented in the software package BOcp13) to 7.7% (Ocp12).Of the 28 microsatellite loci screened, six markers failed to amplify and 12 markers were monomorphic . Ten mar−6. Of the 206 hair samples genotyped, 38 pairs harbored identical multi-locus genotypes. We removed one sample from each pair, resulting in a final dataset containing 168 individuals. The mean number of individuals sampled per site was 16.2, ranging from 5 (H) to 32 (D) (The multi-locus probably of identity for this suite of ten microsatellite loci was 8.3×10o 32 (D) .HWE) in at least one of the ten sampled sites  occurred between four pairs of loci, yet this significant linkage was never observed at all sites (Ocp12/Ocp23) occurred in five of 10 sites  or two sites , H (Ocp22 and Ocp 7) and I  while all other sites were polymorphic at all ten loci (B to 0.28 in site I (rA of 2.95 (SD =0.66) with values ranging from 3.7 in site D to 1.7 in site I. Within-site inbreeding coefficients (isF) were always positive and differed significantly from zero in all instances except one . This value is substantially lower than those reported in previous studies of O. princeps from Montana, California and Nevada 0.65, SD =0.14 O. collarisO. curzoniae sampled from the Qinghai-Xizang plateau, China rA =3.3; SD =0.33) was also lower than that found in O. princeps populations in Nevada, USA [rA =4.8; SD =0.99; The amount of genetic variation found in the A2-H, A2-I, H-I). While average stF values for most sites were centred around 0.20 (0.17 – 0.26), the high elevation site from the Bentinck transect (I) displayed an unusually high stF value of 0.36  yielded results that were mostly consistent with observed patterns of population differentiation, in that mean migration rates were low in all cases, , followed by heat to moisture ratio , precipitation as snow , mean annual precipitation  and summer mean maximum temperatures . All other variables were not significantly correlated with genetic differentiation. Additionally, Bayesian model testing using all seven factors identified mean maximum summer temperature as the variable with the highest cumulative probability (Pr=0.5) in explaining the observed population genetic structure, followed by geographic isolation (Pr=0.497) and mean minimum winter temperature (Pr=0.493). The model with the highest probability (Pr=0.01) contained all three variables listed above. The second round of MCMC containing only these three factors identified that the model with the highest posterior probability contained a constant term (a0=−2.13) and mean maximum summer temperature only (Pr=0.134). This latter model resulted in a positive regression coefficient (1a=0.205), suggesting that genetic differentiation increases with increasing temperature. Yet, a high proportion of the variance remains unexplained by this model as illustrated by a large value of model fit coefficient (2σ=1.13), indicating that Geste failed to detect the true model The results of the Mantel tests indicated that geographical isolation is the environmental variable that correlates most strongly with genetic differentiation  also displayed shifted allele frequency distributions, another indication of recent demographic contraction. These results were not affected when loci that deviated from HWE expectations were excluded from the analyses.Signatures of recent demographic contraction were evidenced in half the sites as they displayed a significant excess heterozygosity relative to the number of alleles expected at mutation-drift equilibrium . Four ofM-ratios were always larger than the critical M value simulated for a stable population with the same number of individuals and loci used here, suggesting historically stable populations. The outcome of the M-ratio tests remained unchanged when θ was varied from 1 to 25.Conversely, the In the present study, we used a noninvasive sampling approach that enabled us to effectively collect population-level samples of the American pika. Following appropriate quality control, our final microsatellite dataset presented a 0.35% error rate corresponding to 0.2% allele dropout  and 0.15% of false alleles , values that are towards the low end of reported genotyping errors for high quality starting material such as plucked hair HWE at several loci in some of our sites are most likely biologically meaningful, associated with pika life history rather than by genotyping errors O. princeps populations are usually small  O. princeps populations from the centre of their range, where other studies did not find evidence of inbreeding HWE are the potential for overlapping generations, post-glacial colonization, limited dispersal capacities (see below) and metapopulation structure. Regarding the latter, we directly observed the impacts of environmental stochasticity over the course of this study, as illustrated by the potential extirpation of one of the high elevation sites on the Hill transect (A1) due to a 2010 forest fire that was subsequently re-occupied in 2011. Further research would be required, however, in order to definitively determine whether pikas observed at A1 in 2011 were the result of re-emergence or recolonization from a neighbouring source population that was not sampled in the current study.Given the extent of quality control used in our study, the observed deviations from O. princeps populations may be a result of a more recent post-glacial expansion from southerly refugia compared to core populations in the USA The low level of genetic variation recovered in our samples may be explained by one or a combination of the following: 1) relatively small population sizes; 2) measurable levels of inbreeding; and 3) location of the Bella Coola Valley at the northwestern tip of the American pika distribution. Based on this latter consideration, lower levels of genetic variation observed in Bella Coola Valley A2, H, I; n<10). As the stF values for these sites were still very high, and in the case of site I, the highest observed in our samples, it is quite likely that the lack of significance for these comparisons is an artefact of small sample sizes. Consequently, each sampled site likely represents an independent unit characterized by a unique allele frequency distribution. Yet, it has been suggested that pikas are able to disperse to neighbouring talus patches located up to three kilometres apart B – C:1.3 km, C – D:2 km, D – E:2 km), as well as between sites C and E separated by five kilometres. It is noteworthy that site A1 and A2, although separated by less than a kilometre did not display evidence for any exchange of migrants, which is most likely due to the local topography that contains a deep valley crossed by a torrent, thus producing an effective barrier to dispersal. Estimates of migration rates corroborated this finding, although the fact that this approach relies on an island model of population structure may bias estimates of gene flow downwards The marked population genetic structure revealed in this system is not surprising given the life history characteristics of pikas . All sites displayed significant differentiation except for the pairwise comparisons of the three sites that contained the fewest samples  between sample sites.(XLS)Click here for additional data file.Table S2Information on the microsatellite loci tested in the present study including locus name, Genbank numbers, length (for successful amplification) and PCR program (for loci retained in the present study), the dye and multiload used. Loci with a single fragment length were monomorphic in our samples.(XLS)Click here for additional data file.Table S3Tests of Hardy Weinberg equilibrium (HWE) within each site for each loci used. Black boxes indicate significant deviation from HWE per locus per site after corrections for multiple comparisons.(XLS)Click here for additional data file.Table S4Test of linkage disequilibrium for each pair of loci calculated within sites. Combined p-values are given below the diagonal, and sites at which the two loci were linked are given above the diagonal.(XLS)Click here for additional data file.Table S5Observed (oH) and expected (eH) heterozygosities for each locus and each site.(XLS)Click here for additional data file.Table S6Mean estimates of the distribution of recent migration rates (m) ayesass+ calculated using B, given as the proportion of migrant individuals per population per generations.(XLS)Click here for additional data file.Table S7Results of the tests of demographic history for each site.(XLS)Click here for additional data file.


Visual imagery has been closely linked to brain mechanisms involved in perception. Can visual imagery, like visual perception, improve by means of training? Previous research has demonstrated that people can reliably evaluate the vividness of single episodes of imagination – might the metacognition of imagery also improve over the course of training? We had participants imagine colored Gabor patterns for an hour a day, over the course of five consecutive days, and again 2 weeks after training. Participants rated the subjective vividness and effort of their mental imagery on each trial. The influence of imagery on subsequent binocular rivalry dominance was taken as our measure of imagery strength. We found no overall effect of training on imagery strength. Training did, however, improve participant’s metacognition of imagery. Trial-by-trial ratings of vividness gained predictive power on subsequent rivalry dominance as a function of training. These data suggest that, while imagery strength might be immune to training in the current context, people’s metacognitive understanding of mental imagery can improve with practice. Mental imagery can be described as the retrieval of perceptual information from memory, and the subsequent examination of this information in the “minds eye.” Research has provided a growing body of behavioral and neuroimaging evidence that there is considerable overlap between the “minds eye” and actual perception  participated in the experiment. All had normal or corrected-to-normal visual acuity and normal stereovision, and all provided written informed consent. Observers received payment for their participation  with the exception of a participating author (RR) and participant BW. The study was carried out with the approval of the Institutional Review Board at Vanderbilt University.Observers viewed the stimuli on a luminance-calibrated CRT monitor with 1152 × 870 resolution and a 75-Hz refresh rate in an otherwise darkened room. Visual stimuli were generated with Matlab 7.5.0 (R2007b) and the Psychophysics toolbox  that faded to black at the stimulus edge (Gaussian σ = 4.29°). Five observers were trained with a green grating of orientation 112.5° and a red grating of orientation 22.5°, while on generalization blocks they were presented with 67.5° green, and 157.5° red gratings. The opposite was true for the remaining four observers, meaning that we counterbalanced which grating-pairs were used for training and generalization between participants. On catch trials, a mock rivalry stimulus was presented consisting of a physical blend of the green and red rivalry patterns. This stimulus was presented to both eyes simultaneously in order to avoid interocular competition. Presentation of the mock-stimulus allowed us to test for decisional bias and demand characteristics  surrounding a central fixation point, presented against a black background with a mean luminance of 0.09 cd/mThe dominant eye plays a key role in determining which of two monocular images is likely to be perceived at the onset of binocular rivalry. Therefore, individual fine-tuning of stimulus contrast was done before the start of the experiment, and before each daily session, to control for differences in ocular dominance between observers. We used the same procedure as in previous research , after which they were cued by the word “effort?” to report the amount of vigor with which they had tried to imagine the pattern . Observers were instructed to use the full range of the rating scale to the best of their abilities.During the experiment, participants were briefly presented with a randomly chosen  central cue  at the beginning of each imagery-trial Figure A. Subseqgreen, 2 = mixed, 3 = red). For this response, the right hand was used in order to minimize potential response conflict between the two hands. A “mixed” response could be made on all trials . On rivalry trials, the observer could give a mixed response in case he or she was unable to distinguish which grating had appeared more dominant due to binocular combination or piecemeal rivalry. This type of mixed percept was reported on 6.49% of rivalry trials (SEM = 2.49%).As soon as a participant had responded to both questions, a rivalry display  or a mock display  was presented for 750 ms. On rivalry trials, the green grating was presented to the left eye, and the red grating to the right eye. On mock trials, the plaid-stimulus was presented to both eyes simultaneously. Participants reported which image had appeared most dominant, by pressing one of three buttons  of imagery on rivalry. This was calculated as the percentage of trials in which the imagined grating matched subsequent perception during rivalry  were analyzed by constructing type II receiver operating characteristic (ROC) curves for each participant on each day of training. This method of assessing metacognitive ability is derived from signal detection methods Swets,  and has Since it is not possible to be “correct” or “incorrect” about an internally generated image, we adapted the definition of the type II decision to include judgments about the vividness of single episodes of mental imagery and its effect on the perceptual outcome during brief instances of subsequent binocular rivalry. Applying the signal detection logic, we categorized trials where participants reported high vividness and where imagery subsequently biased perception as “hits.” Trials where participants reported high vividness but perception was not subsequently biased were categorized as “false alarms.” Here, the ROC II characterizes the probability of a participant being perceptually biased during rivalry, given a certain level of self-reported vividness.p and p for all i, and transformed these into cumulative probabilities before plotting them against each other . Distribution-free methods were employed to characterize type II ROC sensitivity by calculating the area under the ROC curve (Aroc), and type II ROC bias (Broc). These parameters are derived from simple geometry and do not make assumptions about the shape of the distribution  quantifies the extent to which metacognitive judgments are predictive of perceptual bias during rivalry . DistBroc) was defined as the ratio KB/KA, where KB is the area between the ROC curve and the major diagonal  and effort data (mean R2 = 0.981 ± 0.007).Where F < 1].Sustained mental imagery can bias the perception of an ambiguous display, resulting in a reliable measure of imagery strength on a trial-to-trial basis  = 8.861; p = 0.018] which is consistent with previous work demonstrating the effect of mental imagery on rivalry  < 1]. Analyzing the data by session did not unveil any hidden differences in perceptual bias over time , which excludes the possibility that most learning took place between the first couple of sessions.Mental imagery did bias perception in favor of the imagined grating . Self-reports of exerted effort did not change over the course of training either [F < 1]. In summary, neither the perceptual measure of imagery strength  nor ratings of vividness showed any significant change over the 5-days of training. Thus, it appears that training in this study was unable to increase imagery strength over time.Additional evidence that mental imagery was not improved by training comes from participant’s introspective judgments of imagery vividness. Mean self-reported vividness of mental imagery was statistically the same on all days of training  and untrained  orientation . Trained and untrained orientations do not statistically differ [F < 1]. This lack of orientation specificity may not be surprising considering that metacognition for perception is something presumably supported by higher-level frontal areas of the brain  = 3.075; p = 0.019]. This trend is linear when only looking at training days 1–5  but becomes quadratic when follow-up is included , indicating a drop of the proportion Aroc at follow-up. Nevertheless, planned comparisons (uncorrected t-tests) show that – with the exception of day 1 – the predictive value of self-reported vividness on the perceptual outcome is larger than would be expected by chance , and this ability is still present 2–3 weeks after training (p = 0.021).The information from Figure F = 2.83; p = 0.074]. However, a lack of observed power (0.558) indicates that at this sample size there is only a small (44%) chance of finding a significant effect (at α = 0.05) when assuming that people have metacognitive insights into their own imagery strength at the population level. An a priori power analysis indicates that, assuming a medium effect size, 21 subjects would be required to obtain a power of 0.95.In previous work we demonstrated that people can reliably evaluate the vividness of their mental imagery from one trial to the next  < 1]. The area under the ROC II curve (Aroc), which quantifies the degree to which self-reported effort predicts perceptual bias during rivalry, did not differ from chance on any of the training days . Neither did we observe a change over time for the trained [F < 1], untrained  , or collapsed [F < 1] grating orientations.Vividness ratings are predictive of the efficacy that mental imagery has at biasing the perception of rivaling stimuli. By contrast, self-reported effort for imagery was not hypothesized to predict perceptual bias. Attempts to exert greater effort do not necessarily result in highly effective imagery, as demonstrated by previous work . In other words, subjective vividness – but not effort – is predictive of how well something was imagined independent of rating-magnitude. Signal detection theory considers metacognitive ability (sensitivity) and rating-magnitude (bias) as two independent properties  and participant’s mean vividness ratings were not correlated .Vividness appears to predict perceptual bias more strongly over the course of training, whereas effort does not predict perceptual bias at all. Can this finding be explained by the way participants used the rating scales? Participant’s average reported vividness (2.57 ± 0.21) and effort (2.86 ± 0.14) did not significantly differ (Broc) provides us with a distribution-free estimate of the criterion used by participants to provide their subjective ratings. A neutral bias would give Broc equal to zero, while a negative or positive Broc indicates a bias toward lower or higher ratings respectively. This estimate corresponded very well with the actual rating-magnitude collected during the experiment: self-reported vividness ratings and estimated vividness bias (Broc vividness) were highly correlated , as were self-reported effort and estimated effort bias . The close resemblance between these two variables – both measures of participant’s criterion – helps validate the distribution-free approach used to determine ROC estimates in the current paradigm.The type II bias of the ROC curve (Aroc = 0.48–0.71). This type of variability is not uncommon, and previous studies have reported similarly large individual differences in metacognitive ability for perceptual tasks . This suggests that participant’s metacognitive ability in this task is independent of imagery strength, as measured by binocular rivalry.Strikingly, Figure The research presented here suggests that mental imagery strength does not improve over the course of our 5-day training regime. Over the 5-days, no changes were observed relating to imagery strength as measured by rivalry, nor were there any changes in the average introspective judgments of imagery vividness. We further demonstrated that self-reported vividness of mental imagery predicts the perceptual consequences of single epochs of imagery. More importantly, this prediction becomes stronger with practice, implying increased metacognition of imagery over the course of training. Self-reported effort of mental imagery on the other hand, did not predict perceptual outcomes.There have been reports of visual imagery increasing performance on subsequent perceptual tasks (Tartaglia et al., The idea that training cannot easily change imagery strength might be explained by the manner in which imagery strength is linked to brain anatomy. The Tartaglia study (Tartaglia et al., Historically, mental imagery has been considered a fainter form of perception Hume, . EvidencOne could hypothesize that imagery strength is liable to improvement, but we simply failed to find any in this study due to the configuration of our task. Research into the process of improving perceptual skill – or perceptual learning – provides useful context in support of this hypothesis. One influential view known as the reverse hierarchy theory (Ahissar and Hochstein, In light of the reverse hierarchy framework, our training regime is suspect to a critical vulnerability. Namely: training duration. Five days may have been insufficient time to reach the asymptotic learning phase. The Tartaglia study previously mentioned (Tartaglia et al., Recent research has demonstrated that perceptual learning can also occur without a specific task and outside of awareness, as long as the information of interest is paired with feedback or a reward signal (Seitz and Watanabe, During memory consolidation, initially fragile memory traces become stabilized due to practice-induced plasticity in task relevant brain areas Karni, . Can theCan people become better at knowing their own thoughts? We were able to improve subject’s ability to judge the vividness of their imagery. This improvement was still present during a follow-up test, implying a long lasting effect of training on metacognitive evaluation of mental imagery. Furthermore, training of metacognition was not orientation specific: metacognition was improved for both trained and untrained sets of orientations. It is likely that the improvement of metacognition reported here originates from higher-level brain areas. This is in concordance with the suspected high-level neural locus of metacognitive ability for perception (Kepecs et al., Our study demonstrated improvements of the metacognition of imagery, whereas no changes in imagery strength itself were observed. This dissociation suggests distinct brain mechanisms underlying metacognition and visual imagery respectively. Similar distinctions have been made regarding metacognition of perception: Neuroanatomical substrates of introspective ability are distinct from those supporting primary perception (Fleming et al., The ability to introspect on private thoughts is key to human subjective experience. Yet, people’s ability to evaluate internally generated experiences – such as imagery – is not as self-evident as it may appear. Although a large number of studies now demonstrate that something as private as a mental image can be successfully studied from a third-person perspective (Ishai and Sagi, Introspective or “metacognitive” sensitivity is important to guide actions and to make decisions Vickers,  and beinIn conclusion, we discussed a variety of reasons why training did not lead to an improvement of imagery strength in the current study. Such an improvement may simply be very difficult to document, or our task may not have been optimally suited to detect improvements of imagery strength. Nevertheless, we demonstrated that people’s ability to introspect their own imagery strength does improve with training, which suggests distinct mechanisms underlying imagery and metacognition. Being able to improve metacognition by means of practice can have important implications for real-life situations. It would be interesting to know if training metacognition could help people improve certain cognitive functions, such as decision-making or planning actions. If so, this may prove especially helpful for specific patient populations. Finally, future investigations of prolonged training of imagery can prove advantageous in outlining the overlap between mechanisms of perception and imagery. Imagery as defined here is a highly voluntary process that allows introspection in the absence of direct perceptual input. As such, imagery can provide a unique gateway to understanding how perceptual and introspective processes are represented in the brain.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Arum maculatum (Araceae) and its specific psychodid (Diptera) visitors Psychoda phalaenoides and Psycha grisescens. Because the interaction is asymmetric , we expect the genetic structure of the plant to be related with the historical pollinator availability, yielding incongruent phylogeographic patterns between the interacting organisms.In specific and obligate interactions the nature and abundance of a given species can have important effects on the survival and population dynamics of associated organisms. In a phylogeographic framework, we therefore expect that the fates of organisms interacting specifically are also tightly interrelated. Here we investigate such a scenario by analyzing the genetic structures of species interacting in an obligate plant-insect pollination lure-and-trap antagonism, involving Using insect mtDNA sequences and plant AFLP genome fingerprinting, we inferred the large-scale phylogeographies of each species and the distribution of genetic diversities throughout the sampled range, and evaluated the congruence in their respective genetic structures using hierarchical analyses of molecular variances (AMOVA). Because the composition of pollinator species varies in Europe, we also examined its association with the spatial genetic structure of the plant.Our findings indicate that while the plant presents a spatially well-defined genetic structure, this is not the case in the insects. Patterns of genetic diversities also show dissimilar distributions among the three interacting species. Phylogeographic histories of the plant and its pollinating insects are thus not congruent, a result that would indicate that plant and insect lineages do not share the same glacial and postglacial histories. However, the genetic structure of the plant can, at least partially, be explained by the type of pollinators available at a regional scale. Differences in life-history traits of available pollinators might therefore have influenced the genetic structure of the plant, the dependent organism, in this antagonistic interaction. Experimental studies have furthermore demonstrated that these plants fully rely on insect-vectored cross-pollination for seed production A. maculatum is strictly European , two phylogeographic scenarios can be formulated: (i) the genetic structure of the plant is constrained by the presence of its pollinator but not the opposite, a situation that would yield incongruent phylogeographic patterns between the plant and its pollinators ; (ii) despite the strong asymmetry in the ecological benefits received by the interacting species, the plant closely follows the pollinators' dispersal during expansion and retraction of available habitats, yielding congruent phylogeographic patterns.Due to the asymmetric nature of the interaction . Further amplification of ligated fragments was performed with two primer pairs (E-ACG/M-CTG and E-AGT/M-CAG). For digestion, 5 µl of DNA were added to get a final volume of 20 µl, containing 1× Buffer 2, 0.1 mg ml−1 BSA and 1 unit µl−1 of MseI and EcoRI ; the mix was incubated at 37°C for 2.00 h. Adaptors were ligated to the digested products at 37°C for 2.00 h, using 40 µl of a mix containing 1× Buffer T4, 0.45 µM adaptor E, 0.36 µM adaptor M, 0.015 units µl−1 T4 ligase  and 20 µl of digestion product. Pre-selective PCR was done in a 20 µl mix composed of 1× buffer GoTaq , 2 µM MgCl2, 250 µM dNTPs , 0.25 µM primers EA and MC, 0.025 units µl−1Taq-polymerase  and 2 µl ligated DNA. Conditions for this procedure were 2 min at 94°C, followed by 29 cycles of 45 sec at 94°C, 45 sec at 56°C and 1 min at 72°C, and finishing with 10 min final extension at 72°C. The final selective step was done in a 20 µl mix composed of 1× buffer GoTaq , 2 µM MgCl2, 250 µM dNTPs , 0.4 µM primers EAxx and MCxx, 0.025 units µl−1Taq-polymerase  and 3 µl of a 1/20 solution of the pre-selective PCR product. Selective PCR procedure was 2 min at 94°C, followed by 13 cycles of 30 sec at 94°C, 30 sec at 65°C (with temperature decreasing 0.7°C at each cycle) and 1 min at 72°C, followed by 23 cycles of 30 sec at 94°C, 30 sec at 65°C and 1 min at 72°C, followed by a final extension of 5 min at 72°C. AFLP profiles were genotyped by Macrogen Inc. (South Korea). Allele binning was first automatically processed using Genemapper 3.7 (Applied Biosystems) by applying a threshold of 50 RFU between 50 bp and 350 bp. Bins were then visually checked and adjusted when necessary. Because digestion and amplification problems can arise during the procedure and can highly bias results DNA was extracted using the QIAGEN DNeasy Plant extraction kit, following the manufacturer's protocol . Because plastid markers in plants are not as variable as in animals Arum maculatum were calculated for samples having successfully amplified fragments with both AFLP primer pairs, applying a geographic moving window run on R 9.2.1 et al.Nei genetic diversities A. maculatum, 20 runs of 1,000,000 generations with a 200,000 burn-in period for each prior K number of populations (set between 1 and 20) were performed using a model-based assignment algorithm as implemented in Structure 2.2 K number of clusters, individual assignment probabilities that optimize Hardy-Weinberg equilibrium at the intra- and inter-cluster levels. Following recommendations of the authors K was identified using the approach proposed by Pritchard et al.K-means method, following Hartigan and Wong i.e., the average of the distances between the centroid of each cluster and each sample contained in it), following Kergoat & Alvarez et al.et al.K cluster, for values ranging from 1 to 20. Scripts are available upon request to the first author.Several methods currently exist for identifying the genetic structure of a molecular dataset P. phalaenoides (105 samples) and P. grisescens (47 samples) was extracted using the QIAGEN DNeasy Blood and Tissue extraction kit . Psychodids were sampled when trapped in Arum flower chambers and were usually covered by pollen. This precluded performing whole genome fingerprinting analyses (such as AFLP) based on total DNA (which has been contaminated with plant DNA from the pollen). Instead, we performed insect-specific single-gene amplification to infer phylogeographic patterns in the insects. We used three mitochondrial regions (hereafter mtDNA), i.e., Cytochrome b (Cytb), Cytochrome Oxidase subunit I (COI) and small ribosomal RNA sub-unit (16 s) for P. phalaenoides and one, Cytb, for P. grisescens. The difference in the number of amplified regions was due to problems encountered during amplification and sequencing in the second fly species, and could not be overcome despite trials under several PCR and mix conditions. PCRs were done in 20 µl of a mix composed of 0.5× buffer, between 1.25 and 2.5 mM MgCl2, 10 mM dNTP, 1 unit of GoTaq DNA polymerase , 0.5 µM primers (DNA from 152 flies (see below) belonging to the two visiting species  primers  and 3 µl primers , 1 min aPhylogenetic relationships were inferred using Bayesian and Maximum Likelihood (ML) approaches. Models of evolution were estimated using MrAIC v. 1.4.4 Nucleotide diversities were calculated based on Nei genetic diversities using the same procedure as described above for the plant. The same script was used for the two insect species, defining a cell-size of 75 km and a perimeter of 300 km.Dset function implemented in PAUP* 4.0 P. phalaenoides, distances were calculated for each partition and afterwards averaged. Geographic distances between samples were calculated and log transformed using GenAlex 6.Individual-based isolation by distance was investigated with a Mantel test using GenAlex 6 A. maculatum  converge in their aim to detect patterns of spatial genetic structure. Comparing their resulting phylogeographic patterns is thus conceptually correct and in agreement with the goals of this study. Spatial genetic structures for the plant and its associated psychodids were displayed on geographical maps using ArcMap 9.3 , with populations represented as pie charts showing the number of individuals assigned to each cluster or haplotype.The two different methods used to produce molecular data in pychodids and Congruence between the genetic structure of plants and insects was evaluated in two different ways. First, it was addressed qualitatively on visual grounds and considered to be supported if the spatial distribution and the number of genetic clusters were roughly similar for both the plant and the insects.P. phalaenoides and P. grisescens have been respectively observed to be the main visitors Dset option (see above) for insects. This approach was preferred to other methods because: i) precise dating is impossible in the group due to a lack of fossil data and thus temporal divergence estimations , while 47 P. grisescens amplified at one region (679 bp)  .P. phalaenoides and P. grisescens represent well-defined specific entities  that do not hybridize.Both phylogenetic topologies  and haplP. phalaenoides .When testing individual-based isolation by distance , resultsA. maculatum and each of the two psychodids presented no visual congruence: neither the number nor the distribution of genetic groups was similar between the interacting species. While the plant showed a trend towards a geographically-driven structure of its genetic variation  were, however, higher than both ΦSC (0.158) and ΦCT (0.03) values. While 81% of the variation was explained at the intra-population level, only 16% and 3% were found at the inter-population and among-groups levels, respectively.The hierarchical AMOVA performed on the plant dataset showed that the pollinator compositions provided significant values of Φ-statistics at all levels . ΦST vali.e., ΦST, ΦSC and ΦCT), using both model- (K = 2) or non model- (K = 6) based plant scenarios [see above and For flies, no structure was identified at any of the three tested levels  with the non model-based approach is also consistent with climatologic records from the Last Glacial Maximum . During this period, lowered sea levels in the northern Adriatic resulted in land bridges that enabled communication between the eastern and western coasts of the Adriatic Our results show that tructure , with potructure  or two  seems to have little spatial structure. However, because the model-based approach did not identify these groups, it is difficult to conclude whether or not the admixed pattern at the central and northern part of the European distribution area is an artefact. The K-means approach aims to minimize among-sample distances, a principle that can lead to over-split results: the more clusters are parameterized, the smaller the distances between the centroid of each cluster and each included sample becomes, leading to a bias similar to that of overfitted correlations. Following this hypothesis, the multiple central-European clusters identified would be more likely an indication of the difficulty to define a best K using non model-based approaches than a biological reality. This might be supported by the fact that analyses of pairwise Nei genetic distances between the six clusters (data not shown) indicated that those belonging to the Balkans/Italy and the Carpathians presented higher genetic distances to all other clusters, while the pairwise distances among the remaining four were lower.It is worth noting that a large part of the genetic variation identified by the non model-based approach , it is likely that substitution rates per year are high (see below). Although it is empirically difficult to quantify dispersal by a direct approach in these species, P. phalaenoides was recently sampled in aerial netting surveys in England where insects were collected at around 200 m above ground; a height at which any insect found is considered to be engaged in migratory –and thus potentially large-scale– movement Ips typographus (Coleoptera: Scolytidae) at a regional scale in Switzerland Despite the fact that the markers used allowed the identification of a high level of genetic variability in psychodids , P. grisescens shows low diversity levels at its northern colonization edge, a pattern likely to be associated with lower dispersal capacities. Differences in the spatial distribution of diversity centres in both species might also indicate that these two psychodids have contrasting ecological niches, which could cause differences in local fitness, directly impacting population sizes and the output of drift. Differences in ecological niches –notably those related to low temperature tolerance and humidity– could moreover also explain that while P. phalaenoides is able to disperse to higher latitudes, P. grisescens is more restricted to southern, drier and warmer European zones. This point might be addressed in the future by performing ecological niche modelling for the two taxa.Despite both species demonstrate similar numbers of haplotypes at the continental scale, the nucleotide diversity analysis showed that zones of high diversity were distributed differently in the two species. While rn areas , Psycha ern area . This reArum maculatum and its associated psychodids indicates that there is no congruence among the phylogeographies of the three species. Not finding any evidence of shared spatial genetic structure . However, the maintenance of the interaction and the survival of the dependent plant species , requires that at least one refugium is shared between A. maculatum and its associated psychodids. Similarly, the interaction can persist despite differences in recolonization routes, as long as the independent species are frequent enough to allow the dependent species to survive in locations where suitable abiotic and biotic factors overlap. This appears to be a reasonable hypothesis if we consider that these insects are abundant and widespread in Europe It is worth noting that et al.i.e., evidence of spatial genetic structure in one interacting species and absence in the other) could be retrieved when the two interacting species disperse at very different rates. This could be the case in the interaction studied here as well, since it is known that psychodid flies can reach enormous population sizes  is thus rather at the lower margin of the results found for the Yucca-Yucca moth interaction. Still, one should keep in mind that since the A. maculatum - psychodid interaction is antagonistic, in contrast to the mutualistic Yucca - Yucca moth interaction, results from this and our study are hardly comparable. Our AMOVA results should thus be considered as an innovative first examination of the ecological factors explaining the respective genetic structure of antagonistic organisms. They particularly show that pollinators have and/or have had some effect on the phylogeographic history of the plant. If the correlation proposed by our AMOVA is causal, it would indicate that the spatial genetic structure of A. maculatum is being shaped by the variation in the biological characteristics  of psychodid pollinators. This relates to one of the principles of the geographic mosaic theory of coevolution P. grisescens seems more restricted to a narrowly defined region, and thus appears as a less mobile or more ecologically selective species than P. phalaenoides, a result that is paralleled by the diversity analyses  can be explained by the spatial visitation pattern of the most frequently lured pollinator, indicating a possible role played by some of the ecological characteristics of the independent partners in shaping the phylogeography of its dependent associated species.In this study we show that, according to one of our working hypotheses, the phylogeographies of specific antagonists are incongruent. Reasons for such a pattern may be explained by the asymmetric ecological dependence between the interacting organisms. Our results however suggest that a part of the genetic structure of the dependent organism Click here for additional data file.Figure S2Phylogeny of the two Psychodid species inferred applying Bayesian and Maximum Likelihood approaches. Support values are shown on branches, Bayesian/Maximum Likelihood.(DOC)Click here for additional data file.Figure S3Isolation by distance for A) Psychoda phalaenoides and B) Psycha grisescens represented by the correlation between log geographic distances and genetic distances. Regression lines are shown. R2 are 0.002 and 0.006 for P. phalaenoides and P. grisescens, respectively, with P values>0.05 in both cases.(DOC)Click here for additional data file.Table S1Sampled locations with geographic coordinates. Number of plants, Psychoda phalaenoides and Psycha grisescens analyzed at each sampled location are given. Assignments to groups for the AMOVA tests are indicated under “group AMOVA”.(DOC)Click here for additional data file.Table S2GenBank accession numbers and TreeBase link to data  of sequences used in this work.(DOC)Click here for additional data file.