Batrachochytrium dendrobatidis (Bd) has caused variable population declines in the lowland leopard frog (Lithobates yavapaiensis); thus, disease has potentially shaped, or been shaped by, host genetic diversity. Environmental factors can also influence both amphibian immunity and Bd virulence, confounding our ability to assess the genetic effects on disease dynamics. Here, we used genetics, pathogen dynamics, and environmental data to characterize L. yavapaiensis populations, estimate migration, and determine relative contributions of genetic and environmental factors in predicting Bd dynamics. We found that the two uninfected populations belonged to a single genetic deme, whereas each infected population was genetically unique. We detected an outlier locus that deviated from neutral expectations and was significantly correlated with mortality within populations. Across populations, only environmental variables predicted infection intensity, whereas environment and genetics predicted infection prevalence, and genetic diversity alone predicted mortality. At one locality with geothermally elevated water temperatures, migration estimates revealed source–sink dynamics that have likely prevented local adaptation. We conclude that integrating genetic and environmental variation among populations provides a better understanding of Bd spatial epidemiology, generating more effective conservation management strategies for mitigating amphibian declines.A central question in evolutionary biology is how interactions between organisms and the environment shape genetic differentiation. The pathogen  Infectious diseases are potent agents of natural selection Darwin  that impBatrachochytrium dendrobatidis (Bd) that has caused population declines or extinction in hundreds of amphibian species worldwide  per swab , and (iii) Bd mortality prevalence (the proportion of encountered frogs found dead or dying with visible signs of chytridiomycosis and a positive Bd qPCR test)  is a series of small interconnected pools heated by geothermal activity that are constantly at >30°C, (ii) the Secret Spring (MRSS) is a pond fed by another geothermal spring that is >30°C at the source but below 30°C elsewhere, and (iii) Bass Canyon (MRBC) is a nearby canyon stream that is not fed by a thermal spring  represented in our sample, allowing for admixture and assuming uncorrelated gene frequencies. We ran 20 independent runs for each value of K, each with 3 000 000 Markov chain Monte Carlo (MCMC) iterations after a burn-in of 1 000 000 iterations; we assessed convergence by examining summary statistics , inbreeding (FIS), allelic richness (AR), and to test for deviations from Hardy–Weinberg equilibrium (HWE) at each locus and population locality using MCMC  and Bonferroni correction for multiple tests. We estimated D, a measure of the fraction of allelic variation among populations  among populations with distinct Bd disease dynamics. Specifically, we compared susceptible populations , tolerant populations , and uninfected populations (where Bd infection has not been detected) using Bartlett's tests, one-way anovas, and Kruskal–Wallis tests implemented in R ; thus, we performed M-ratio tests for θ values ranging from 0.01 to 100.We used BOTTLENECK version 1.2.02  , inbreeding (FIS), and allelic richness (AR) for each population locality. For environmental variables, we extracted spatial information of nineteen bioclimatic variables of temperature and precipitation using Worldclim/Bioclim layers at 1000 m resolution  metrics and used the first and second PC axes from each data set  in downstream model selection analyses  to test for associations of disease variables with both genetic and environmental variables. For genetic variables, we included observed heterozygosity , we used a GLM model selection approach. Specifically, we included explanatory environmental and genetic PC variables and disease  as a response variable. We tested all possible models including interactions among explanatory environmental and genetic variables. Models were ranked based on Akaike information criterion (AICc), and we selected the most parsimonious model for each run.To test for an association between genetic and environmental factors and each disease response variable , which defines the minimal cline distance at which populations cannot respond to environmental variation. Predictions of three alternative scenarios—genetic homogenization (H), differentiation due to random drift (R), or adaptive divergence (A)—are based on two derived variables: β, the ratio of migration to drift, and k, the ratio of the geographic scale at which selection favors a given allele (j) relative to lc . We used a range of estimates of effective population size (Ne) and strength of selection (s) to infer the conditions likely to lead to adaptive divergence , random differentiation (R: β < 1), or genetic homogeneity  across the 95% confidence interval of estimated migration among MRHS and MRBC.To explore the dynamics of gene flow, drift, and selection among neighboring populations differing in disease epidemiology, we focused on the geothermal MR locality, where populations with different disease dynamics occur in close proximity and migration could thus potentially have large effects on the evolution of  Adkison  and McCa Adkison  to definlatkin's  characteBd infection from skin swabs for 208 L. yavapaiensis individuals sampled in winter  across 12 study sites in Arizona, USA . Populations were significantly differentiated; excluding comparisons among the MR subpopulations, mean pairwise FST was 0.32 (range 0.17–0.60) with 90% of comparisons significant (adjusted P = 0.000549) and mean D was 0.64 (range 0.41–0.91) with all comparisons significant  and allelic richness . Post hoc comparisons using the Tukey's HSD test indicated that mean allelic richness for Bd-tolerant populations was significantly different than for Bd-uninfected populations, but not significantly different from for Bd-susceptible populations ; however, we also performed Kruskal–Wallis nonparametric tests to infer whether means were significantly different without assuming equal variances. Similar to anova results, mean allelic richness was significantly different between disease categories , while mean heterozygosity was not . AR; Fig.,B, and Bd AR Fig.,D. Mean N = 4), and (ii) individuals from the two Bd-uninfected localities (HS and AS) were assigned to the same genetic deme despite the large geographic distance separating these populations (265 km) and the presence of four genetically distinct populations in the intervening region  of 0.89 , we re-ran genetic structure analyses with this locus removed due to putative non-neutral effects. Analyses excluding the outlier locus did not produce differences in deme membership or the number of inferred demes (data not shown).Bayesian assignment revealed 10 genetic clusters that corresponded to the 12 geographic sampling localities with two exceptions: (i) Individuals from population UH showed mixed ancestry among several genetic demes, likely due to extremely small sample size  or the two-phase model . The three populations that did not show a pattern of demographic expansion under any model were the two thermal spring subpopulations (MRHS and MRSS) and one of the two Bd-uninfected populations (HS).We did not detect genetic signatures of population bottlenecks in any of the sampled populations using either M-ratio tests  or tests of heterozygosity excess compared to simulated values under mutation–drift equilibrium (for any of the three mutation models). However, in nine of the 12 sampled populations, we detected a signature of recent demographic expansion based on a significant deficit of heterozygosity across loci under the stepwise mutation model . Four ofRoC110 showed a pattern of directional selection with an exceptionally high FST value (P < 0.005). All other loci fell within the expected range for neutrally evolving genetic markers. We tested the 10 identified population genetic demes for associations between microsatellite allele frequencies and two chytridiomycosis phenotypes: alive (0), for individuals observed to be alive and healthy regardless of Bd infection status, or dead (1), for individuals that were Bd-infected and found dead or dying with signs of chytridiomycosis. Across all 14 loci only RoC110, the previously identified outlier locus showed a significant association between allele frequencies and Bd infection phenotype within genetic groups , with higher average temperatures predicting higher Bd infection loads across sampled populations . Although environmental factors were important predictors of both Bd infection intensity and prevalence, host genetics alone best explained mortality . Specifically, populations with lower AR and HO and higher FIS  showed significantly higher mortality rates in the field.In our combined analysis of genetic variables, environmental variables, and their interactions, both genetic diversity and environmental variables were significant predictors of evalence . Warmer nce Table, and low P = 0.05; Table1.m) among all pairs of populations  into both the pond  and the canyon . Migration was not detected between MRSS and MRBC, or from either of these localities back to MRHS  ranging from 10 to 10 000 individuals and included migration rates spanning the 95% confidence interval of estimated dispersal from MRHS into MRBC (14–29% per generation). Assuming that Bd-driven selection is zero at the thermal springs, the model predicts that the strength of selection  for chytridiomycosis resistance in the canyon must be >0.07 for the MRBC frogs to adapt at the lower 95% CI of migration, independent of Ne  was the best predictor of mortality  while others show mortality at fairly low infection intensities . The ‘10 000 Zoospore Rule’, a Bd infection threshold for inducing frog mortality in California's Sierra Nevada , or in the Bd-uninfected population House Spring (HS). Thus, populations that currently show Bd-associated declines have recently expanded, whereas populations that have not faced Bd-associated declines have not. Based on these patterns, we propose the following scenario: In the recent past , compared to currently Bd-tolerant populations that likely held standing genetic variation for Bd tolerance when the pathogen first emerged and therefore did not crash as severely upon initial Bd outbreaks. The lack of demographic expansion in three of the four populations that have not experienced Bd declines  provides further support for this scenario. Demographic expansion was also detected in a phylogeographic analysis of L. yavapaiensis based on mitochondrial DNA haplotypes  individuals were under selection for chytridiomycosis resistance, while MRHS and MRSS  subpopulations were environmentally sheltered from this selective pressure. However, MRBC belongs to the same genetic deme as MRHS and MRSS and was not significantly differentiated based on pairwise FST and D values  for MRBC frogs to adapt given the annual influx of susceptible genotypes from MRHS. A selection coefficient of 0.11 corresponds to an 11% increase in fitness of individuals with the advantageous genotype when compared to individuals lacking that genotype. In genomewide studies of polymorphisms in Drosophila, estimated selection coefficients for single mutations range from 0.000012 to 0.02  was a surprising pattern that may derive from a common genetic signature of population structure in the absence of Bd, although further identification and sampling of uninfected populations is necessary to draw conclusions about the precise effects of Bd on population genetic structure. Of note, we did not explore pathogen genetic variation in this study. Recent genetic analyses of worldwide Bd samples have identified genomic recombination, selection, and chromosome copy number variation (Farrer et al. Bd strains; thus, future work incorporating fine-scale pathogen variation will likely further elucidate the epidemiology of chytridiomycosis in L. yavapaiensis.We found a single outlier locus that showed significant association to Bd currently infects amphibians on every continent where it occurs (Skerratt et al. Bd will be critical for accurate planning and implementation of species conservation efforts (Woodhams et al. Bd resistance, effective conservation efforts will likely entail management actions that promote genetic diversity and increase effective population sizes, as genetic diversity explained Bd-associated mortality in L. yavapaiensis but environmental factors did not (TableL. yavapaiensis populations in recent decades (Fig.Bd-resistant and/or Bd-tolerant genotypes to overcome chytridiomycosis susceptibility. Preserving and promoting genetic diversity in isolated populations is therefore likely to be the most effective management strategy to increase the long-term probability of L. yavapaiensis species persistence in the face of ongoing negative effects of habitat change and chytridiomycosis.Our findings demonstrate the importance of integrating genetic polymorphisms, environmental variables, and detailed measurements of disease dynamics in the field to better understand potential evolutionary responses to disease emergence in natural landscapes. Our findings may prove useful in predicting the fate of populations facing pathogen selective pressure and in designating important evolutionary lineages containing genetic variation for local adaptation to chytridiomycosis. not Table. Paradoxades Fig. has prev


Glossina fuscipes fuscipes is the main vector of African Trypanosomiasis affecting both humans and livestock in Uganda. The human disease (sleeping sickness) manifests itself in two forms: acute and chronic. The Lake Victoria basin in Uganda has the acute form and a history of tsetse re-emergence despite concerted efforts to control tsetse. The government of Uganda has targeted the basin for tsetse eradication. To provide empirical data for this initiative, we screened tsetse flies from the basin for genetic variation at the mitochondrial DNA cytochrome oxidase II (mtDNA COII) gene with the goal of investigating genetic diversity and gene flow among tsetse, tsetse demographic history; and compare these results with results from a previous study based on microsatellite loci data in the same area.Gff tsetse fly samples from 14 localities in the entire Ugandan portion of the Lake Victoria coast, covering 40,000 km2. We performed genetic analyses on them and added data collected for 56 Gff individuals from 4 additional sampling sites in the basin. The 529pb partial mitochondrial DNA cytochrome oxidase II (mtDNA COII) sequences totaling 485 were analysed for genetic differentiation, structuring and demographic history. The results were compared with findings from a previous study based on microsatellite loci data from the basin.We collected 429 ΦST  and Bayesian analyses suggest some level of weak genetic differentiation, there is no correlation between genetic divergence and geographic distance , and demographic tests provide evidence of locality-based demographic history.The differences within sampling sites explained a significant proportion of the genetic variation. We found three very closely related mtDNA population clusters, which co-occurred in multiple sites. Although Gff populations were more connected in the past. Microsatellite data revealed more genetic structuring than mtDNA. The differences in connectedness and structuring over time could be related to vector control efforts. Tsetse re-emergence after control interventions may be due to re-invasions from outside the treated areas, which emphasizes the need for an integrated area-wide tsetse eradication strategy for sustainable removal of the tsetse and trypanosomiasis problem from this area.The mtDNA data analysed here complement inferences made in a previous study based on microsatellite data. Given the differences in mutation rates, mtDNA afforded a look further back in time than microsatellites and revealed that The online version of this article (doi:10.1186/s13071-015-0984-1) contains supplementary material, which is available to authorized users. Appranosomes : Trypanoute form , 5. Therute form . AAT is ute form , 8. TherSince reducing host/vector contact can rapidly slow human trypanosomiasis transmission , controlGlossina palpalis gambiensis and Glossina tachinoides in a 3000 km2 area in an agro-pastoral zone of Sideradougou, in the Guinea savannah in Cameroon [In 2001, the African Union established the Pan African Tsetse and Trypanosomiasis Eradication Campaign (PATTEC) with a view of using an integrated area-wide approach to control HAT and AAT with the available methods. A prerequisite to any vector control campaign aiming at eradication is to identify and target isolated populations to minimize the risk of reinvasion. If not already isolated, populations could be isolated by creating physical obstacles, such as the insecticide-impregnated biconical trap barriers. Such a method has been used to effectively control Cameroon .Glossina fuscipes fuscipes (Gff) based on mark-release-recapture (MRR) studies are about 14.2 km per generation, given a movement estimate of 338 m/day [Population genetic techniques can help understand and quantify gene flow between populations, which can be used as a proxy for dispersal . Dispers38 m/day .Gff disperse up to 14 km per generation [Gff appear to be genetically homogeneous over 1–5 km2.Fine-scale genetic analysis based on microsatellites confirmed that neration , Gff appGlossina palpalis palpalis in west and central Africa [palpalis tsetse group in cross-boundary projects. Studies of tsetse in Burkina Faso, Guinea and Senegal have identified riverine tsetse populations that are sufficiently isolated to warrant attempts at complete eradication [morsitans or savannah tsetse group, population genetic studies have indicated high gene flow among Glossina morsitans morsitans populations separated at geographic scales of 12–917 km in East and Southern Africa [Information about dispersal derived using population genetic techniques can be used to support vector control decision-making , 18 at vl Africa  have prodication , 21. In n Africa , 23.Gff, a riverine subspecies in the palpalis group, is the major vector of HAT. The acute form of HAT (T. b. rhodesiense) previously had its historical focus along the shores of Lake Victoria, but has recently extended its range northwards into central Uganda [T. b. gambiense) found in northwestern Uganda, thereby complicating diagnosis, treatment, and providing new challenges, as recombination between the two trypanosome forms can occur and could lead to unforeseen pathologies [In Uganda, l Uganda , 24. If hologies , 26.Gff in the Lake Victoria basin; an area with a history of tsetse re-emergence despite concerted tsetse control efforts [Gff in the Lake Victoria basin may elucidate the factors influencing re-emergence. Indeed, genetic tools have revealed genetic structuring among localities north, south and west of Lake Kyoga in Uganda, occurrence of gene flow among genetic clusters [In an effort to eliminate the acute form of the disease and to prevent potential challenges associated with overlap of the two forms of HAT in Uganda, in 2008 Pan African Tsetse and Trypanosomiasis Eradication Campaign (PATTEC) activities were initiated against  efforts . Tsetse  efforts . Understclusters , and temclusters . We prevclusters . That stIn this study, we followed up on the work of our group  by screeGff tsetse fly samples from 14 localities in the entire Ugandan portion of the Lake Victoria coast, covering 40,000 km2 .Total genomic DNA was extracted from legs of individual tsetse flies using the PrepGEM™ Insect kit (ZYGEM Corp. Ltd) as per the manufacturer’s protocol. A 570 bp fragment of mtDNA COII gene was PCR-amplified using the primers COIF1 (5’ – CCT CAA CAC TTT TTA GGT TTA G – 3’) and COIIR1 (5’ – GGT TCT CTA ATT TCA TCA AGT A – 3’), as described by . ReactioGff individuals from 4 additional sampling sites in the basin [Chromatograms were visually inspected and sequences trimmed to remove poor quality data using the CLC Workbench (CLC Bio Denmark). The forward and reverse strands were used to create a consensus sequence for each sample. In addition to the newly sequenced 429 samples, mtDNA COII gene sequences for 56 he basin   and nucleotide diversity (π) using DnaSP version 5.10 . Signifihttp://fluxus-engineering.com). This program implements the median-joining method in the absence of recombination. The method, which provides an estimation of the haplotype genealogical relationships, is a more powerful method than bifurcating trees, when studying phylogenetic relationships at the intraspecific level, because it allows for the inclusion of multi-furcations and reticulations [To understand the evolutionary relationship of the mtDNA haplotypes, we constructed a median-joining haplotype network , where iulations . The proulations  was useda priori that the structure within a particular area depends on the neighbouring areas. This program uses a statistical genetic model that treats nucleotide frequencies and K  as random variables. The best K was determined using posterior probabilities. The best partition was visualized using a Voronoi tessellation as implemented in BAPS.Genetic differentiation among the 18 sampling sites was evaluated with and without spatial information as a priori , using tΦST values among sampling sites using Arlequin 3.5 with 1000 random permutations. We used ΦST because it also accounts for the evolutionary relatedness of the mtDNA haplotypes. To test the correlation between these pairwise genetic distances and pairwise geographic distances, we used Mantel’s test [To obtain pairwise estimates of genetic differentiation we computed l’s test  with 9,9l’s test .D [FS [We used mismatch distributions   to deterD  and Fu’sD [FS  statistiD [FS  and signA 526 bp fragment of the mtDNA cytochrome oxidase II (COII) was analysed from 485 individuals from 18 localities around the Lake Victoria basin , confirming population expansion of the Gff population in this part of the basin. At locality level, however, FS and D statistics , which are continental sites about 100 km apart. Samples from Lingira (LI), an island site in Buvuma islands and Nkumba (NA), a continental site about 40 km away, were not genetically distinct , suggesting that there has been gene flow between islands and continental sampling sites. Surprisingly, samples from KO, a site only 5 km from DB and NS in the Koome archipelago, were genetically distinct from all samples including those from DB and NS which are only 5 km within the same archipelago, but similar to samples from KG, an island site more than 100 km away in Kalangala islands, suggesting possible long-range dispersal among the islands’ Gff. Additional file R =0.109, P = 0.185), confirming the findings from the ΦST and the BAPS analyses.Similar conclusions in terms of overall levels of genetic divergence can be inferred from the pairwise es Table . Among lGff populations across the Lake Victoria basin revealed very little genetic structuring. Most of the genetic variation at this locus was found within rather than between sampling sites , with the majority of the haplotypes (91.3 %) in the network originating from it. This haplotype has a range-wide distribution across the basin, and more than 95 % of all the haplotypes are shared among the localities, suggesting long-range gene flow across the basin. Despite the long-range gene flow, some haplogroups were retrieved from only geographically proximate localities, which, coupled with the presence of private haplotypes at some localities further supports the importance of both gene flow and genetic drift in shaping the observed genetic patterns. Localities around the source of the Nile, such as BD, BV, LI, BY and MG  from adjacent areas and/or residual tsetse pockets. As such, the high levels of genetic mixing between


Balanus improvisus , is one of the most successful aquatic invaders worldwide, and is characterised by broad environmental tolerance. Although the species can spread through natural larval dispersal, human-mediated transport through (primarily) shipping has almost certainly contributed to the current global distribution of this species. Despite its worldwide distribution, little is known about the phylogeography of this species. Here, we characterize the population genetic structure and model dispersal dynamics of the barnacle B. improvisus, and describe how human-mediated spreading via shipping as well as natural larval dispersal may have contributed to observed genetic variation. We used both mitochondrial DNA (cytochrome c oxidase subunit I: COI) and nuclear microsatellites to characterize the genetic structure in 14 populations of B. improvisus on a global and regional scale . Genetic diversity was high in most populations, and many haplotypes were shared among populations on a global scale, indicating that long-distance dispersal (presumably through shipping and other anthropogenic activities) has played an important role in shaping the population genetic structure of this cosmopolitan species. We could not clearly confirm prior claims that B. improvisus originates from the western margins of the Atlantic coasts; although there were indications that Argentina could be part of a native region. In addition to dispersal via shipping, we show that natural larval dispersal may play an important role for further colonisation following initial introduction.Understanding the ecological and evolutionary forces that determine the genetic structure and spread of invasive species is a key component of invasion biology. The bay barnacle,  The number of non-native species being introduced to coastal and estuarine habitats has increased dramatically during the past century; largely due to anthropogenic activities including increased shipping intensity and aquaculture trading ,2. In maDispersal dynamics in the marine realm are generally complex and not well understood . DispersGenetic markers are typically used in tracing origins of populations as well as understanding population structure and dispersal mechanisms ,27–29. SBalanus improvisus  has invaded shallow coastal environments worldwide and is particularly common in estuaries and low salinity environments where it often forms dense populations , 72°C for 1 min) x 11 cycles;  s, 72°C for 1 min) x 23 cycles; 72°C for 5(7/10) min. Details of the PCR protocol, i.e. MgCl2 concentration, number of PCR cycles and type of ‘universal’ tail, are provided in https://datadryad.org/) with the accession number DOI: 10.5061/dryad.sf2v0).Three different development approaches were used to obtain microsatellites for  PRIMER3  implemen PRIMER3 ; Biomatt PRIMER3  from an SKER 3.3 . Three dSKER 3.3 . A PIG-tSKER 3.3 . Some mimM MgCl2 , 0.025 Uhttp://www.geneious.com, [The COI sequences were edited and aligned using GENEIOUS PRO 6.1.6 . Primerh, [π; [th best model choice according to AIC and BIC criteria).Molecular diversity indices including haplotype diversity , nucleoh, [π; ), numberh, [π; . The apph, [π; ,77. ResuBalanus eburneus were used as an out-group for this maximum likelihood analysis.Genealogical relationships among COI haplotypes were examined by reconstructing a haplotype network following the parsimony method of Templeton et al.  implemenST [ST were further linearized following [http://www.R-project.org). A hierarchical analysis of molecular variance (AMOVA) [B. improvisus was investigated using a mismatch distribution analysis [D [FS [FS test was set to 0.02 according to recommendation in the ARLEQUIN 3.5 manual.We estimated pair-wise genetic differentiation between populations using the fixation index ΦST  obtainedST . Pairwisollowing  as imple (AMOVA)  using thanalysis ,86. The analysis  was usedlysis [D  and Fu’ss [D [FS  that tesNA), observed (HO) and expected (HE) heterozygosity, and to test for deviations from Hardy–Weinberg equilibrium and linkage disequilibrium. FIS was estimated and tested using the probability tests within GENEPOP. Microsatellite allelic richness (Ar) was calculated using the rarefaction method in FSTAT [FST estimator θ [The software MICRO-CHECKER  was usedin FSTAT . Populatimator θ , and in imator θ . For nulimator θ . The BOTimator θ ) was appB. improvisus was explored with approximate Bayesian computation analyses (ABC). ABC analyses of both the four microsatellite markers and mitochondrial sequences of the COI locus were analysed with the program DIYABC v2.1.0 (www1.montpellier.inra.fr/CBGP/diyabc/), described in [B. improvisus in the Baltic Sea. The tested scenarios are shown in B. improvisus and with one introductory branch to the Pacific coast of America, Japan, the Black Sea and the Caspian Sea, and another introductory branch to Europe (France) and later into the Baltic Sea . Scenario 2 instead, assumes the west coast of the Americas to be the native region with one introductory branch to Japan, the Black Sea and the Caspian Sea, and another sequence to the east coast of the Americas then to Europe and into the Baltic Sea. Scenario 3 assumes an early introduction to Europe and subsequent dispersal into the Baltic Sea and later to the Black and the Caspian Seas. Finally, Scenario 4 assumes that B. improvisus originates from Europe. We also simulated two scenarios for the invasion into the Baltic Sea  ranged between 10–10,000 generations for all introductions. The genetic variation within and between populations was calculated using a set of summary statistics. For microsatellites we used mean number of alleles and expected heterozygosity within populations, and the pairwise comparisons FST and dμ2 between populations. For the COI sequences we used mean number of haplotypes and mean of pairwise differences within populations, and FST and mean number of pairwise differences between populations. We simulated between 106 to 4∙106 data sets per scenario. The distributions of summary statistics based on the sampled priors were reasonably close to observed data  for microsatellites [www.sea-distances.com) and distances obtained in nautical miles were converted into km.To test the hypothesis of isolation-by-distance, correlation between pairwise linearized Φtellites , versus tellites  implemen2) we released a total of 47040 particles. Dispersal probabilities between the seven localities were calculated by summing all the trajectories starting in locality i having end positions within locality j normalized by the total number of simulated trajectories from locality i. Also the probability to disperse within any locality was calculated. In addition, we calculated the multi-generation connectivity where stepping-stone dispersal was allowed over 16 and 32 single-generation dispersal events, and summed over all possible dispersal routes [B. improvisus is poorly described in the Baltic Sea, and to reduce the risk of underestimating connectivity. However, we excluded all areas below 100 m, which are anoxic. Tests for correlations between multi-generational connectivity and linearized genetic differentiation (FST /1- FST) were performed using the same Mantel test as described above. The data on linearized FST for genetic differentiation are symmetric between localities. This is generally not the case for oceanographic connectivity and in the study area there are marked asymmetries in water transport. To allow for a Mantel test we made the connectivity matrices symmetric by calculating the minimum connectivity between each pair of localities, which may arguably be best correlated with increasing FST. Minimum connectivity also explained more of the genetic differentiation compared to the maximum, as well as to the arithmetic and geometric means of connectivity.We also tested if genetic differentiation between populations was correlated with oceanographic connectivity in the Baltic Sea. The connectivity between sites was estimated using a biophysical model, where velocity fields from an ocean circulation model were combined with a Lagrangian particle-tracking routine to simulate drift trajectories representing the dispersal of barnacle larvae. Velocity fields were first produced with the BaltiX model, which is a regional Baltic-North Sea configuration of the NEMO ocean model . The spal routes . We chosST). Haplotype diversity for the 12 remaining populations ranged between 0.75–0.96. The lowest haplotype diversity out of these 12 populations was found in the northern Baltic populations—Umeå (0.85) and Öregrund (0.75)—as well as in the Caspian Sea (0.83) and Black Sea (BL: 0.82), and the highest was observed in the Estonian (0.96) and Japanese (0.95) populations (A 694 bp sequence of the cytochrome oxidase I (COI) was successfully obtained for 448 individuals from 14 populations . Sequenculations . Nucleotulations .The geographic distribution of the 12 most frequent haplotypes (across the samples) revealed high haplotype diversity in most populations . The mosD showed significant negative values for all populations except the Black Sea population, and Fu’s FS showed significant negative values for all analysed populations  was similar in all populations, ranging from 0.76 in Kiel to 0.83 in Torhamn  and Chesapeake Bay (CB) populations despite multiple PCR trials. We identified 78 alleles in total , where the mean number of alleles per population ranged from 8 to 13 . No sign Torhamn . Allelic Torhamn . Their m Torhamn . However Torhamn , S4 Fig.Population genetic differentiation (pairwise Φst) based on COI data varied from -0.009 (Torhamn-Kiel) to 0.167 (France-Black Sea), with an overall average of 0.039 ±0.005 (SE) . Based oFST, after null allele corrections (mean FST = 0.013±0.001 SE), were similar to uncorrected estimates (FST = 0.015±0.001) (FST varied from -0.002 (Black Sea-Caspian Sea) to 0.034 (France-Argentina) with an average of 0.013 ±0.001 (Estimates of microsatellite pairwise 5±0.001) . Hence, 3 ±0.001 .Both the MDS plots, visualising similarity between populations in 2-dimensions based on microsatellites and mtDNA, grouped the Baltic populations together, although the northern Baltic (UM and OR) and southern Baltic  were separated into two clusters only in the mtDNA data . Saltö . France FCT = 0.037; p<0.0001), whereas slightly less variation (2.1%) was explained when separating Saltö from the Baltic populations    . No vari p>0.07) . In cont p>0.07) , showed B. improvisus, showed that scenarios 3 and 4 received very weak support based on the posterior probabilities using logistic regression of COI summary statistics  for microsatellites , but not for mitochondrial DNA . In the Baltic-Skagerrak region, microsatellites showed no isolation by distance (IBD) , and for mitochondrial DNA there was a nearly significant IBD  . OceanogB. improvisus, we found high levels of genetic diversity in both mitochondrial and nuclear markers in most populations . These levels are also high when compared to several other invertebrate species with similar invasive backgrounds, such as the tunicate Botrylloides violaceus  [Carcinus maenas  [Amphibalanus amphitrite [In this first study investigating global population genetic structure of the widely distributed barnacle 3.0–4.4) , or the lations) . Howeverphitrite  revealedBalanus glandula populations along the Pacific US coast. However, the genetic diversity within populations was very low due to the recent invasion (1970’s), and no evidence of multiple sources was detected. In contrast, Chen et al. [A. amphitrite, where sequences were divided into three distinct clades (with a 4% divergence between clades) indicating historical isolation between populations or possibly a cryptic species complex. In comparison, we found high genetic diversity within all B. improvisus populations, but could not identify any phylogenetic clades. Furthermore, no clear colonisation routes were identified, probably because high global shipping intensity has resulted in high admixture between populations.Previous phylogeographic studies on barnacles have typically investigated regional genetic structure connected to present dispersal patterns ,111 or qn et al.  found hiB. improvisus is a simultaneous hermaphrodite, and self-fertilization has been suggested to occur [B. improvisus (www.cemeb.science.gu.se/research/imago-marine-genome-projects). Heterozygote deficiency is commonly observed in some invertebrate groups [Microsatellite results revealed very high heterozygote deficiencies relative to Hardy-Weinberg expectations (HWE) in three out of four loci , which mto occur ,116, alte groups ,27 and te groups ,117,118.B. improvisus originates from the Atlantic coast of North and/or South America  and North Carolina (NC), but that most of these were later most likely identified as Balanus subalbidus based on their highly divergent COI sequences and additional sequencing of other individuals that were identified as B. subalbidus based on morphology. B. subalbidus is an estuarine barnacle species with similar morphology to B. improvisus, especially as juveniles [B. subalbidus in our samples indicates that B. subalbidus may be more common in the Chesapeake Bay and Neuse River area (North Carolina), than previously acknowledged [B. subalbidus and B. improvisus. If B. improvisus has indeed been partly out-competed by B. subalbidus in low salinities, then the remaining small population sizes of B. improvisus could result in partial isolation and reduced genetic diversity. Furthermore, nothing is known about possible hybridization between B. improvisus and B. subalbidus, where e.g. introgression also could explain the mismatch between the amplification of mtDNA and microsatellites for these samples. Clearly, more studies are required to evaluate this possibility.It is commonly stated in the literature that ca e.g. ,43,56), ,56, B. ica  population being part of the native region for iversity , as welliversity . Furtheriversity . The ABC America , S5 Fig.B. improvisus has probably been transported between coasts for many centuries, even before the species first was described by Darwin in 1854. Therefore, the early descriptions of B. improvisus from the Atlantic American coast may not provide evidence of the true origin of B. improvisus. The fact that many introduced populations had a high proportion of private haplotypes , suggests that we may have missed several native populations in our sampling for this study, and thereby the extent of native genetic diversity could be greatly underestimated. For example, the French population displayed a remarkably high proportion (34%) of unique haplotypes  compared to North American (introduced) populations . However, many recent studies have shown that introduced populations show little reduction in genetic diversity, and that some may even display higher genetic diversity than in the native range, caused by multiple introductions from different source populations [A common assumption regarding introduced populations has been that they should experience loss of diversity relative to native sources because of founder effects and post-introduction demographic bottlenecks ,119. Forulations ,122.h = 0.75–0.96, Ar = 7.5–9.1). This is likely the result of multiple introductions from different sources, with large founding populations and/or potential admixture, e.g. [In our study, we found high genetic diversity in almost all populations  was also found in the Caspian Sea and Black Sea populations, supporting the idea that at least one introduction from Atlantic US to these regions has occurred . This ins leyidi . HoweverColonisation history of fouling organisms is often complex, since human-mediated dispersal via maritime activities has occurred for several centuries. Especially during the past century, shipping intensity has increased dramatically, facilitating new invasions of non-indigenous species as well as potentially modifying population genetic structure in already established species . PreviouB. improvisus. An interesting pattern, related to historical shipping, is the unexpectedly high similarity between Argentina (AR) and Saltö (SA) (Φst = -0.003). From the late 19th century to early 20th century there was intensive shipping activity between these regions: the small town Krokstrand  in Sweden was a key port from which granite was shipped to several parts of the world during many decades, including Buenos Aires in Argentina where it was used to pave the streets of the city [The high genetic diversity that we observed in most populations including many shared haplotypes on a global scale, suggests that shipping and other anthropogenic activities have played an important role in shaping the current population genetic structure of the city .B. improvisus was observed in French waters already in 1872 [Crassostrea gigas) to French oyster farms in the 1960’s [Sargassum muticum and the mollusc Crepidula fornicata [C. fornicata populations along the French coast, and suggested that these populations derived from several genetically diverse, but poorly differentiated source populations.Another common source of introductions of non-native species is indirectly through aquaculture activities . The hig in 1872 , they wee 1960’s . Other eornicata ,129. Simornicata  found hiS. balanoides.On a global scale, there was a pattern of isolation by geographical distance (defined as closest shipping distance) for microsatellites, but not for mitochondrial DNA. One possible explanation for this pattern is that most CO1 haplotypes were already present when global shipping began to translocate populations between places, thus resulting in a re-shuffling of “old” haplotypes that may poorly reflect geographic distance. Microsatellites on the other hand may reflect contemporary processes of gene flow and random drift; while it is also possible that new alleles can arise through mutations to produce an “isolation by distance” signal, it is unlikely that new mutations have caused this pattern (cf. ), given Oceanographic connectivity seemed to better explain patterns of genetic differentiation at a regional scale  where both microsatellites and mitochondrial DNA revealed a significant correlation with (minimum) connectivity between sampling sites . The lacB. improvisus.Notably, the AMOVA comparing groups of populations within the Baltic Sea  indicateB. improvisus is a cosmopolitan species, successfully colonising many parts of the world, is not surprising. The species displays several life history traits that are associated with successful invaders including broad environmental tolerance , has an extended spawning season and a low habitat selectivity at settlement [B. improvisus, intensive human-mediated gene flow probably counteracts these processes, resulting in the pattern of high diversity and little differentiation even on a global scale, as we found in this study. This high diversity and gene flow from multiple sources may have implications for the ability of B. improvisus to adapt to local conditions, compete with native species, spread to new areas as well as cope with future environmental change.Furthermore, ttlement , all of ttlement . Fluctuattlement . HoweverB. improvisus, but suggest that Argentina may at least be part of the native region. Further sampling of multiple populations in this area is required to clarify the pattern. Evidence of bottlenecks associated with founder events were only observed in the Caspian and Black Sea and in the northern Baltic Sea, although most populations showed genetic patterns consistent with recent expansion events. Oceanographic connectivity, rather than geographic distance, seems to explain regional genetic structure within the Baltic Sea, highlighting the importance of larval dispersal for further natural spreading of introduced species. Knowledge about different types of dispersal dynamics of non-native species is crucial to our understanding of both evolutionary aspects of colonisation as well as future management of biological invasions. The implications of the broad environmental tolerance and high dispersal capacity of B. improvisus for its ability to adapt to local conditions and tolerate future environmental changes remains to be elucidated.In conclusion, we found high genetic diversity in most populations, including both putatively native and introduced regions, indicating high gene flow between populations via shipping and other anthropogenic activities. Furthermore, mitochondrial and nuclear markers revealed similar patterns. Our results could not clearly identify the geographic origin of S1 FigB. improvisus on a global scale while the last two scenarios focus on two alternative colonization routes for the Baltic Sea. Abbreviations of population samples are: AR–Argentina, FR–France, SA–Saltö, BA–Baltic Sea, BL–Black Sea, CS–Caspian Sea, PU–Pacific US, JP–Japan, BA-S–southern Baltic Sea , BA-N–northern Baltic Sea . See The first four scenarios  explore the most likely origin of (TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 FigBalanus eburneus was used as an out-group for this maximum likelihood analysis.The robustness of branches was tested with 100 bootstraps, and a COI sequence of (PDF)Click here for additional data file.S4 FigA) locus C103 separately; B) B4, E29 and E42 pooled. Although the loci B4, E29 and E42 showed high heterozygote deficiency, they display similar patterns to locus C103.(TIF)Click here for additional data file.S5 FigThe figures are based on samples of (a) COI sequences, and (b) microsatellite loci.(TIF)Click here for additional data file.S6 FigThe figures are based on samples of (a) COI sequences and (b) microsatellite loci.(TIF)Click here for additional data file.S1 Table(TIF)Click here for additional data file.S2 Table2 (mM) = magnesium chloride concentration, Tm = melting temperature, Ta1 and Ta2 = annealing temperatures .The table contains locus name, repeat motif, primer sequence, universal tail name, MgCl(TIF)Click here for additional data file.S3 TableThe populations are: Argentina (AR), France (FR), Saltö (SA), Kiel (KL), Torhamn (TO), Estonia (ES), Öregrund (OR), Umeå (UM), Black Sea (BL), Caspian Sea (CS), Japan (JP) and Pacific US (PU).(PDF)Click here for additional data file.S4 TableFIS) according to Weir & Cockerham (1984), number of alleles (A) and number of alleles per locus (Ar). Populations: Argentina (AR), France (FR), Saltö (SA), Kiel (KL), Torhamn (TO), Estonia (ES), Öregrund (OR), Umeå (UM), Black Sea (BL), Caspian Sea (CS), Japan (JP) and Pacific US (PU).Sample size (N), expected (He) and observed (Ho) heterozygosities, deviations from HWE ((TIF)Click here for additional data file.S5 TableB. improvisus population separately.The EM algorithm  was used for each locus and (TIF)Click here for additional data file.S6 TableFST without correction for null alleles using ENA correction, FDR corrected significant differentiation in bold (FDR adjusted α0.05 = 0.0341); above diagonal: null-allele corrected pairwise FST between population. NB: p-values cannot be obtained in FreeNA when <5 loci.Below diagonal: Pairwise (TIF)Click here for additional data file.S7 TableBased on mtDNA (COI) data for populations in the Baltic Sea-Skagerrak region: UM = Umeå, OR = Öregrund, TO = Torhamn, KL = Kiel, ES = Estonia, SA = Saltö.(TIF)Click here for additional data file.


Aedes aegypti is the most important vector of dengue fever in Brazil, where severe epidemics have recently taken place. Ae. aegypti in Brazil was the subject of an intense eradication program in the 1940s and 50s to control yellow fever. Brazil was the largest country declared free of this mosquito by the Pan-American Health Organization in 1958. Soon after relaxation of this program, Ae. aegypti reappeared in this country, and by the early 1980s dengue fever had been reported. The aim of this study is to analyze the present-day genetic patterns of Ae. aegypti populations in Brazil.Ae. aegypti in Brazil based on 12 well-established microsatellite loci. Our principal finding is that present-day Brazilian Ae. aegypti populations form two distinct groups, one in the northwest and one in the southeast of the country. These two groups have genetic affinities to northern South American countries and the Caribbean, respectively. This is consistent with what has been reported for other genetic markers such as mitochondrial DNA and allele frequencies at the insecticide resistance gene, kdr.We studied the genetic variation in samples of 11 widely spread populations of Ae. aegypti in Brazil are more consistent with a complete eradication of the species in the recent past followed by re-colonization, rather than the alternative possibility of expansion from residual pockets of refugia. At least two colonizations are likely to have taken place, one from northern South American countries  that founded the northwestern group, and one from the Caribbean that founded the southeastern group. The proposed source areas were never declared free of Ae. aegypti.We conclude that the genetic patterns in present day populations of  Aedes aegypti, was historically very important as the major vector of yellow fever, whereas today it is most notorious for being the major transmitter of dengue fever. In the 1940s and 50s, the Pan-American Health Organization organized a campaign to eradicate Ae. aegypti from the New World. They were partly successful, with Brazil being the largest country to be declared free of Ae. aegypti. Within ten years of relaxation of control efforts, Ae. aegypti reappeared in Brazil and today is the vector of the most intense dengue epidemics in the New World. Here, we present population genetic data that are most consistent with the species having truly been eradicated from Brazil rather than simply pushed into small refugia as a consequence of the eradication campaign. The re-infestation most likely resulted from two sources: 1) from northern S. American countries like Venezuela into northwest Brazil and 2) from the Caribbean into the southeast of the country.The mosquito,  Aedes mosquitoes that occur in tropical and subtropical areas around the world. Due to a widespread distribution, this disease could be more important than malaria in terms of economic impact and morbidity Dengue fever is a viral disease transmitted by Aedes aegypti, which is also a vector for yellow fever and chikungunya viruses Ae. aegypti is a particularly adaptable invasive species that has successfully colonized most tropical and subtropical regions of the world. This is due to the vector's highly anthropophilic behavior and ability to lay its desiccation-resistant eggs in man-made water containers, widely available in most developing countries where water distribution and sanitary conditions are rudimentary. Modern transportation and commerce have greatly contributed to the passive geographical spreading of this vector and, consequently, to disease dissemination. Due to the lack of an effective vaccine, currently, dengue control programs rely almost exclusively on vector control efforts Brazil is especially vulnerable to dengue epidemics, with ten times more cases than other Latin American countries during recent outbreaks Ae. aegypti populations Historically, neurotoxic insecticides have been the method of choice to control th century, when dengue was not yet a public health issue, Ae. aegypti populations were widespread and responsible for several yellow fever epidemics, especially in the northeast of Brazil. Motivated by the success achieved by the Anopheles gambiae control program, the Brazilian government launched, in 1947, an initiative to eradicate Ae. aegypti populations based on the use of DDT. In 1958, during the XV Conferencia Sanitária Panamericana in Puerto Rico, Brazil was declared free of Ae. aegypti. The species was again recorded in the late 1970's, probably as a consequence of a reduction in the efficacy of the vector control measures employed In this context, Brazil is a particularly interesting country regarding dengue epidemiology because it has gone through a well-documented vector eradication program Ae. aegypti populations were based upon RAPD markers and revealed high levels of interpopulation genetic differentiation The first studies to assess the genetic structure of Brazilian kdr (knock-down resistance) mutations, which confer pyrethroid resistance, found at least three distinct genetic groups in 30 Brazilian populations. The analyses of mtDNA sequence data (ND4 and COI) of several Brazilian populations revealed the co-occurrence of two distinct lineages in the country Ae. aegypti in Brazil. Here, we present the results of the analysis of 12 microsatellite loci in Brazilian Ae. aegypti populations in an effort to better understand the genetic structure of this vector in the country, which may lend insights into the presumed recolonization following eradication events.Microsatellites are assumed neutral, highly variable codominant markers commonly used in population genetics. However, they have never been used in a nationwide study of Ae. aegypti samples were field-collected from 11 sites in Brazil  following the manufacturer's protocol. Individual genotypes were scored for 12 previously published microsatellite loci et al.et al.Microsatellite alleles were scored using Gene Mapper software (Applied Biosystems). The experiments were performed in the Yale Laboratory using the same ABI machine as used by Brown ST values. Genetic diversity per locus and in each population was estimated by unbiased expected heterozygosity using GenALEx v6.5 ST values and their significance between all pairs of populations with 1,000 permutations. Cavalli-Sforza and Edwards distances were computed using the software package Phylip 3.6 ST/(1-FST)). For both analyses significance was inferred with 1,000 permutations.To infer the statistical reliability of our markers, each locus was tested for deviations from Hardy-Weinberg expectations on the web version of Genepop v1.2 The Bayesian approach used in the software STRUCTURE v2.3.2 IS values deviated significantly from Hardy-Weinberg expectations at the 5% significance level after sequential Bonferroni correction  locus-by-locus tests for LD remained significant after Bonferroni correction, no two loci were consistently correlated across populations. Eleven of the 231 (4.76%) Frrection . Of the n et al.. Other ln et al.. Null alST and identity values ST values and almost none when assignment methods are used ST values shows very small deviations in our dataset , and allelic richness for all loci studied are given in p<0.08) with only Pau dos Ferros, São Gonçalo, Dominica and Miami with estimates greater than 0.16  indicates a moderate level of population differentiation . Miami and some Brazilian populations had FST values lower than 0.10  but not so much for K = 5 (92%) and even less for K = 13 (86.5%), corroborating the higher peak found for K = 2 in the Evanno plot .et al.Since STRUCTURE seems to identify the higher hierarchy in population differences When the red group is analyzed K = 2, K = 3, and K = 5 provide some insights . The twoAe. aegypti separate into two major genetic groups with distinct affinities to populations outside Brazil as indicated in Despite these subtle genetic patterns, we have strong evidence to conclude that Brazilian populations of Ae. aegypti in 1958 Brazil was officially declared free of et al.et al.Ae. aegypti are highly susceptible to DENV2 virus et al.Our results indicate that two major genetic groups are present in Brazil, one descending from Venezuela and probably other northern American countries and another one from the Caribbean . Bracco et al.kdr genetic groups in the country . Since differential selection pressures acting in the area studied could not account for their findings, the authors argued that the pattern observed could have resulted from genetic differences in the Ae. aegypti strains that founded those populations . The isolation by distance found within Brazilian samples suggests some connectivity among populations, so it is not surprising that the two lineages that may have initially re-invaded Brazil are now exchanging genes and perhaps merging.In our results, although the most important genetic break occurs between Northern populations and all others  and 4, tet al.Ae. aegypti is the fact that Linss et al.kdr mutation allele, Val1016Ile and not Val1016Gly, that is commonly observed in Asian populations. Furthermore, Brown et al.Ae. aegypti probably came from West Africa into the New World, where it dispersed to Asia and Australia. In their study, a Brazilian population from the Southeast (Cachoeiro) is in the same clade as Venezuelan and Caribbean populations, consistent with our findings.The origin of these two genetic units seem reasonably clear from our data, although with only a single Caribbean sample  to compare, the origin of the southern lineage is less well established. Bracco o<0.67) and allelic richness (2.46<Na<4.44) are similar in Brazilian samples and other populations from the Americas, even when compared to countries where eradication did not occur  Ae. aegypti is a simpler explanation consistent with the patterns observed in present day Brazil populations of this vector.While our data are consistent with the re-colonization hypothesis, we cannot exclude alternatives. The two major genetic groups observed today may have existed prior to 1958; following relaxation of vector control, the expansion from refugia within Brazil could have re-established the pattern present today. However, one expects small refugia to drift to heterogeneous gene frequencies such that subsequent expansion would lead to a mosaic of genetic units not geographically structured. Our data do not support such a scenario. Furthermore, a low genetic diversity would be expected due to a bottleneck period, which was not observed either. Measures of diversity Click here for additional data file.Figure S2Ae. aegypti populations analyzed. ΔK plots are based on the rate of change in the log probability of the data between successive K values.Scatter plots of ΔK (A) and Log probability of the data (B) for all (TIF)Click here for additional data file.Figure S3Ae. aegypti populations. ΔK plots are based on the rate of change in the log probability of the data between successive K values. A and B – blue group from STRUCTURE analysis on Scatter plots of ΔK (A and C) and Log probability of the data (B and D) for the two groups of (TIF)Click here for additional data file.Figure S4Ae. aegypti individuals of the blue cluster group from STRUCTURE analysis on STRUCTURE bar plots for (EPS)Click here for additional data file.Figure S5Ae. aegypti individuals of the red cluster group from STRUCTURE analysis on STRUCTURE bar plots for (EPS)Click here for additional data file.Table S1Aedes aegypti FIS values by locus.(DOC)Click here for additional data file.Table S2MicroChecker v2.2.3 null allele frequency.(DOC)Click here for additional data file.Table S3Allele frequencies for the 12 microsatellite loci analyzed.(DOC)Click here for additional data file.


Psittacula krameri) is one of the most successful invasive species, established in over 35 countries. However, little is known about the evolutionary genetic origins of this species and what population genetic signatures tell us about patterns of invasion. We reveal the ancestral origins of populations across the invasive range and explore the potential influence of climate and propagule pressure from the pet trade on observed genetic patterns. Ring-necked parakeet samples representing the ancestral native range (n = 96) were collected from museum specimens, and modern samples from the invasive range (n = 855) were gathered from across Europe, Mauritius and Seychelles, and sequenced for two mitochondrial DNA markers comprising 868 bp of cytochrome b and control region, and genotyped at 10 microsatellite loci. Invasive populations comprise birds that originate predominantly from Pakistan and northern areas of India. Haplotypes associated with more northerly distribution limits in the ancestral native range were more prevalent in invasive populations in Europe, and the predominance of Asian haplotypes in Europe is consistent with the higher number of Asian birds transported by the pet trade outside the native range. Successful establishment of invasive species is likely to be underpinned by a combination of environmental and anthropogenic influences.Invasive species present a major threat to global biodiversity. Understanding genetic patterns and evolutionary processes that reinforce successful establishment is paramount for elucidating mechanisms underlying biological invasions. Among birds, the ring-necked parakeet ( Invasive species represent a global concern to society and the wider environment as a consequence of their rapid spread and competitive nature , which comprises multiple invasive populations and a well-documented invasion history. The ring-necked parakeet is one of the most widely introduced parrots in the world, with successful breeding populations established in over 35 countries  and two in sub-Saharan Africa  on patterns of contemporary genetic composition for the globally invasive ring-necked parakeet  sequence data and a suite of 10 microsatellite DNA markers to examine patterns of genetic structure in the native distribution, and identify the genetic composition of invasive populations across Europe, Mauritius and the Seychelles in relation to their native sources. We then examine the observed genetic patterns to address the following questions: (i) is the genetic composition of the invasive populations a random mix of native genes originating across their Asian and African native range, or (ii) given that during invasion, parakeets have expanded their native climatic niche into colder areas, are genetic patterns associated with temperature differences between native and invasive ranges?, and (iii) can propagule pressure (as measured by records of parakeet imports for the bird pet trade) explain patterns of genetic composition of invasive populations?n = 69), Heidelberg (n = 185), Wiesbaden (n = 80), Bonn (n = 29), Dusseldorf (n = 9), Seville (n = 57), Madrid (n = 2), Greater London (n = 195), Tuscany (n = 1), Marseille (n = 2), Rotterdam (n = 75), The Hague (n = 13), Amsterdam (n = 19), Utrecht (n = 2), Mauritius (n = 115) and Seychelles , P. k. manillensis (n = 13), P. k. krameri (n = 31) and P. k. parvirostris (n = 7).Feather and blood samples from ring-necked parakeets were collected from invasive populations in Brussels  were included during the DNA extraction and PCR process. A selection of negative extractions PCRs were sequenced to ensure there was no traces of contamination in negative controls. DNA was extracted from both contemporary feather samples and historical toe-pad samples using a Bioline ISOLATE Genomic DNA extraction kit . Samples were suspended in 400 μL lysis buffer plus 25 μL proteinase K and incubated at 55 °C overnight . DNA was washed through a spin column and historical samples were suspended in 50 μL of elution buffer, whilst contemporary samples were suspended in 100 μL of elution buffer. Genomic DNA was extracted from blood using an ammonium acetate precipitation method following Nicholls et al.  to provide sequence replication from independent PCRs and detect potential artefacts or contamination . Sequences were edited in four Peaks . PCRs were conducted using differently fluorolabelled forward primers . Three loci were ambiguous to score and therefore were excluded from the analysis . Loci identified as sex-linked in echo parakeets (Psittacula echo) by Raisin et al. (Peq16 and Peq21), resulting in a total of 16 loci. Due to the degraded nature and low volume of the DNA extracted from historical museum specimens, only 10 of the 16 loci amplified . Each sample was genotyped twice to ensure consistent scoring of alleles (genotypes which could not be scored consistently were removed), and to identify potential genotype errors. Such degraded samples are known to be susceptible to genotyping errors due to allelic dropout  was assessed using microchecker 2.2.3 , to infer relationships between haplotypes from the ancestral native and invasive ranges. Haplotype frequencies and distributions in the ancestral native and invasive range were then plotted on a map using qgis  across the ancestral native range using the microsatellite data from the 10 selected loci. Ten repeated runs were conducted with K ranging from one to 10 for 500 000 iterations with a burn-in of 100 000, under the admixture model and specifying correlated allele frequencies , a further admixture analysis was performed assuming the same two putative ancestral native source populations for the assignment of invasive populations. Here, the ancestral native clusters were set as ‘known’ by activating the ‘usepopinfo’ flag, and the invasive populations were included as unknown. This approach requires the analysis to cluster the invasive populations with their ancestral native source populations  were excluded , leaving 11 populations in the final diyabc analysis . Three competing scenarios were designed where samples from the ancestral native range data were clustered into two main ancestral sources according to our structure results (K = 2) and geographic location, Asia and Africa. Our scenarios tested whether invasive populations of ring-necked parakeet originate solely from Asia (scenario 1), solely from Africa (scenario 2) or are an admixture, originating from both the Asian and African ancestral native range (scenario 3) . Scenario three includes an admixture event where the admixture rates ‘ar’ and ‘1-ar’ represent the genetic contribution of each ancestral native population  and type II  errors, and by computing the relative bias across the 500 pseudo-observed simulated data sets. Finally, to verify the goodness of fit for each scenario, model checking was implemented in diyabc to compare summary statistics between observed and simulated data sets.Analyses for each invasive population were performed using a combined data set of both mtDNA sequences and microsatellite genotypes. A total of 3 × 10ns Table . A stepwcites Trade Database . To compare the observed genetic composition of European parakeet populations derived from microsatellite data with expectations based on propagule pressure, the genetic composition of all populations within a country was averaged, as cites trade data are only available at the country level. Using the proportion of Asian/African birds documented as having been imported into each European country, and the proportion of Asian/African genes observed from the genetic data for each country, a binomial GLM was applied to test for differences between the proportions of imported and observed Asian/African genes.To place in context the resulting genetic data and patterns of invasion by ring-necked parakeets alongside the potential contribution to these patterns by releases or escapes of pet parakeets, all import records of ring-necked parakeets between 1975 and 2007 from the ancestral native ranges (Asia and Africa) were obtained for Spain, Italy, UK, Germany, Netherlands, Belgium and France from the se CITES . No equiet al. sensu Broennimann et al. During the invasion of Europe, ring-necked parakeets have shifted their climatic niche towards colder areas (Strubbe b (346 bp) gene for 696 specimens from the invasive ranges (Peq02 and Peq15). Estimated frequencies of null alleles ranged between 0.003- and 0.084% per locus. The museum specimen genotyping error rates were 3.89%, and the estimated frequencies of null alleles per locus ranged between 0.003 and 0.460%.A total of 868 bp of DNA sequences were obtained from the mtDNA control region spanning the hypervariable domain I and conserved domain II (522 bp), and cytochrome e ranges . DeviatiIn total, 44 unique haplotypes were identified from the 96 museum samples representing ring-necked parakeets across their ancestral native range. When the mtDNA sequence data derived from the ancestral native and invasive populations were combined, a total of 74 haplotypes were identified . The majstructure analysis using ancestral native range microsatellite data only revealed a ΔK statistic suggesting two distinct population clusters, one in Asia and one in Africa , with each cluster corresponding to these two continental ranges . These results were used to infer genetic clustering for use in our diyabc modelling. Using approximate Bayesian modelling, implemented with diyabc, scenario 3 was the best-supported model under a logistic regression (posterior probability >0.9) in all populations ] also supports the approximate Bayesian computation scenario, and these results were used to infer the proportions of ancestry from each ancestral native source population for each of the invasive populations. All invasive populations demonstrated a higher assignment probability to the Asian cluster, suggesting a stronger Asian (rather than African) contribution to the genetic make-up of the invasive populations  and 2007, before the EU ban on the trade of wild birds was implemented (Commission Regulation (EC) No.318/2007), a total of 109 467 ring-necked parakeets were imported from the Asian ancestral native range and 37 072 from the African ancestral native range (Table Between 1984 (the earliest ring-necked parakeet trade record available from P < 0.01). However, accounting for the known skew in propagule pressure (from Asia: 109 467 birds imported (75%) vs. from Africa: 37 072 birds (25%), Table P = 0.24). No relationships were observed between microsatellite-based estimates of the proportion of Asian/African genes observed in European countries and the proportion of Asian/African birds imported into each country .A comparison of the observed distribution of haplotypes detected across Europe (12 Asian and 2 African haplotypes) against an equal expectation  suggests that Asian haplotypes are more common across Europe than expected , the UK (31% imports vs. 60% genes), Germany (30% imports vs. 67% genes), Belgium (55% imports vs. 68% genes and France (0% imports vs. 86% genes). The proportion of Asian genes detected was lower than expected in Spain (80% imports vs. 64% genes) and the Netherlands (97% imports vs. 70% genes).r23 = 0.58, P < 0.01; haplotype prevalence across Europe log transformed). This result holds when comparing the maximum native-range latitude of haplotypes detected in Europe with haplotypes not detected . The weighted average maximum native-range latitude of haplotypes present in a European parakeet population was positively and significantly correlated with the latitude of that population . Replacing latitude with temperature consequently does not affect our results  are more prevalent in invaded Europe ; alternatively, they may be a result of admixture between ring-necked parakeets originating from different ancestral native continents. Below, we discuss the supporting evidence for each alternative explanation and their likely levels of influence on the observed patterns.et al.  introduced across the US were concordant with trapping records from the native range, suggesting that propagule pressure exerted by the international pet bird trade contributed to the distribution of genetic diversity across the monk parakeets' invasive range.Analyses of nuclear and mtDNA evidences a predominantly Asian origin for the invasive populations of ring-necked parakeets, which is consistent with expectations from the bird pet trade, as about 75% of all ring-necked parakeets imported in Europe originate from Asia. Cassey et al.  reported. et al. . Strubbe. et al.  found th. et al.  and Edel  have shown that trade can also influence biological invasions in more subtle manners (e.g. see Banks Our study has provided the first substantial insights into the ancestral origins of ring-necked parakeets across their widespread invasive range. Our findings provide strong evidence that the invasive populations predominately comprise birds of Asian ancestry, in particular from the northern areas of the ring-necked parakeets' range in Asia. Our data also suggest that a combination of nonrandom effects from prior adaptation to cold in the northern parts of the ancestral native Asian range, along with high levels of trade in birds, has influenced the signatures of ancestral origin within the invasive populations of ring-necked parakeets. This proposed eco-evolutionary scenario, shaped by a large number of importations from Asia and subsequently influenced by prior adaptation to cold climates in the ancestral native range, represents an important first step in reconstructing pathways of invasion. Our identification of the ancestral origins of invasive ring-necked parakeets provides crucial information that can be applied to further studies such as ecological niche models aimed at predicting areas at risk of invasion by this species, and ultimately to inform decision-makers tasked with developing future policy of invasive alien species. Based on our findings, such policy should, in addition to controlling global trade of wild birds, also incorporate measures to control or prohibit the commercial breeding and keeping of parrots as pets in regions outside of their native ranges. Our findings provide an important contribution for understanding the evolutionary adaptation of a globally invasive species in a novel environment.


PST/FST, would increase with residence time and secondary releases. We also explored whether interspecific competition between invaders could drive phenotypic divergence. Residence time had no significant effect on genetic diversity, phenotypic divergence, effective population size, or signatures of expansion of invasive trout. In contrast, secondary releases had a major effect on trout invasions, and rainbow trout populations mostly affected by aquaculture escapees showed significant divergence from less affected populations. Coexistence with brown trout had a positive effect on phenotypic divergence of rainbow trout. Our results highlight an important role of secondary releases in shaping fish invasions, but do not support the contention that older invaders are more differentiated than younger ones. They also suggest that exotic trout may not have yet developed local adaptations in these recently invaded habitats, at least with respect to growth-related traits.Invasion success may be expected to increase with residence time  and secondary releases , but this has rarely been tested in natural fish populations. We compared genetic and phenotypic divergence in rainbow trout and brown trout in Chile and the Falkland Islands to test the prediction that adaptive divergence, measured as  Among invasive plants, residence time and secondary releases often promote naturalization and population expansion  differentiation  or convergent (PST < FST) selection on the trait of interest may be invoked  and brown trout , in two locations in the southern hemisphere, Chilean Patagonia and the Falkland Islands  older populations with longer residence time would display stronger genetic and phenotypic differentiation than younger, more recent populations of each species and (ii) that populations aided by secondary releases would be more differentiated than those that have dispersed mostly through natural colonization.Brown trout is native to Eurasia and rainbow trout to the West coast of North America, but both species were reared in hatcheries and propagated for sport fishing and aquaculture to many countries elsewhere  rainbow trout collected from 15 streams in Chile and 187 wild brown trout collected from six stream Chile and three streams in the Falkland Islands during 2007–2009 Fig.  for ChilAll rainbow trout had previously been genotyped for seven microsatellite loci, and the extent of admixture with secondary releases from farmed escapees had been estimated for each study river  – and two markers (MHCI and TAP2A) tightly linked to the MHC class I and TAP genes, respectively  or separately , all analyses were performed with the total set of 14 markers.Total genomic DNA was extracted from brown trout samples with the Wizard® SV96 Genomic DNA purification kit  following the manufacturer's instructions and 14 di- and tetranucleotide microsatellites were PCR amplified . These included 12 putatively neutral markers – genemapper 4.0 .PCR amplifications were carried out in two multiplex reactions  of 11 μL, using the QIAGEN Multiplex PCR kit  and 3 μL of extracted DNA (∼20 ng), following the manufacturer's recommendations. PCR products were diluted 1:10 in water and resolved on an Applied Biosystems ABI3130xl Genetic Analyser . Fragment length was determined using the GeneScan 500-LIZ size standard and scored using micro-checker 2.2.3 , allelic richness based on 10 diploid individuals , and unbiased expected heterozygosity .Allelic data for brown trout were screened for genotyping errors using Ne) of brown trout were obtained by two different methods, using a full likelihood method based on sibship assignments and random mating implemented in colony 2.0 , we computed 100 iterations with a burn-in of 25 000 and 75 000 MCMC replicates using the admixture model with allele frequencies correlated. To assess the most likely number of clusters, we calculated ΔK following Evanno et al.  was used to partition variation among- and within-population components using the program arlequin v3.5  relative residence time  inferred from the presence/absence of native galaxiid fishes. Given that brown trout tends to drive native galaxiids to extinction  level of admixture with farm fish  coexistence with brown trout (present versus absent), and (iv) relative residence time (age of each population). Residence time was inferred from the relative abundance of ‘aquaculture alleles’ in the population using a median cutoff point of 0.6 to classify populations as ‘recent’ (q > 0.6) or ‘old’  between seven populations of rainbow trout and five populations of brown trout at four size-related phenotypic traits that are likely to show divergence during the colonization of novel geographical ranges with different growing conditions: (i) condition factor  with neutral molecular differentiation . The observed value of PST/FST was then compared with the simulated PST/FST to determine whether it fell outside the simulated distribution. Computations were performed in R following the codes provided by Holand et al. (h2) and between (c) populations (Brommer c) was included to allow for environmental between-population variance, whereby small values of c  indicate that the phenotypic variation is mostly influenced by environmental effects, and large values of c  indicate that only genetic variation has contributed to phenotypic differences. We estimated PST according to Brommer −1 with a random number drawn from the chi distribution having (a–1) degrees of freedom (a being the number of populations). Samples of FST, h2, , and PST/FST. This was repeated 1000 times to generate a sampling distribution of PST/FST under neutrality, which was then used to compare observed PST/FST for different values of c, ranging from 0 to 1. The critical value for c  was determined, and if this was less than h2, PST was deemed to be significantly higher than expected under neutrality  as well as between Chilean and Falkland populations (n = 5). For rainbow trout , PST/FST was calculated among all populations  had some missing data in the Falklands populations and one tetra-nucleotide marker (Ssa171) presented some alleles that differed only in two base pairs, probably due to the compound motif GTGA + GT. The exclusion of these markers did not change our results; hence, we retained them in the analyses. No evidence of null alleles, stuttering, or allele dropout was detected for any microsatellite, and no marker deviated significantly from HWE after sequential Bonferroni correction in more than one population (data not shown). Analysis of linkage disequilibrium was significant in only three of 819 pairwise comparisons (between loci and populations). There was no evidence for outliers under divergent selection with either lositan or bayescan (Table S3a).Three microsatellite loci  were varied among populations, with a tendency to be lower in the Falkland Islands than in Chile  and observed heterozygosity (Ho) were significantly different between all brown trout populations  and the Falkland Islands  considered as a whole . Similarly, we found no significant differences in relatedness , FIS  or global FST among populations , although Dest values were lower in Chile  than in the Falklands . However, it should be noted that the low number of populations analyzed in the Falklands, combined with their different origins (see Results from structure below), could limit our ability to detect significant differentiation between Chile and the Falklands.Diversity estimates  using colony and onesamp were highly correlated  and yielded small sizes (Ne < 50) for all brown trout populations in all cases (Table P = 0.025), characterized by negative FIS values (FIS = −0.015), while population expansion was only detected in one Falkland population .Our two estimates of effective population size  to 0.390 . Pairwise Dest values were positively correlated with FST values . Pairwise FST values estimated with neutral and gene-linked markers were strongly correlated with pairwise differentiation estimated with all markers combined . There was no evidence of IBD . structure showed two genetic clusters (K = 2), but these did not exactly match with the two broad geographical areas analyzed. The first cluster included all Chilean populations and Estancia Brook , while the second cluster comprised the two other Falkland populations , splitting the first cluster identified by structure into five independent clusters . We also found significant differentiation among populations with respect to condition factor , number of circuli deposited in the scales during the first freshwater year , and scale size at the end of first year .Brown trout ranged between 47 and 556 mm in fork length; the minimal adequate mixed-effects model that explained variation in the spacing between consecutive scale growth rings included population as the only significant fixed term . Similarly, variation in PST/FST was unrelated to geographical distance for all traits (Table S5).The contribution of environmental effects to phenotypic variance was low only for condition factor, as evidenced by the fact that  Brommer , diverge c Table , likely lositan or bayescan that could be indicative of divergent selection (Table S3b). In general, rainbow trout showed similar levels of heterozygosity (Ho) and allelic richness (AR) than brown trout  revealed small population sizes, similar to those of brown trout .Analysis of microsatellite data for rainbow trout  and age  as fixed factors and an interaction between population and individual fork length . As with brown trout, rainbow trout populations also showed significant differences in the three other growth-related traits examined, that is, condition factor , number of growth circuli deposited during the first freshwater year , and scale size at the end of the first year .Rainbow trout ranged between 50 and 245 mm in fork length, and the minimal adequate linear mixed-effects model that explained variation in scale intercirculi spacing included population .tor Fig. A. In conned Fig. A. None ored Fig. B, suggester Fig. C, suggester Fig. . As withPST/FST comparisons to assess such predictions in two invasive salmonids, rainbow trout and brown trout, screened for microsatellite DNA variation and growth-related traits in rivers of Chilean Patagonia and the Falkland Islands. Using PST as a phenotypic analogue for QST has limitations , and in which our assignment grouped with Chilean populations of presumably older age. Such a result is consistent with what is known about multiple origins of brown trout in the Falklands: an initial introduction likely from German origin (Estay et al. Whatever the precise reasons for the increased In their native range, brown trout populations tend to be highly structured and even populations in nearby streams often show significant differentiation conductive of local adaptations (Bernatchez h2 of 0.25 for body size and growth rate in freshwater based on salmonid studies carried out mostly in captivity (Garcia de Leaniz et al. h2 of 0.31 for rainbow trout and 0.26 for brown trout in our study, not markedly different from the value of 0.25 used in our PST/FST simulations. Future studies might benefit from measuring additional traits, ideally under common garden conditions, and to compare ancestral and invasive lineages in order to tease apart the effects of founder effects, local adaptations, and phenotypic plasticity (Leinonen et al. The capacity to grow quickly has been flagged as an important determinant of invasion success Townsend  because PST/FST comparisons between rainbow trout living in sympatry or in allopatry with brown trout were significantly higher than 1 in three of the four growth-related traits examined, suggesting that competitive interactions may have resulted in adaptive divergence of rainbow trout when these two invaders were translocated together with the southern hemisphere.Rainbow trout exhibits a wider geographical range than brown trout in Chile (Young et al. PST/FST comparisons provides insights into the nature of diversifying forces acting during fish invasions.In summary, residence time did not explain well the observed patterns of genetic and phenotypic divergence among invasive trout in our study, as some of the youngest populations were also the most genetically diverse ones. Although the conditions necessary for adaptive divergence appear to exist (i.e., high genetic variability, high population structure, and habitat heterogeneity at the relevant spatial scales – see Young et al.


Culicoides brevitarsis is a vector of the bluetongue virus (BTV), which infects sheep and cattle. It is an invasive species in Australia with an assumed Asian/South East Asian origin. Using one mitochondrial marker  and six nuclear markers, we inferred population genetic structure and possible incursion pathways for Australian C. brevitarsis. Nine mitochondrial haplotypes, with low nucleotide sequence diversity (0.0–0.7%) among these, were identified in a sample of 70 individuals from seven sites. Both sets of markers revealed a homogeneous population structure, albeit with evidence of isolation by distance and two genetically distinct clusters distributed along a north-to-south cline. No evidence of a cryptic species complex was found. The geographical distribution of the mitochondrial haplotypes is consistent with at least two incursion pathways into Australia since the arrival of suitable livestock hosts. By contrast, 15 mitochondrial haplotypes, with up to four times greater nucleotide sequence diversity (0.0–2.9%) among these, were identified in a sample of 16 individuals of the endemic C. marksi . A phylogenetic tree inferred using the mitochondrial marker revealed that the Australian and Japanese samples of C. brevitarsis are as evolutionarily different from one another as some of the other Australian species  are. The phylogenetic tree placed four of the species endemic to Australia  in a clade, with a fifth such species (C. bunrooensis) sharing a common ancestor with that clade and a clade comprising two Japanese species . Culicoides variipennis species complex and the subgenus Culicoides  of a C. brevitarsis individual from Grafton  have been presented C. brevitet al. .Primary sequencing reads were assembled into contigs using Pregap4 and Gap4 from the Staden package  and the nd Nei’s  nucleotind Nei’s  to obtaind Nei’s ). StandaCulicoides species previously deposited into GenBank, covering the same 547bp region as the C. marksi haplotypes reported in this study, were also included , 335bp , or 339bp  with our C. brevitarsis haplotypes. Reducing the length of the alignment of our C. brevitarsis mtDNA COI region to nucleotide positions 1 to 339  also reduced the total number of C. brevitarsis mtDNA haplotypes identified from nine to seven   .The mtDNA COI haplotype of the individual from Grafton [GenBank: KJ162974] is likely to be Cbrev-01 or Cbrev-05  and nucleotide sequence diversity (π)) in C. brevitarsis (based on 835bp) and C. marksi (based on 547bp), and the Analysis of Molecular Variance (AMOVA)   were, suC. marksi  of the mtDNA marker from Culicoides species sampled in Australia and those available from GenBank  to 0.264 ± 0.020 SE ). When third codon sites were excluded (reason given below), the genetic distances between the species were much lower  to 0.172 ± 0.021 SE (C. actoni vs. C. jacobsoni)). The average genetic distances within species with at least two haplotypes ranged from 0.0  to 0.065 (in C. matsuzawai) across the trimmed 547bp region. Differentiation of Culicoides species based purely on mtDNA COI sequence divergence may be impossible  while the maximum intra-specific genetic distance is 0.082   due to itarsis) , a diffeh) and nucleotide sequence diversity (π) were both higher for the Australian endemic C. marksi  than for the Australian C. brevitarsis . We did not detect any isolation-by-distance effect between the Australian populations of C. brevitarsis based on the mitochondrial DNA COI partial gene marker, with these populations lacking significant substructure as indicated by a low FST value (FST = 0.026), and non-significant correlation between geographic distances and FST/(1 –FST) values (R2 = 0.0016), possibly due to the wide geographical distribution of the Cbrev-01 haplotype (FCT (among groups), FSC (among populations within groups) and FST (within populations) , providing the reason for the lack of polymorphisms for these two EPIC DNA markers. This, therefore, leaves the availability of four EPIC markers  as well as two microsatellite DNA markers  to infer the population genetic structure of C. brevitarsis.Two exon-primed intron-crossing (EPIC) DNA markers  were found to be monomorphic across all the populations of C. brevitarsis were largely in agreement with those obtained from the mtDNA marker, with the exception that the fixation index for the among populations within groups comparisons (FSC = 0.020) was significant at both the mean and lower estimates, but not at the higher estimate . The availability of results from analyses of nuDNA markers enabled a fine-scale investigation of within population variation, which showed that 93.3% of the variation was at the within individual level relative to the total population (FIT) level  level . Pair-witructure  due to tstimates , no sign2 = 0.192, P value = 0.0152), indicating that neighbouring populations tended to be genetically more similar to one another than they are to distant populations. Overall, the six nuDNA markers appeared to assort independently, and using Fisher’s exact test did not disclose any departure from Hardy-Weinberg equilibrium, the only exceptions being Cimi-85 for Kalumburu and Douglas-Daly, and RpS6 and RpL27A for Paterson .Significant isolation-by-distance was detected using the nuDNA markers  and genomes with predominantly uni-parental inheritance mode  should be interpreted with caution C. brevitC. brevitarsis samples from northern and southern Australian sites  is a single species with low nucleotide sequence and haplotype diversities across >800bp of this genome. There is no support for the notion that C. brevitarsis in Australia is a set of cryptic species. Culicoides brevitarsis has been recorded in Australia for over 100 years and is believed to be an introduced species  and Cbrev-05 [KP201848] are t study, , and [61(XLSX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.