Mantella madagascariensis group is composed of two rainforest and three swamp forest species of poison frogs. We first confirm the monophyly of this clade using DNA sequences of three nuclear and four mitochondrial genes, and subsequently investigate the population genetic differentiation and demography of the swamp forest species using one mitochondrial, two nuclear and a set of nine microsatellite markers. Our results confirm the occurrence of two main mitochondrial lineages, one dominated by Mantella aurantiaca  and the other by Mantella crocea + Mantella milotympanum. These two main lineages probably reflect an older divergence in swamp Mantella. Widespread mitochondrial introgression suggests a fairly common occurrence of inter-lineage gene flow. However, nuclear admixture seems to play only a limited role in this group, and the analyses of the RAG-1 marker points to a predominant incomplete lineage sorting scenario between all five species of the group, which probably diverged relatively recently. Our demographic analyses show a common, severe and recent demographic contraction, inferred to be in temporal coincidence with the massive deforestation events that took place in the past 1000 years. Current data do not allow to conclusively delimit independent evolutionary units in these frogs, and we therefore refrain to suggest any taxonomic changes.Madagascar is a biodiversity hotspot particularly rich in amphibian diversity and only a few charismatic Malagasy amphibians have been investigated for their population-level differentiation. The  Mantella [Madagascar is home to an almost unparalleled diversity of flora and fauna, with the majority of its native species being endemic to this island . AmphibiMantella ,17.Mantella bernhardi, M. expectata and, to a shallower extent also in Mantella viridis [Mantella species of the eastern rainforest [Mantella species and in the tomato frogs of the genus Dyscophus [Mantella species [Phylogeographic studies in amphibians often identify limited gene flow among populations and a genetic structure that correlate with their geography and distribution ,19,20, w viridis ,16,21). inforest ,23; rapiyscophus ,17, and  species ,25.Mantella are probably among the best-studied group of Malagasy amphibians [Due to their usually bright aposematic coloration  and we investigate the population genetics of this group to explore this hypothesis. According to current taxonomy, this group consists of two rainforest species, M. madagascariensis and M. pulchra, and three swamp forest species M. aurantiaca, M. crocea and M. milotympanum [Mantella aurantiaca is characterized by a uniform and translucent orange coloration  and a ventral surface uniformly orange. Mantella crocea shows a lateral black coloration, a frenal stripe, a ventral black color with a variable number of markings that can be grey, bluish-white or yellowish, and a dorsal color being yellow-brown in the more southern populations and bright green in the populations of the western and northern portion of its range. Populations with intermediate patterns between Mantella crocea and M. milotympanum  based on the presence of the black tympanic region and a uniformly orange ventral surface and on the lack of both lateral black coloration and frenal stripe. The population of Andaingo was assigned to M. crocea based on the presence of a lateral black coloration, a frenal stripe and a ventral black coloration with sparse grey, yellowish-white markings  [2), the ongoing decline in the extent and quality of their habitat and their possible over-exploitation in the pet-trade. On the contrary, M. crocea is listed as of Least Concern due to its relatively wide extent of occurrence and presumed large population [M. crocea and M. milotympanum (and to a lesser extent between M. crocea and M. aurantiaca) and their radically different IUCN Red List categorization it is important to investigate the degree of differentiation of these species and assess their taxonomic status, given that most studies to date focused on only mitochondrial genes and did not cover the entire known distributional range of these species.In this study we focus on the tympanum . Mantellloration . MantellAndaingo ) were asew palms . These stympanum ,23. Mante (IUCN) . This ispulation . Due to M. madagascariensis group for which we had a complete extended molecular dataset.Although there is still no consensus on the time of human colonization of Madagascar  extending the known distribution of this species substantially. Twenty-three samples of Mantella spp. representing all the currently described species and the recently identified cryptic lineages were used for the phylogenetic analyses (details below).Two-hundred and fifteen tissue samples of individuals of the p (sensu ) were an. crocea , with thM. crocea from Zahamena) or femur muscle from collected voucher specimens, all collected between 2002 and 2009 during several field expeditions along the eastern coast of Madagascar and stored in 96% EtOH. Sampling and tissue sample export permits were approved by the Ministère de l’Environnement et des Forêts of Madagascar.Tissue samples were either toe clips from subsequently released individuals, saliva swabs (COB) gene of ca. 600 nucleotides, a fragment of the nuclear recombination activating gene 1 (RAG-1) of ca. 750 nucleotides, and a fragment of the nuclear recombination activating gene 2 (RAG-2) of ca. 500 nucleotides , and of the mitochondrial cytochrome oxidase subunit 1 (COX1), 12S rRNA and two fragments of 16S rRNA genes were sequenced for all known Mantella species to ascertain the monophyly of the M. madagascariensis group within the genus  digestion following a standard saline method . For theleotides . In addi®, and 2.5 µL 5x Green GoTaq® Reaction Buffer (Promega). Primers and PCR amplification conditions in PCRs were performed in a final volume of 11 µL and using 0.3 µL each of 10 pmol primer, 0.25 µL of total dNTP 10 mM , 0.08 µL of 5 U/mL GoTaqThe same tissue samples that were used for the phylogeographic analyses were genotyped for nine microsatellite loci . DetailsCOB sequence of M. baroni (AY862201) was added to the COB alignment. A Neighbor-Joining (NJ) tree based on uncorrected p-distances was constructed with MEGA, version 7.0.9 [COB sequences of M. aurantiaca from the captive-bred colony housed in the breeding facility managed by Association Mitsinjo in Andasibe) . A homologous on 7.0.9  to gain ndasibe) . All newCOB sequence dataset by confirming the absence of stop codons in the analyzed fragment. Because the RAG-1 and RAG-2 alignments contained heterozygous positions we phased genotypes to identify haplotypes for further analyses using the PHASE algorithm (version 2.1.1) with default settings [COB, RAG-1 and RAG-2 fragments and computed Tajima’s average number of pairwise differences . PHASE nces  and hapnces  for eacnces  and concatenated for analysis. Because mitochondrial introgression has previously been detected in Mantella [COB and 3rd position of COX1, HKY+I; (2) 2nd position of COB, GTR+G; (3) 12S and 3rd position of COB, GTR+I+G; (4) 1st position of COX1, GTR+G; (5) 2nd position of COX1, SYM+I; (6) 16S, GTR+I; (7) intervening tRNAs  between 16S and 12S, GTR+G. Bayesian inference (BI) phylogenetic analysis was subsequently run in MrBayes [DNA sequences of four mitochondrial and three nuclear genes were sequenced from one individual . Prior to calculating haplotype relationships using networks, we analyzed the nuclear RAG-1 and RAG-2 datasets with the Phi test of Bruen et al. [p-values > 0.1) and thus they were used for network reconstruction. We used TCS version 1.21 [COB haplotypes and of the RAG-1 and RAG-2 inferred haplotypes (COB fragment. Loops that occurred in the network were resolved by (1) treating connections with singletons and/or rare haplotype to be less likely than connections with central and frequent haplotypes [Individual n et al.  as implen et al.  to assesion 1.21  to analyplotypes . With thplotypes  and (2) plotypes .4 permutations to assess significance. The average number of alleles per locus, allelic richness (AR), expected (HE) and observed (HO) heterozygosities and inbreeding coefficients (FIS) were calculated using MSA v. 4.05 [The presence of null alleles was tested with MICRO-CHECKER . Linkage v. 4.05   [ST between sampling localities was also computed with MSA with 104 permutations to assess significance     with 100e (BAPS)  was calcificance . We also−4 [−2 and 10−6. Each Msvar was run for each demographic scenario for 400 million steps of the MCMC algorithm. For each sampling locality three independent runs (one under each demographic prior) were analyzed for convergence using Gelman and Rubin’s statistic [Due to the conservation concerns on these species we carried out analyses of the demographic history of these populations to determine whether they present robust effective populations sizes that have been stable across time and thus maintained their evolutionary potential. For this purpose, the demographic history of the nine localities with the largest sample sizes and no more than 10% missing data was estimated with Msvar 1.3 ,71. Msva−4 ,73,74 altatistic  implementatistic  in R [77M. madagascariensis group  together form a monophyletic group within the genus Mantella, we performed a phylogenetic analysis based on DNA sequences of multiple genes. To exclude effects of mitochondrial introgression, we analyzed mitochondrial and nuclear genes separately. The phylogenetic trees obtained from BI analysis of the concatenated nuclear and of the mitochondrial data sets  was sister to a clade containing the M. betsileo group , M. laevigata group  and M. madagascariensis group. The nuclear DNA analysis failed to unambiguously resolve relationships among the M. laevigata and M. betsileo groups, probably due to missing data for M. manery for which only a RAG-1 sequence was available. Similarly, relationships within the species groups did not receive significant support in the nucDNA analysis. However, both analyses provided high support for monophyly of the M. cowani group and of the M. madagascariensis group.To understand if the target species of this study, defined as the ata sets a,b both COB, 215 individual sequences and a total length of 552 nucleotides; RAG-1, 211 individual sequences (422 after phasing) and a total length of 732 nucleotides; RAG-2, 21 individual sequences (42 after phasing) and a total length of 531 nucleotides. In all the three alignments we did not detect any gaps, and the translation into amino acids resulted in neither nonsense nor stop codons. In the COB alignment we found 81 (14.7%) variable sites (out of 552), among which 69 were parsimony-informative and 12 were singletons, and a total of 49 haplotypes were identified  were variable (8.1%), among which 51 were parsimony-informative and 8 were singletons, and a total of 78 haplotypes were identified  were variable (5.1%), among which 16 were parsimony-informative and 11 were singletons, and a total of 17 haplotypes were identified , while the Hd values of the analyzed populations of M. aurantiaca and M. milotympanum were very variable, ranging from 0 to 0.684 in M. milotympanum and from 0 to 0.752 in M. aurantiaca  values were on average lower than the estimated π at the COB fragment for M. aurantiaca and M. crocea and higher for M. milotympanum, M. madagascariensis and M. pulchra , it is worth noting that in this alignment the highest π was observed in the population from Ampangadimbolana of M. crocea  for the three genes was: R01–R78; . In the d 01–17; . In the rantiaca . The nucof π see . In the ulations . RAG-1 nchra see . Althougocea see . Nucleottive see , suggesttive see , and aretive see , suggestCOB sequences suggests several instances of introgression of the M. crocea mitochondrial genome into the populations of M. aurantiaca of Andranomandry and Besariaka, and of introgression of M. pulchra mitochondrial genome into the population of M. aurantiaca of Torotorofotsy , the northernmost population known for this species. This analysis also shows that the northern populations of M. madagascariensis share the mitochondrial genome with M. pulchra   and some sequences of M. aurantiaca from Andranomandry and Besariaka. The third network is mostly composed of sequences on M. aurantiaca from its entire distributional range, but it also includes one haplotype of M. crocea from Ambohitantely , and at least 23 mutational steps to be linked to the M. crocea/M. milotympanum network  group together, and 10 mutational steps link this group of haplotypes to all the others. See The haplotype network of the pe (C41) . One netRAG-1 alignment, which included all the five species of the M. madagascariensis group  and M. madagasariensis. Haplotype R10 and R15 are uniquely found in these individuals. Other RAG-1 haplotypes found in these introgressed individuals are: R1, widely shared by all analyzed species; R3, shared by all species of the M. madagascariensis group with the exception of the southern population of M. madagascariensis; R4, mostly found in the brown populations of M. crocea but also found in M. milotympanum, M. aurantiaca and in the southern population of M. madagascariensis; R5, mostly found in M. aurantiaca populations from Andranomandry and Besariaka, but also found in the M. crocea population from Andasibe and in the population of M. madagascariensis from Ranomafana; R6, exclusive of M. aurantiaca populations of Andranomandry and Besariaka; R12, mostly found in M. milotympanum but also found in the M. aurantiaca population of Besariaka, in the population of M. crocea of Ambohitantely (green phenotype) and in the southern population of M. madagascariensis  and with M. pulchra  and Ampangadimbolana (brown phenotype), but also with another individual of M. aurantiaca from Torotorofotsy (Only one network was retrieved for the phased is group . The throcea see  share twocea see . Most ofariensis . The ind pulchra . In the orofotsy .M. madagascariensis from the North (Besariaka) mostly share haplotype R18  and R19 . Other RAG-1 haplotypes found in this population are: R21, also found in one population of M. aurantiaca and M. milotympanum and in the population of M. madagascariensis of unkown origin); R67, also found in the population of M. madagascariensis of unkown origin; and R68, uniquely found here (M. madagascariensis of unknown origin (but showing a pattern of genetic variability similar to the population of M. madagascariensis from Besariaka) we found the following RAG-1 haplotypes: R1, R2, R3, R19, R21 and R67 as discussed above; R65, found also in the population of Andriambe of M. milotympanum and M. pulchra; and R73, uniquely found in this population  haplotypes R36, R40, and R41 are uniquely found in the population of M. crocea from Ambohitantely; and (ii) R57 and R56 in the M. crocea population of Hevirina (both of them showing the green phenotype); (iii) haplotype R47 was found in the population of M. crocea from Ampangadimbolana (with the brown phenotype); (iv) haplotypes R10, R13 and R17 plus haplotypes R49 and R50, and haplotype R59, are found in the population of M. aurantiaca from Besariaka, M. crocea from Ampangadimbolana (brown phenotype) and M. crocea from Zahamena (green phenotype), respectively. Similar to what was observed in the COB network, the population of M. crocea showing a more consistent genetic differentiation from the others is the northernmost known population of Hevirina (cf. RAG-1 haplotypes R56 and R57). See RAG-1 haplotype frequencies and distribution.All the RAG-2 fragment was amplified only for a small subset of individuals from six populations , mostly to verify if other nuclear genes display a pattern of differentiation comaparable to that in RAG-1. The phased RAG-2 sequences grouped into a single network, although the genetic differentiation of the RAG-2 haplotypes might be slightly higher compared to RAG-1 . In all cases this lack of HWE was due to a deficit of heterozygotes, in particular in loci G10X, B8 and M14. Such pattern could be indicative of the presence of null alleles on these loci, however, we found no significant difference in estimates of genetic variation and inbreeding coefficients when excluding them , thus we retained these loci for further analyses. No significant linkage disequilibrium within any of the sampling localities was detected after Bonferroni correction for multiple testing, with the exception of the pairwise comparison between loci A9 and B7 in the M. milotympanum population of Andriambe . Excluding the M. crocea sampling site of Ambodivoasary due to its small sample size, the number of alleles per locus ranged between a minimum of 6.11 and 12.78 across localities, the observed and expected heterozygosity were relatively high, ranging between 0.46 and 0.74, and 0.77, and 0.88, respectively (We tested for Hardy–Weinberg Equilibrium (HWE) in the nine microsatellite markers studied by sampling locality. At all localities included in the microsatellite analysis, except for the ectively . The inbectively  in the dM. aurantiaca, i.e., (1) Andranomandry and Besariaka, (2) Sahasarotra, and (3) Torotorofotsy. The M. crocea samples formed three additional clusters: (4) Ambodivoasary, (5) Ambohitantely, and (6) Ampangadimbolana. Lastly, cluster (7) was formed by the M. milotympanun samples from Fierenana-Sahamarolambo, Andriambe and Savakoanina . The same results were obtained for three independent BAPS runs indicating strong support for the pattern of population structure identified. These included three clusters of akoanina . With thdmixture . The gendmixture , howeverST showed that most of the comparisons were significant after Bonferroni correction  slightly smaller than the average between species FST (0.07). The observed low differentiation between sampling localities was reflected by the average low frequency of private alleles, namely 0.0819. These values reflect either recent gene flow between populations, or rather little divergence from the ancestral population, also reflected by the low statistical support in the dendrogram depicting the relationships between sampling localities , RAG-1 (with widespread haplotype sharing between these taxa) and RAG-2 (with 1 widespread shared haplotype between M. aurantiaca and M. milotympanum)  .COB haplotypes uniquely identified in the southern populations of M. aurantiaca that cluster in the M. crocea/M. milotypmpanum phylogroup , and one haplotype uniquely identified in the Torotorofotsy population of M. aurantiaca that clusters with the M. pulchra/M. madagascariensis (haplotype C11) network (M. aurantiaca in M. crocea (green population from Ambohitantely), with haplotype C17 being nested within the M. aurantiaca network, and therefore confirming mitochondrial introgression happening in both directions between these taxa  and northern (Torotorofotsy) edge of the known distribution. Two of the southern populations of M. aurantiaca (Andranomandry and Besariaka) formed a single cluster in our microsatellite analysis  may form a genetically coherent unit also from a nuclear DNA perspective , whereas M. milotympanum populations vary greatly in the extent of the black color around the tympanic area and in the overall coloration (predominantly greenish in the southern and orange in the northern part of their range), despite their restricted distributions. Here we confirm fairly common COB haplotype sharing between M. milotympanum and M. crocea. Although the majority of the analyzed individuals of M. milotympanum have haplotypes that are poorly differentiated, they are different from the haplotypes found in the populations of M. crocea  and recent gene flow   . At the ivergent . Despiteivergent , and recM. madagascariensis group is inevitably a highly controversial matter. In the studies available to date , the current data do not allow to conclusively delimit independent evolutionary units in the entire complex, and therefore we do not see a simple answer in immediate reach to clarify the uncertain taxonomic status of M. crocea and M. milotympanum. Given the conflicting genetic results, but also the importance of these species in conservation and their listing in the Convention on the International Trade in Endangered Species (CITES), a certain stability of the (necessarily inconsistent) current taxonomy is important and we therefore here choose not to propose—and strongly discourage—any premature nomenclature and/or taxonomic changes in this group [A taxonomic resolution of closely related species complexes such as the to date  sequencing. Similar to our results, their study found clear genetic clusters that did not align with current species designations, and supported a substantial genetic differentiation between yellow- and green-colored populations of M. crocea. However, the RADseq data [M. crocea specimens with M. aurantiaca, not recovered by our study. These results reinforce our conclusion that the taxonomy of this complex of frogs is convoluted but without an obvious and simple resolution in sight, despite an increasing body of detailed population genetic and population genomic data.While the present paper was under final review, Klonoski et al.  publisheseq data —obtainedM. madagascariensis did not form a single mitochondrial network. The southern populations were extremely homogeneous (only one single haplotype was identified from Ranomafana), whereas, the samples of M. madagascariensis from the central east  show haplotype sharing and shallow mitochondrial differentiation with the chromatically different M. pulchra . The Ranomafana population could not be included in the multi-gene phylogenetic analysis , pet trade over-collecting can exacerbate this threat and therefore requires careful regulation. Our data exemplify how the massive past forest reduction has drastically reduced the effective population size of amphibian species, and highlight the importance of fine-scale conservation genetic assessments of the remaining fragmented populations of these species.Inferring the demographic history of one species is crucial to better understand how present-day genetic diversity is distributed . A recen to 2003 ,30, with species ,87,88,89


Salamandra salamandra in peninsular Italy. Both mitochondrial and nuclear markers clearly identified two main population groups. However, nuclear and mitochondrial zones of geographic transition between groups were located 600 km from one another. Recent population declines in central Italy partially erased the genetic imprints of past hybridization dynamics. However, the overall pattern of genetic variation, together with morphological and fossil data, suggest that a rampant mitochondrial introgression triggered the observed mitonuclear discordance, following a post-glacial secondary contact between lineages. Our results clearly show the major role played by reticulate evolution in shaping the structure of Salamandra salamandra populations and, together with similar findings in other regions of the species’ range, contribute to identify the fire salamander as a particularly intriguing case to investigate the complexity of mechanisms triggering patterns of mitonuclear discordance in animals.Discordance between mitochondrial and nuclear patterns of population genetic structure is providing key insights into the eco-evolutionary dynamics between and within species, and their assessment is highly relevant to biodiversity monitoring practices based on DNA barcoding approaches. Here, we investigate the population genetic structure of the fire salamander  In practice, however, discordant patterns of variation among characters and among markers are not uncommon (e.g.6 among others). Several processes have been involved with the formation of such discordant patterns of variation, including various forms of selection, adaptive introgression, demographic disparities, hybrid zone movements, and sex-biased processes10. Consequently, discordance per se is emerging as a tremendous source of insights into the evolutionary process.In principle, concordance between distinct phenotypic traits and/or genetic markers is a plausible expectation when analysing geographic patterns of biological diversity, above and below the species level. Derived from the shared history of individual characters of organisms, this expectation forms the basis for the extensive use of single markers  to draw inferences about the evolutionary history of populations and species13, to the extent that a comparative approach using both mitochondrial and nuclear genetic data is becoming customary in phylogeographic investigations14. At the same time, however, after more than three decades when most phylogeographic studies adopted a single-marker approach (since15), there is now a huge amount of mtDNA data which needs to be complemented, in order to reach reliable conclusions about the evolutionary history and current genetic structure of populations. Furthermore, integrating mtDNA data with those drawn from the nuclear genome also has major practical implications. Indeed, mtDNA has been widely employed to revise classical taxonomy16, and to define conservation strategies for species and populations threatened by human impacts on the natural environment17. While in most cases such integration will hopefully lead to only slight revisions of previous conclusions based on mtDNA data, there are compelling examples of the far reaching implications of a more integrative experimental approach to the study of population structure and history7.The drawbacks of using mitochondrial DNA (mtDNA) as the sole marker of genetic variation among and within populations are now widely acknowledgedSalamandra salamandra  is a temperate amphibian largely distributed in Europe18. Owing to its remarkable phenotypic variation in traits encompassing external morphology, colour patterns, and reproductive strategy, the geographic variation and population structure of S. salamandra have been investigated in several portions of its range, using various combinations of phenotypic and genetic traits20. As a consequence, the taxonomy of fire salamanders has been long discussed and repeatedly revised. Once regarded as a single highly polytypic species, the fire salamander group is now recognized as made up of four distinct species, with more than 10 sub-species within S. salamandra alone19. At the same time, conflicting patterns of variation between traits have been frequently observed, and their analysis has formed the basis for intriguing insights into processes of reticulate evolution, range-change dynamics, and life-history traits evolution23. Consequently, the fire salamander is emerging as a compelling system for studying the contribution of multiple processes to the formation of intraspecific patterns of biological diversity20.The fire salamander S. salamandra in peninsular Italy, a geographic area where instances of discordance between morphological traits and preliminary mtDNA data were previously observed24, without being reconciled into a population history, and whose underlying causes remain unclear. Based mostly on differences in colour patterns and body shape, fire salamander populations occurring along the Italian peninsula have long been attributed to the endemic subspecies S. s. giglioli, whereas populations from the pre-alpine and alpine areas have been attributed to the nominal subspecies S. s. salamandra26, with some intergradation between the two subspecies through the Liguria region  assess the population genetic structure of the fire salamander throughout the Italian peninsula, (2) get a comprehensive understanding of the pattern of discordance observed between phenotypic traits and mtDNA data, and (3) shed light on its possible causes in these salamanders.Nuclear genetic variation was investigated at level of 23 allozyme loci Table . Five loS. s. gigliolii and the nominal subspecies S. s. salamandra, respectively. The geographically intermediate sample 16 was the only one showing substantial evidence of admixture between both groups. When the best clustering option for K = 3 was considered  was 582 bp in length, with 23 variable positions of which 21 were parsimony informative and the cytochrome oxidase subunit I gene fragment (hereon COI) was 638 bp in length, and showed 29 variable positions, of which 24 were parsimony informative. Twenty-five unique haplotypes were identified in the concatenated dataset, whose distribution among the sampled populations is shown in Table The final mtDNA sequence alignment comprised 1220 bp for all the 158 The mtDNA haplotype genealogy estimated using HaplotypeViewer is presented in Fig. Finally, the two sub-groups found within the southern lineage at the level of the nuclear dataset Fig. , have alS. salamandra occur along the Italian peninsula. However, while populations marking the geographic transition between groups have been observed both with mitochondrial and with nuclear markers (samples 8 and 16), their respective geographic locations were more than 600 km apart , show that two main lineages of see Fig. .32), but the extent of discordance observed in the present study is conspicuous. The geographic displacement between mitochondrial and nuclear contact zones among the two main lineages, largely exceeds the extent of discordances previously noted among fire salamander lineages from different geographic regions23, and has no parallels among different taxa from peninsular Italy. Interestingly, both mtDNA and nuclear contact zones are located within well-known suture zones (sensu33), where interspecific and intraspecific hybrid zones and range edges have been previously reported for various taxa, including amphibians (e.g.37). Therefore, lines of cross-taxon concordance cannot be used here as inferential clues in the attempt to reconcile such discordance into a population history.Mitonuclear discordances are not uncommon in amphibians (e.g.24), suggests that the northern lineage  colonized the Apennines as the last step of a large-scale range expansion out of the Balkans into Western Europe24. Here, it underwent a secondary contact with the southern, peninsular endemic lineage (namely S. s. gigliolii), most likely during the post-glacial epoch24. But where did the two lineages first meet and mate? And what processes might best explain the observed mito-nuclear discordance? At least two conflicting scenarios could be delineated in this respect. The first that the secondary contact between both lineages first occurred in the north-western Apennines, as depicted by nuclear data . For example, in a similar case concerning a Triturus newts’ hybrid zone with extensive mito-nuclear discordance, Wielstra and colleagues32 found extensive nuclear clines - and introgression of multiple distinct and geographically structured mtDNA clades - consistent with the genomic footprint of a hybrid zone movement. The highly fragmented geographic distribution of the fire salamander through north-central and central Apennines, prevented us from carrying out a formal and straightforward cline analysis. Nonetheless, the strongly structured pattern of genetic variation that emerged with the Bayesian clustering analyses of nuclear variation, does not conform with this expectation. In fact, within the range of the southern lineage, it showed the occurrence of genetic sub-clusters along the north-south axis , close to our sampling site 14, and dated back to the last glacial epoch (around 45 000 years bp). The occurrence of this fossil record is instead consistent with a scenario of a secondary contact zone primarily located in the north-western Apennines, and a mtDNA introgression southward. Under this scenario, the genetic cluster emerging at K = 3, grouping samples 12–14, would reflect the presence of S. s. gigliolii in this area during the last glaciation, and the occurrence of a glacial sub-refugium within the region, as already suggested for several temperate species (see37 and references therein). Alternatively, the fossil record might suggest a glacial refugium for the northern lineage in the northern Apennines. As glacial conditions alleviated the northern lineage could have moved south to meet the southern lineage there. Subsequently, the southern lineage may have expanded to the north, at the expense of the northern one, with hybridization, resulting in mtDNA introgression. However, a plausible expectation under this scenario would be some level of mtDNA sequence divergence between populations S. s. salamandra in Italy, achieved during the prolonged isolation in distinct refugia . Instead, such an instance of divergence was not observed.A second indication comes from the Upper Pleistocene fossil record. A scenario of post-glacial colonization of northern and central Apennines by S. s. salamandra mtDNA moving southward, then the main question to answer is, why did S. s. salamandra mtDNA introgressed so deeply into S. s. gigliolii populations? Providing a definitive answer goes behind the scope of this study, and would require specific experimental designs. However, it is worth noting that several of the commonly invoked causes of mito-nuclear discordance could already be dismissed in the present case. First, sex-biased processes, such as female-biased dispersal43 or disassortative preferences in female mate choice30, are unlikely to have played a role. In fact, although extensive surveys are still lacking, the available evidence does not support such female-biased processes in S. salamandra43. Second, purely stochastic processes related to demographic disparities between interacting lineages upon secondary contact38, are unlikely to have been implicated either. Literature surveys and simulation-based works38 strongly suggest that differential introgression triggered by these processes is more likely to occur at the uniparentally inherited markers, and from the resident toward the expanding lineage. In the present case, this pattern would imply massive introgression of mtDNA from east to west of the contact zone , that is, in the opposite direction actually observed.Under a scenario of 44 suggests that, under a wide range of conditions, sex-biased and purely demographic processes are unlikely to yield strong mito-nuclear discordances. In contrast, adaptive mitochondrial introgression can easily generate such discordances44, particularly in low-dispersal organisms, as is the case of S. salamandra. Of course, given the many organismal functions in which the mitochondrial genome is implicated48, and the unsuitability of our data in this respect, we refrain from even hypothesizing which adaptive advantage might have promoted a massive mtDNA introgression. In light of the frequently observed mito-nuclear discordances in S. salamandra, at various levels of population structure23, we see this issue as a major research question, amenable to future experimental efforts.Noteworthy, recent evidenceSalamandra salamandra populations and, together with similar findings in other regions of the species’ range, contribute to identify the fire salamander as a particularly intriguing case to investigate the complexity of mechanisms triggering patterns of mitonuclear discordance in animals.Our results clearly show the major role played by reticulate evolution in shaping the structure of S. salamandra from 21 localities, ranging from the southern slope of the Alps to the southern tip of the Italian peninsula  electrophoresis was used to investigate the genetic variation of 23 putative allozyme loci. Enzyme systems analyzed, putative loci, and buffer systems used in electrophoretic procedures are listed in Table 49. Polymerase chain reactions (PCR) were carried out to amplify portions of the two mitochondrial gene fragments CYTB and COI. After preliminary PCR amplifications using generic primers drawn from the literature51, more specific primer pairs were designed and used to amplify and sequence all the individuals analysed. Primers designed and used to amplify the CYTB gene fragment were 494-salamod-CATCAACATCTCCTACTGATGAAA and CYTB-salamod-GGAGTAAGCAGTGAGATTACC, whereas VF1d-TTCTCAACCAACCACAARGAYATYGG and VR1d-TAGACTTCTGGGTGGCCRAARAAYCA52 were used to screen variation at the COI gene fragment. Amplifications were carried out in a final volume of 15 μl containing: MgCl2 (2 mM), four dNTPs (0.2 mM each), primers (0.2 μM each), the enzyme Taq polymerase , reaction buffer  and 2 μl of 20 ng/μl DNA template. PCR cycling conditions were the same for both the genes: a step at 94 °C for 5 min followed by 36 cycles of 45 sec at 94 °C, 1 min at 55 °C (CYTB) or 51 °C (COI), and 1.5 min at 72 °C, followed by a single final step at 72 °C lasting 10 min. The PCR products were purified and sequenced by Macrogen Inc. (http://www.macrogen.com). All sequences were deposited in GenBank (accession numbers: MH668103-MH668152).Genomic DNA was extracted using proteinase K digestion followed by a standard phenol-chloroform protocol53, were estimated using the programs GENETIX 4.05.2 software54. The occurrence of Hardy-Weinberg and genotypic linkage equilibria were addressed for each locus and locus-pair, respectively, in each sample by means of exact tests as implemented in FSTAT 2.9.355.Allele frequencies and genetic diversity estimates, including allelic richness, observed heterozygosity, and unbiased expected heterozygosityS. salamandra populations along peninsular Italy, using two Bayesian clustering methods: the individual-based and spatially explicit approach implemented by TESS 2.3.156, and the sample-based approach implemented in BAPS v 657.We investigated the genetic structure of 58, and the resulting clustering was visualized with DISTRUCT59.The analysis with TESS was carried using the admixture model, the option to update the spatial interaction parameter activated, and all other settings left to the default options. A preliminary analysis was conducted to restrict the range of plausible K values (i.e. the number of clusters). Values of K between 1 and 21 were tested, with 10 replicates per K, each of 5000 iterations following 3000 iterations discarded as burn-in. The settings for the final run were: K between 2 and 10, 100 replicates per K, and a burn-in of 30 000 iterations followed by 50 000 iterations. For each value of K, the 10 replicates with the lowest Deviance Information Criterion (DIC) were permuted in the software CLUMPP 1.1.2The Bayesian clustering analysis with BAPS was carried out using population samples as the units of the analysis. With this method we run two sets of analyses, with and without using geographic coordinates as prior information to infer the best number of clusters (K). In both cases, we explored values of maximal K between 2 and 10, carrying out 5 replicates for each maximal K to check for consistency among runs.60, that is, we presented and discussed results of each clustering option deserving biological interpretation, irrespective of the K-value that is deemed ‘optimal’ according to the summary statistics.When interpreting results from both TESS and BAPS analyses, we followed recommendations by Meirmans61. Sequences of the two gene fragments analysed were concatenated using the software CONCATENATOR 1.1.062. The best partitioning strategy for the concatenated mtDNA dataset was assessed by means of the software PartitionFinder v1.0.163, using the Bayesian information (BI) criterion and the ‘greedy’ search method. This analysis suggested that the HKY substitution model best fitted all the data partition considered .Sequence electropherograms were controlled by eye using the software FinchTv1.4.0 (Geospiza Inc.), and the sequence alignments were obtained using CLUSTALX 2.064, using default settings for all parameters but the substitution model (HKY) and the type of tree improvement (SPR and NNI). The estimated tree was then converted into an haplotype network using the software HaplotypeViewer65.The phylogenetic relationships between haplotypes were inferred by means of the maximum likelihood algorithm as implemented in PhyML 3.10S. salamandra in Italy (see Results). Consequently, we refrained from using mtDNA variation to estimating historical demographic processes, phylogeographic dynamics, and their time line.The overall pattern of genetic variation observed at level of the entire dataset, suggested that the mtDNA variation might be not entirely reflective of the population structure and history of


Martes flavigula, from the Korean Peninsula, Russian, Taiwanese and Chinese localities in a biogeographic framework using mitochondrial  and nuclear gene sequencing (ghr).Peninsulas often harvest high genetic diversity through repeated southward migrations of species during glacial maxima. Studies addressing within-species evolutionary responses to climate fluctuations in northeast Asia are limited compared to other regions of the world, and more so in the Korean Peninsula. In this study, we conducted the first population-level study of the yellow-throated marten, Martes flavigula likely colonized the Korean Peninsula from Mainland China through the Yellow Sea twice, ca. 60 kya and 20 kya. Korean martens diversified during the Late Pleistocene with at least two dispersal events out of Korea, towards the southwest to Taiwan (ca. 80 kya) and towards the North into Russia and eastern China; most likely after the Last Glacial Maxima (ca. 20 kya). We argue that the lack of population structure and mixed populations is possibly a consequence of the high dispersal capability of the species. The Bayesian skyline plot revealed a population decline within the last 5000 years, suggesting potential negative biotic and anthropogenic effects in the area. We find that local populations are not genetically differentiated, therefore no perceptible population structure within Korea was found.Bayesian analyses revealed a rather young population, with a split from the most recent common ancestor at around 125 kya. M. flavigula adds to the lack of geographical structure in this species and the paraphyly of Korean lineages.The topography and geography of the Korean Peninsula has played a pivotal role in its colonization. Connections between the Korean Peninsula and the Mainland through sea-level drops of the Yellow Sea at times of glacial maxima and the high dispersal capability of The online version of this article (10.1186/s12862-019-1347-x) contains supplementary material, which is available to authorized users. Present day species richness and distributions are believed to have been strongly influenced by the Last Glacial Maxima (LGM), patterns well documented throughout diverse European and North American studies [ studies –5. At gl studies , 6, and, studies . The bio studies –14. Ice  studies , 16 in r studies , 17, 18.Karsenia koreana, Onychodactylus koreanus, Hynobius quelpartensis, H. unisacculus, H. yangi) and frogs  are endemic, with a complete absence of endemic reptiles or mammals. Yet, phylogeographic and population genetic studies on small mammals reveal a strong genetic structure and unique lineages within the Korean Peninsula and adjacent areas. For example, molecular work on rodents, Apodemus peninsulae, A. agrarius, Myodes regulus, Tamias sibiricus and Crocidura shantungensis from the Korean Peninsula, China and Russia suggest that some areas within these regions likely acted as refugia during the Pleistocene [One interesting feature of the Korean Peninsula, from a biogeographical point of view, is that it is peripheral to some widely distributed Eurasian species, and therefore likely to hold genetic signatures through peripatric speciation events . Howeveristocene , 20–23. istocene , 24. Somistocene . Subsequistocene , 31, allistocene .Meles leucurus) [Sorex caecutiens [Throughout the Holocene, China, Taiwan, the Korean Peninsula and Russia have undergone complex environmental changes to their coastline as a consequence to cyclical sea-level fluctuations , 33. Theeucurus)  and Soreecutiens  from theVulves vulpes), the grey wolf (Canis lupus) and the raccoon dog (Nyctereutes procyonoides) in Korea, China and Russia have revealed a lack of geographical structure and unclear phylogeographic patterns within the region [Martes, found in Asia, Europe and North America, with species generally showing considerable distribution ranges. However, most eastern Eurasian marten species today exhibit a disjoint distribution, reflecting population fragmentation of former wider species ranges, possibly as a consequence of glaciation events throughout their range [Martes flavigula). The Korean Peninsula offers a unique model to assess patterns and processes, as it is part of the northern- and eastern-most distribution limit of the yellow-throated marten. This species is widely distributed throughout southern and eastern Asia, ranging from the Himalayas to southern China, the Malay Peninsula, Sunda Islands, Siberia and The Korean Peninsula [Martes flavigula is believed to have originated in tropical regions and expanded to the northeast temperate areas such as Korea and Russia after the last glacial maximum  between Taiwan, Russia (Primorye), and South China (Kunming), and as in other mustelid species they are thought to have had complex colonization episodes of nearby areas [Studies on larger mammals with broad home ranges such as the red fox . De8 ky BP; , 49, 50.by areas . Howeverby areas , 53. Basby areas , their hA total of 24 martens were collected throughout Korea and one individual from Russia Fig. . All samb (cyt b), NADH dehydrogenase subunit 2 (nd2) and the control region (cr) fragments and nuclear growth hormone receptor (ghr). These mitochondrial sequences were available from Genbank for M. flavigula from Taiwan, China and Russia [GHR locus was only used for population comparison among the Korean localities to assess levels of heterozygosity [M. flavigula. Internal markers were designed to resolve poor quality amplification of blood samples  and Chelex® 100 following the instructions of the manufacturer. The targeted genes were the mitochondrial cytochrome d Russia , 54 and zygosity . Polymorzygosity . The priM. melamprus, M. martes, M. foina and Gulo gulo [Sequences were aligned and visualized in Seaview v.4.2.11  using Clulo gulo , 62. Howulo gulo  under thulo gulo , 65 usinulo gulo ).Martes flavigula cyt-b sequences in Genbank from Thailand . However, after careful examination, the first half of the cyt-b sequence matched M. melampus and the second half M. flavigula. The change happened exactly after the internal cyt-b primers employed in their study [Martes and therefore we suspect that the chronological phylogeographic estimates, at least in part, might be inaccurate or erroneous. Thus, only the second half of the cyt-b (581 bp) remained usable. However, because of these issues, in addition to the unconfirmed origin (as they came from a zoo), these sequences were not included in the final analyses. Nevertheless, they were included in the MCMC (Monte Carlo Markov Chain) continuous phylogeography analysis shown in Additional file M. flavigula (AY882061) coming from China’s Kunming zoo was included in the analyses as it matched very closely to other martens from the Kunming Province. When geographical positioning system (GPS) coordinates were not available from published records, we used the center GPS coordinate for their alleged location.To infer ancestry from the likely ancestral population we downloaded the only available ir study  and thushttp://beast.bio.ed.ac.uk). We inferred a mitochondrial gene tree based on a constant coalescent model, by linking all mitochondrial partitions (as they represent the same locus), but specifying separate nucleotide substitution and molecular clock models; HKY + G and strict clock for each, respectively. In order to time-calibrate the population tree, we fixed the mutation rate in cyt-b to 2.403 × 10− 8 substitutions/site/year following [nd2 and cr we selected a diffuse gamma distribution . In addition to the gene tree, we co-estimated the dispersal history using a discrete phylogeographic  model also implemented in BEAST [n2)-n transition-state parameters (where n is the number of location or states) [First, we performed statistical coalescent and phylogeographic analyses using BEAST v1.8.3  . This mo states) .cyt-b data and the same prior clock for the nd2 and cr fragments. For both analyses, we ran two independent MCMC chains, each with 20 million states and sampling every 4000th state. Independent runs were evaluated for convergence and mixing by observing and comparing traces of each statistic and parameter in Tracer v1.6 ([http://beast.bio.ed.ac.uk/tracer). We considered effective sampling size (ESS) values > 200 to be good indicators of parameter mixing. The first 500 states of each run were discarded as burnin, and samples were merged using LogCombiner v1.8.3. The resulting 9000 states were summarized using TreeAnnotator v1.8.3, where a maximum-clade-credibility (MCC) tree with mean values were generated under the “-heights ca” option [Secondly, we inferred changes in effective population size through time using a Bayesian Skyline Plot (BSP) model  with a ser v1.6  and Bayes factors (BF). MLE were calculated with path sampling (PS) and stepping stone (SS) analyses in BEAST [http://earth.google.com).Thirdly, to estimate approach . We usedin BEAST   method  as impleTajima’s D , Fu’s FsGHR gene fragment had the lowest genetic polymorphism, with only one polymorphic site , with 6 heterozygotes C or T , and 17 homozygotes, . The lengths of the alignments were: 993 bp (cyt-b), 957 bp (nd2), 592 (cr) and 443 (ghr). The combined mitochondrial data set resulted in 2542 bp. For the concatenated mitochondrial data set, a total of 9 haplotypes were recovered, 5 of these from the Korean Peninsula. The ghr alignment recovered 2 haplotypes from the Korean Peninsula. The best partition schemes inferred by PartitionFinder, employed for the Maximum Likelihood (ML) network in Haploviewer, were: 1) cyt-b + nd2 1st codon position, cyt-b + nd2 2nd codon position, cyt-b 3rd codon position+cr, nd2 3rd codon position. The ghr network was run under no partition scheme.The nuclear Runs showed high Effective Sample Size > 200), indicating adequate sampling of the posterior distribution. Both discrete and continuous MCC trees , and both Korean and mainland individuals (n = 29) suggests population stasis , Tajima’s D = 2.29 , SSD , Raggedness index = 0.29  and Mainland and Korean samples; Fu’s F = 3.9 (non-significant), Tajima’s D = − 0.2 (non-significant), SSD = 0.06 (significant p = 0.01), Raggedness index = 0.17 . These results confirm the observed population decline of the BSP  during the Pleistocene from southern China. The ancestral root (125 kya) equidistant between the Korean Peninsula and southern China suggests at least two migrations or dispersal events towards the Korean Peninsula through the Yellow Sea. The first colonization event dates back to ca. 60 kya and a more recent arrival at around 20 kya. Although we cannot ascertain the origin of the Taiwanese population, the data and timing would support a possible Korean origin. It is likely that arrival at Taiwan as well as the event towards northern localities occurred recently, during the Holocene , East, South China  and Taiwan has similarly been found in other mustelid species such as Mustela sibirica and Mu. nivalis and concurs with a scenario of recent continental marine regression during glacial periods in the area [Mu. sibirica in relation to its counterpart populations in the Korean Peninsula, Russian and East China [M. flavigula) colonized Taiwan from nearby China during the Pleistocene via land bridge connections through sea level regression at glacial periods [Martes flavigula’s estimated time of colonization  between the Mainland-Taiwanese population  lies within our estimated time range of ancestral M. flavigula migrations, at around the Late Pleistocene [The close phylogenetic affinity in the area , 51. Furst China . Four sp periods –93. MartM. flavigula population (n = 21) at four localities in Mountain Jiri in South Korea revealed an overall low mean relatedness and moderate genetic diversity [Vulpes vulpes) and the grey wolf (Canis lupus) with high dispersal mobility and high habitat adaptability [Nyctereutes procyonoides) populations of the Korean Peninsula has been attributed to dispersal, changing climate and geography over the past 50 kya, preceding their population expansion after the Last Glacial Maximum [Ursus thibetanus) [Panthera tidris) [Meles leucurus) [Apodemus peninsulae) and the Korean red-backed vole (Myodes regulus) from Eurasia, with Korean populations distinct from Russian and/or China, and are arguably Korean endemics [Tamias sibiricus) show strong genetic structure with northern, central and southern populations in South Korea [Apodemus agrarius), genetic divergences between populations in Russia, South Korea and central Asian populations range from 175 to 192 Kya, and between Taiwan and China from 450 to 500 kya [Crocidura shantungensis) dates between 192 and 397 kya. This suggests that the Korean Peninsula, Russia and Taiwan acted as refugia throughout the Pleistocene [M. flavigula to those regions.Genotype analyses of a iversity . Low kiniversity , which iiversity , 96. Furiversity . These diversity . Similartability , 37, 98,tability , 100. Motability . Similar Maximum . Furtherbetanus) , the Sib tidris)  and the eucurus) , which sendemics , 21. Othth Korea . A highe 500 kya . Similaristocene  for smalMeles leucurus), where populations from Korea (including Jeju island in the South), East Russia, Mongolia and West Siberia showed little genetic divergence between haplotypes, indicating high population dispersal [Sorex caecutiens) from the Korean Peninsula show admixture with Asian populations but monophyly in Jeju Island [The Yellow Sea, separating South Korea and central and northeastern China, was partly dry land throughout the last glacial period  and servispersal . Similaru Island . The recu Island .M. flavigula and the timing of colonization of the Korean Peninsula can be further understood from the species distribution range and its absence in Japan, as has been shown for other species of mustelids in the region [M. flavigula to the Korean Peninsula, which might have happened up to 60 kya  and the Sika deer (Cervus nippon) are some examples of mammals not found but that crossed over from the Peninsula to Japan before the sea started to rise [M. flavigula in Korea, in the mainland and Taiwan and absence in the Japanese islands follows patterns of topographic changes by Pleistocene climatic conditions. Similarly, successive dispersal events from the mainland to the Korean Peninsula postdate such events, as do the probable outward dispersal events from the peninsula to Taiwan (between 60 and 20 kya) and northern localities at the turn of the LGM. These data agree with LGM (ca. 23.5–18 kya) connections throughout the area, coastal China, Korea and Taiwan [Mustela sibirica mtDNA sequences between Korea and the Tsushima Islands (between South Korea and Japan) and Jeju Island, suggesting a recent land bridge connection in the area [P. bengalensis) in Tsushima Islands shows close genetic affinity to the mainland and is not present in Japan [M. flavigula was already present in the Korean Peninsula at the time of the LGM sea regression, its presence in Jeju Island and Tsushima Islands has not been reported.Further insights into the biogeography of e region , 40. Pare region  argues te region , 104. The region , which de region , 91, 105ya Figs.  and 3. M to rise , 28. Thud Taiwan , 31. Evithe area , 107. SiM. flavigula’s observed population decline  and cou7.5 kya, , 111.M. flavigula adds to the lack of geographical structure in this species and the paraphyly of the Korean population. In general, insufficient population sampling typically leads to a false signal of population structure. In contrast and in spite of our sample size, we do not observe structured populations, but rather a signal of high dispersal capability. These findings may be further assessed in studies with broader sample sizes and denser genetic markers.Here, we report on the biogeography of the yellow-throated marten from South Korean populations, Taiwan, southern and eastern China and eastern Russia. We find a recent population origin throughout its geographical range with at least two Pleistocene expansions towards the Korean Peninsula from central China. Such colonization events are likely a consequence of the proximity, topography and geography of the Korean Peninsula. The repetitive land connections between the Korean Peninsula and the Mainland through sea-level falls of the Yellow Sea at times of glacial maxima and the high dispersal capability of Additional file 1:Martes flavigula codes, country of origin and sampling. (DOCX 14 kb)Additional file 2:Martes flavigula gene fragments. (DOCX 12 kb)Primers use to amplify Additional file 3:Martes flavigula including the two short (581 bp) cyt-b fragments from Thailand. High posterior probability nodes are represented in red circles. Thailand is highlighted in red and South China in green. (DOCX 115 kb)Continuous coalescent tree of Additional file 4:Martes flavigula. The asterisk (*) represents the best model selected. (DOCX 12 kb)Marginal likelihood estimates and Bayes factor comparison of coalescent priors for Additional file 5:Martes flavigula. Posterior probability nodes are represented in red circles. (DOCX 96 kb)Continuous coalescent tree of Additional file 6:cyt-b, B) nd2, C) cr for all Martes flavigula individuals. (DOCX 25 kb)Mismatch distribution analyses of A)


Lithobates catesbeianus) that was extensively farmed on 14 islands in the Zhoushan Archipelago of China and in three nearby regions on the mainland. We quantified the relative importance of propagule pressure and hunting pressures on the genetic variation of bullfrog populations and found that insular populations have greater genetic variation than their mainland counterparts. Although genetic differentiation between the populations was observed, no evidence of recent bottlenecks or population expansion in any of the tested population was found. Our results suggest that the propagule pressures of bullfrogs escaping from farms, multiple releases and hunting pressure influence the genetic variation among bullfrog populations. These results might have important implications for understanding the establishment and evolution of alien species on islands and for the management of invasive species.Islands are often considered to be more susceptible to biological invasions and to suffer greater impacts from invaders than mainland areas, and this difference is generally attributed to differences in species introductions, ecological factors or human activities between islands and mainland areas. Genetic variation, as a good estimate of evolutionary potential, can influence the invasion process and impacts of alien species. However, few studies have compared the genetic diversity of alien species between islands and a corresponding mainland. Here, we examined the genetic variation and differentiation in feral populations  of a globally invasive species (the American bullfrog,  This difference is generally attributed to the facts that islands often harbor more alien species, that islands have lower biological resistance  to invaders than the mainland areas; or that islands experience more human disturbances than the mainland areas9, and/or that islands exhibit a lower hunting pressure10. Genetic variation, a good estimate of population fitness and adaptive potential, may influence the invasion process and impacts of alien species12. Greater genetic diversity is hypothesized to promote rapid evolutionary responses to selection pressures in novel environments and may therefore facilitate invasion success and range expansion14. However, few studies have compared the genetic diversity and structures of alien species between islands and the mainland16.Islands are often considered to be more susceptible to biological invasions and to suffer greater negative impacts from invaders than the mainland17. A small founder population only represents a portion of the genetic variation in the native populations and is more likely to result in a genetic bottleneck. In contrast, multiple introductions of a species from different source populations in the native range may facilitate the admixture of previously isolated native populations and increase the genetic variation in the invading populations19. Residence time  may reflect the time dimension of propagule pressure20. With increasing residence time after the first population becomes established, more propagule pressure from multiple releases  may be introduced into a region, which would promote genetic variation and differentiation in the invading populations in the region20. More or less propagule pressure from introductions to islands compared with a mainland might directly result in higher or lower initial genetic diversity in insular populations. In addition, island environments, which are characterized by a lower resistance of native species or pathogens and/or decreased hunting pressure to invaders compared with mainland areas, are more likely to reduce the mortality of insular propagules21 or to reduce the length of the bottleneck period following an introduction, which could lead to more genetic variation in the insular populations than in their mainland counterparts.Identifying the factors that influence the genetic variation of alien species on islands is not only important for understanding their successful establishment and evolution but is also crucial for the prevention and eradication of such species. The introduction history , island environment and human activities  are likely to influence the genetic variation of insular introduced populations. Low propagule pressure  from a single introduction often leads to reductions in initial genetic diversityLithobates catesbeianus = Rana catesbeiana, hereafter referred to as the bullfrog) is one of the world’s worst invaders22. Native to eastern North America, the bullfrog has been introduced to many countries and regions, including both mainland regions, such as Europe, Asia, South America and some areas of North America outside its native range, and some islands, including Vancouver Island, the Caribbean Archipelago, Crete, the Hawaiian Archipelago, the Zhoushan Archipelago, Japan, Singapore, Sri Lanka, and Indonesia24. Bullfrog invasions have led to population declines among some native amphibians in the invaded range through competition (bullfrogs have a high reproductive ability and high densities) with or predation  on native amphibians28. Bullfrogs can also spread chytrid fungus, Batrachochytrium dendrobatidis, which is the proximate cause of rapid amphibian declines across diverse biomes29. Bullfrogs are usually found in permanent still water bodies, such as ponds, pools, lakes or reservoirs30. The frog is intentionally introduced for aquaculture (frog leg trade) or as pets32. Feral bullfrog populations are established by bullfrogs escaping from farms or by frogs released by people33.The American bullfrog  from Hansu during the 1980s. Because most feral populations of bullfrogs were founded by escaping individuals from temporary (0.5–2 years), low-quality enclosures 36, information on the number of bullfrogs raised and the number of farms in a region has been summarized in great detail35. The number of bullfrogs raised in a region may be a surrogate for the propagule pressure of local introductions because the local invasion success increases with the number of bullfrogs raised on farms36. Furthermore, due to recent introductions, the residence time for each invaded site can be determined35. This availability of data provides a good opportunity to evaluate the effect of introduction history on genetic diversity and differentiation in alien species.The well-documented bullfrog invasions in the Zhoushan Archipelago in the East China Sea and near the Chinese mainlandWe hypothesize that propagule and hunting pressures have a profound impact on the genetic variation of bullfrog populations, leading to two major predictions concerning the expected distribution of the nuclear microsatellite diversity of bullfrog populations in the island system of the Zhoushan Archipelago. First, island bullfrog populations will exhibit enhanced genetic diversity relative to mainland populations. Second, the genetic diversity of island bullfrog populations will be influenced the number of bullfrogs raised, the residence time, the number of bullfrog farms and the hunting pressure.The methods were designed based on the Good Experimental Practices adopted by the Institute of Zoology, Chinese Academy of Sciences, China. All experimental procedures and animal collection were approved by the Animal Ethics Committee at the Institute of Zoology, Chinese Academy of Sciences, China (Permit Number: IOZ10013).37.We included 14 islands of the Zhoushan Archipelago: Daxie, Fodu, Liuheng, Xiazhi, Taohua, Dengbu, Zhujiajian, Zhoushan, Cezi, Jintang, Depengshan, Xiushan, Daishan and Sijiao . Bullfrog farms are generally located near a permanent still-water body or rice fields near permanent still-water bodies (less than 1 km from a water body) because they require a water supply. We counted the number of bullfrog farms within a plot (with a radius of 1 km centered at a sampling site) for each of the sampled sites in a region or island and summed the number of bullfrogs raised on the farms. For the sampled sites where a bullfrog farm was located, the residence time was considered as the time since the farm began to raise bullfrogs. We obtained information on residence time in the sampled sites without a bullfrog farm by using questionnaire surveys  of their answers was used. The residence time for all the sampled sites in a region or island is defined as the longest reported residence time.We obtained information on the owners of the bullfrog farms from the Fisheries Bureau for the counties where the sampling sites were located. According to a regulation in China, a permit issued from the bureau is needed before a bullfrog farm can be operated. We then visited each owner to collect information on the number of bullfrogs raised on the farm and the periods during which bullfrogs were raised using a questionnaire survey10. For the questionnaire surveys, we interviewed three resident individuals living in the invasive region and asked “is there frog hunting activity at night.” The answers were usually “frequent hunting”, “occasional hunting” or “no hunting”, and the answers provided by the three residents in each invasive region were always consistent. For field monitoring, we recorded any human hunting activity in the invasive regions during three consecutive nights. Hunters usually used electric torches to find bullfrogs and caught them by hand or with a fishing net during the night. Therefore, we could find hunters by torchlight during the night. “Frequent hunting” was associated with higher hunting pressure. We classified hunting pressure as a dichotomous variable with the values “frequent hunting” and “no hunting”. An invasive region was considered to “frequent hunting” if the questionnaire surveys yielded the answer “frequent hunting” or hunting activity was detected in two of the three nights monitored, and all other cases were defined as no  hunting.We obtained information on the hunting pressure in invasive regions through the use of questionnaire surveys and field monitoring in 2011–2018We randomly captured 30 postmetamorphic bullfrogs in invaded water bodies manually or with long-handled nets between May and October in 2011–2018. The distal third of the third toe on the right hind-foot from each frog was clipped. We then released the frog at its capture site. Each tissue sample from the toe clips was preserved separately in 95% ethanol in a 2-ml screw-cap microcentrifuge tube and stored at −20 °C in the laboratory.39. In brief, the tips of bullfrogs’ second hind toes (approximately 3 mg) were clipped and placed in a 2-ml centrifuge tube with 100 μl of lysis buffer containing 0.01 M NaCl, 0.1 M EDTA, 1 mg/ml proteinase K, 0.01 M Tris–HCl (pH 8.0) and 0.5% Nonidet P-40. The tube was vortexed for 1 min at ambient temperature, centrifuged to recover all material from the bottom of the tube, and incubated at 50 °C for 120 min and at 95 °C for 20 min. The tube was then centrifuged at 12,000 rpm for 3 min in a cold temperatures, and the extract was diluted to one tenth of its original concentration for polymerase chain reaction (PCR) amplification. The individuals were genotyped using nine nuclear microsatellite loci . Sequence information for the primers and the amplification conditions used for these loci were based on previously published data41   and the observed heterozygosity (Ho), and the mean number of alleles (Na) for each region or island. Asymmetric migration rates were estimated using the MIGRATE-N 3.2.7 program47.We applied GenAlEx 6.5We examined the difference in the mean genetic diversity and allelic richness for bullfrogs between introduced regions on the mainland and the islands using a one-way ANOVA. We tested the differences in residence time, the number of bullfrogs raised and the number of farms between introduced regions on the mainland and the islands using a Wilcoxon rank sum test.Dest in the R package DEMEtics V0.8.048, which is an unbiased estimator of genetic divergence for multiple loci49. The significance of the Dest results was assessed by bootstrapping with 1,000 permutations. In addition, we examined the relationship between the pairwise Dest and relative residence time using a Mantel test implemented in ARLEQUIN3.5 with 100,000 permutations50.We determined the genetic divergence between regions or islands using 52. This software measures heterozygosity excess with respect to the mutation-drift equilibrium characteristic of population-size reductions for each population to infer recent population bottlenecks. We applied the one-tailed Wilcoxon signed rank test to determine the significance of heterozygosity excess. Two-phase mutation models were used: 90% single-step mutations and 10% multiple-step mutations with 10,000 replicates. To assess population expansion, we performed an intralocus k-test and interlocus g-test54 using KGTESTS Excel Macro53. The intralocus k-test estimates the P value of k using the one-tailed binomial distribution. The significance of the g value for expanding populations was set at α = 0.0554.We tested for population bottlenecks using the program BOTTLENECK55 to evaluate the relative importance of the introduction history and hunting pressures on the expected heterozygosity. The full model was a multiple linear regression model with He as the response variable and with hunting pressure , residence time, number of bullfrogs raised and number of farms as predictors for island populations. All the models that included all possible combinations of the four (24−1 = 15 models) variables were ranked. We compared the alternative models using the second-order Akaike information criterion (AICc)55 and calculated the parameter estimates and their variances based on Akaike weights. Those models that were within two AICc units of the highest-ranked models 55 were reported. We conducted these analyses using the lme4 and MuMIn packages in R version 2.15.256.Island area and the number of bullfrogs raised were log-transformed to improve linearity. Because several predictors were collinear . The number of bullfrogs sampled in each site ranged from seven to 30 individuals in an island or from five to 30 individuals in a region (Table The number of sampled sites on an island or in a region ranged from one to four bodies of water and there was no significant difference between the island and mainland sampling points (Mann-Whitney U test: P > 0.05). We also found that none of the populations or loci showed significant departure from Hardy-Weinberg equilibrium after Bonferroni corrections (P > 0.05). The loci were polymorphic within all populations.MICRO-CHECKER did not detect the presence of null alleles or scoring errors. After a Bonferroni correction, we found no patterns of linkage disequilibrium among the loci and populations (He) and observed heterozygosity (Ho) for mainland populations ranged from 0.52 to 0.56 and 0.56 to 0.67 . The mean number of alleles (Na) and effective population size (θ) for mainland populations ranged from 3.78 to 4.33 and 0.0022 to 0.0145, respectively, and for island populations from 4.22 to 6.78 and 0.0022 to 0.0971, respectively. Overall, the genetic diversity (He) and allelic richness (Na) for island populations were higher than those for mainland populations .The expected heterozygosity  or population expansion in any of the populations , but there was no difference in the residence time between islands and regions of the mainland .The number of bullfrogs raised on islands was higher than that in invaded regions of the mainland  ranging from 0.8015 to 0.8691 for insular populations (Table Wi = 0.206 to 0.304)  for insular populations contained three variables: the number of bullfrogs raised, the residence time and hunting pressure  for expected heterozygosity in insular populations Table . The modWe detected a statistically significant pattern in which greater genetic diversity and allelic richness in feral populations of bullfrogs on the islands of the Zhoushan Archipelago than on mainland China, although some island populations  have genetic diversity similar to mainland populations. A feral population would have greater genetic variation if there had previously been a larger number of bullfrogs raised on farms in the invaded region or island or if bullfrogs invaded early or invaded islands. These results suggested that both the introduction history and hunting pressure likely influenced the genetic diversity in bullfrog populations.et al.16 detected lower genetic variation in one insular population of Vulpes vulpes on Phillip Island compared to three populations on the Australian continent16. Similarly, higher genetic diversity was measured in eight populations of Neovison vison in Scotland (treated as a mainland) than one Outer Hebridean island population due to the admixture of introductions in the Scotland populations15. Therefore, the higher genetic diversity of bullfrog populations on the islands of the Zhoushan Archipelago than on mainland China is correlated to larger numbers of bullfrogs being raised on the islands than on the mainland and to lower hunting pressure in the islands. The propagule pressure of introductions plays an important role in determining the genetic variation of alien species58. The large number of bullfrogs raised may increase the number of bullfrogs escaping from the enclosure given that individual bullfrogs in the enclosures have the same chance of escaping, which would increase the input of more variation from escaped bullfrogs and therefore have positive effects on the genetic diversity of feral populations. In contrast to another study on invasive salmonids20, we found a positive effect of residence time on genetic variation in bullfrog populations, indicating that there might have been multiple releases at the sampled sites following the original introduction by escaped bullfrogs from farms. Bullfrog releases by both religious communities and individual persons are actively observed in China, where our sampled sites are located36. Such releases might have increased propagule pressure on the studied water bodies.Several studies have compared the genetic variation in introduced populations between islands and the mainland. For example, Lade 10. Lower hunting pressures would be more likely to reduce the mortality of bullfrog founders from farms on islands and could therefore could result in higher genetic diversity in insular populations than in their mainland counterparts.In model averaging, hunting pressure might represent the main factor that influences the survival of bullfrogs escaping from farms on the islands. Human hunting pressures on bullfrogs were lower on the Zhoushan Archipelago than in the Beilun region of the mainland likely due to smaller human populations and lower demand for frogs as food throughout much of the archipelago19. The higher genetic diversity in insular bullfrog populations is unlikely due to such an admixture for three reasons. First, seawater might be a significant barrier to the dispersal of bullfrogs among islands due to the species’ intolerance of seawater30. As a result, gene flow between island bullfrog populations might have been limited among the islands of the Zhoushan Archipelago. Second, a lack of genetic structure within all bullfrog populations indicates that multiple introductions from different source populations in the native range are unlikely to have occurred and contributed to genetic structure in each of these invasive populations. Third, this result is in line with a recent study based on the mitochondrial cytochrome b gene34, which suggests that a single introduction from a local population in the native range might have driven the limited haplotype diversity (only two haplotypes) in invading bullfrog populations in China58.Studies have found that the admixture of multiple introductions from different source populations in a native range can increase the genetic variation in the invading populations59, we found no evidence for either recent bottlenecks or population expansion in either insular or mainland bullfrog populations . We detected genetic differentiation in both insular population and mainland population pairs, suggesting the existence of genetic structuring exists among bullfrog populations. However, the differentiation (Dest) between pairs was not related to differences in residence time , suggesting that there were no differences in genetic differentiation between old and young bullfrog populations. Three factors may be responsible for such differentiation. First, gene flow among mainland and insular populations might be very low (Table 67. Similar to most amphibians69, bullfrogs are intolerant of seawater30, and sea barriers might isolate gene flow among insular populations. Second, large differences in the number of bullfrogs raised on farms (Table 20, which can increase or restore genetic diversity in invading populations.Both high and low levels of genetic differentiation have been observed in invasive species, including those with highly structured populations, such as 19. Although evidence exists for successful invasions that display reductions in genetic variation71, increasing numbers of studies show that higher genetic diversity facilitates invasion success73. Higher genetic variation in insular invasive populations than in their mainland counterparts would make islands more prone to biological invasions. The available data for bullfrogs are limited but consistent with this conjecture. Bullfrogs are more likely to invade from farms located on the Zhoushan islands than from farms in the nearby the mainland10. Future work is required to quantify the relative contributions of ecological factors and genetic factors to the differences in the invasion success and evolution of bullfrog populations between islands and the mainland.The results from this study might have important implications for understanding the establishment and evolution of alien species and for the management of invasive populations on islands. Enhanced genetic variation may increase the potential for adaptive evolution, which could lead to rapid evolution by natural selection in novel environmentsSupplementary InformationSupplementary Dataset


Several population genetic studies investigated the extent of gene flow and population connectivity in bumblebees. In general, no restriction in gene flow is considered for mainland populations of common bumblebee species. Whether this assumption holds true for all species is not known. An assessment of bumblebee genetic structure in the context of their geographic distribution is needed to prioritize conservation and management needs. Here, we conducted a genetic study on seven bumblebee species occurring in Belgium and Estonia. Using 16 microsatellite markers, we investigated genetic diversity and population structuring in each species. This is the first study investigating population structuring of both declining and stable bumblebee species on both small and large geographic scales. Our results showed no or only low population structuring between the populations of the restricted and declining bumblebee species on both scales, while significant structuring was found for populations of the common species on the larger scale. The latter result, which may be due to human or environmental changes in the landscape, implies the need for the conservation of also widespread bumblebee species. Conservation strategies to improve gene flow and connectivity of populations could avoid the isolation and future losses of populations of these important species. They experience worldwide declines, even more severe than many other pollinator species5. Different hypotheses aim to explain the observed declines in bee populations8. Although decline of bumblebee populations is clearly a multi-factorial phenomenon7, agricultural intensification, with increasing loss of habitats and plant species providing key forage resources, has been declared to be the key driver of the observed bumblebee declines across Europe9. Genetic factors play herein also a role. As genetic variability reflects a species potential to adapt to current and future changes in the environment, having a low genetic diversity will increase the likelihood towards extinction12. Genetic drift, founder effects, and inbreeding can all decrease genetic variability within populations13.Bumblebees are essential pollinators for natural and managed ecosystems14. On one hand limited dispersal could lead to significant substructure and isolation of previously well-connected populations following a pattern in which nearby populations will be genetically more similar than those far away16. On the other hand high dispersal rates can buffer drift effects and lead to weak population substructure or even panmixia over large areas18.Gene flow can also alter the present levels of genetic diversity19. In bumblebees, queens and drones  are the only reproductive stages21. Although some indirect information on male and queen dispersal capabilities is available (e.g.23), accurate species specific data are currently lacking. However, dispersal and gene flow are key determinants of a species’ ability to respond to land-use change. Populations of bumblebee species with a more limited dispersal rate will have less chance of successfully recolonizing a suitable habitat and will be more vulnerable to inbreeding13. Furthermore, the amount of reproductive offspring a species produces will also contribute to the level of gene flow, as more reproductives may enlarge the chance of successful matings and exchange of genetic material between populations .In eusocial species, population structuring can occur due to differential dispersal rates between both sexes25. Such barriers can block dispersal and thus limits gene flow between populations, leading to a non-uniform increase in genetic differentiation across the landscape16. In North America, population genetic studies have compared common and declining species within shared landscapes. These studies showed the impact of such geographic barriers, as they reported an increased population genetic differentiation for mountain and island species30, and a significant fine-scale spatial genetic structure for B. vosnesenskii30 due to human altered-landscapes17. For Europe, only studies investigating island populations of declining and common species in the UK described genetic differentiation and low levels of gene flow35. Studies with common species (B. terrestris and B. pascuorum) showed no population structuring on a European scale37 (respectively). Furthermore, Dreier et al.38 found only very low fine-scale spatial genetic structuring in two common species (B. terrestris and B. pascuorum) out of the five investigated bumblebee species . Thus, in general no restriction in gene flow is considered for mainland populations for most bumblebee species39. Whether this assumption holds true for all bumblebee species is not known. Although few population genetic studies have compared common and declining species within shared landscapes in Europe38, none have studied their population structure on both small and larger geographic scales. However, an assessment of bumblebee genetic structure in the context of their geographic distribution is needed to help prioritize conservation and management needs .Geographical barriers, such as water bodies and mountains, can also greatly limit dispersal and gene flowB. ruderarius, B. soroeensis, B. sylvarum, B. hortorum, B. hypnorum, B. lapidarius, and B. pascuorum). Three species are considered to be declining and restricted in Belgium , while the other four species have a nationally common and widespread distribution 18. Species status and distribution are different in Estonia. Indeed, when comparing 1955–1967 with 2009–2018 abundance data from the same area  increasing population trends were visible for B. sylvarum, B. soroeensis and B. lapidarius, while B. hortorum and B. ruderarius show clear negative trends  and two in Estonia (Harjumaa and Põlvamaa) during bumblebee foraging seasons of 2013–2015 and 2015–2017, respectively. This approach allowed us to test our hypotheses that (i) no population structuring is present for populations of common bumblebee species, while (ii) limited gene flow is expected between populations of restricted and declining species. For the latter hypothesis, gene flow might not be limited at small spatial scale (between the two selected locations of Estonia or Belgium) but we expect it to be at least present at large scale due to less population connectivity, and fewer emerging queens. This is the first study investigating population structuring of both declining and stable bumblebee species on small and large spatial scale. This study has not only great impact on making species specific conservation strategies but also has major consequences for all studies performing population genomics with European bumblebee species as the assumption for the absence or present of structuring within species is a key factor for making an accurate sampling and experimental design.Here, we conducted a genetic study of seven social species of bumblebees occurring in Belgium and Estonia  ranged from 1.87 to 3.72, with a mean AR of 2.71. Mean HE was 0.488, with individual population values ranging from 0.269 to 0.750. For most species, AR and HE estimates were very similar overall populations, showing no significant differences between the Estonian and Belgian bumblebee populations , B. lapidarius  and in B. pascuorum . Global FST and Dest-estimates were low in the other four species . Pairwise FST comparisons were significant (P < 0.05) for 46 of 72 comparisons ranging from 0.014–0.231 . Indeed, all specimens evenly belonged to each identified populations  by Geneland analysis  and four more stable and widespread bumblebee species  on small and large spatial scale. Specifically, we tested the hypotheses that (i) population structuring is absent between populations of common bumblebee species on both scales, while (ii) between populations of restricted and declining species gene flow can be limited at the small scale and structuring should be present at the larger geographic scale. For the common bumblebee species we found no population structuring on a small scale but on the large scale population structuring was present in three out of the four common species . That our data was not able to support our first hypothesis was rather unexpected considering previous studies showing no population structuring for mainland populations of North-American bumblebee species42, and for two common European species (B. terrestris and B. pascuorum) on an European scale37. Although in the latter species, some indications of low genetic differentiation between central European and Scandinavian populations were observed, significant differentiation was only present between populations below and above the Alps showing the impact of large geographic barriers on population structuring37. Indeed, significant genetic differentiation between mainland populations have been shown in several widespread species across natural barriers such as mountains37, and between island and mainland populations35. There were no great mountains present within our study design to limit gene flow, and although the Baltic Sea could be considered as a great water body possibly limiting gene flow, we believe that there are still enough possibilities for gene flow over the main European continent. Hence, as genetic structuring could be present at both low and continental scale due to human-modified landscapes38 this presumably caused the significant differentiation between Belgian and Estonian populations. Another possible explanation is demonstrated in B. lapidarius by Lecocq et al.43. These authors showed evidence of genetic allopatric differentiation in B. lapidarius caused by population movement during Quaternary climatic oscillations. Belgian and Estonian B. lapidarius may have found refuge in another of the main refugia  during Ice Ages causing differentiation, and may be reinforced during post-glacial recolonization45. Although the hypothesis of different Ice-Age refugia has also been suggested in B. pascuorum37, more research is needed to support this hypothesis for both B. hypnorum and B. pascuorum, and to better understand the impact of Ice Age refugia on bumblebee population differentiation.Here, we investigated population structuring in three for Belgium declining and restricted bumblebee species  dispersal rates are currently lacking, this hypothesis cannot be tested.B. ruderarius and B. sylvarum; see Table 18) genetic diversity maybe became so low that no or only few rare alleles are present and thus additional losses due to drift and limited gene flow are unlikely to be detected. The absence of population structuring in restricted species may thus be an artifact of the limited amount of markers used within our study. Recent advances in genotyping-by-sequencing (GBS) methods such as RAD-sequencing (restriction site-associated DNA sequencing) made screening the bumblebee genome for thousands of polymorphisms possible46 allowing the possibility to greatly enlarge the power of population differentiation studies among others. Future research is needed to exclude possible biases due to marker choice.It is important to realize that technical aspects may also influence our results of structuring within the restricted species. The low level of genetic diversity detected within the restricted species  they are more vulnerable for population losses due to environmental changes, which may even lead to local extinction10. Therefore, populations of declining bumblebees should be monitored over the European mainland for their present genetic diversity levels. This knowledge will allow for the development of accurate conservation and management strategies to help maintain or increase current genetic diversity levels, current population connectivity and their effective population sizes. The presence of structuring in the populations of more widespread, stable species has also major impacts on their conservation. Although there is still a high genetic diversity present within their populations, changing landscapes due to human, environmental or climate changes may limit gene flow between populations of these common species. The connection between populations, which have belonged to one metapopulation, must be ensured to allow gene flow and avoid possible future genetic isolation. Furthermore, additional studies must enlarge our knowledge on how human-modified landscapes may influence population structuring38 and which role glacial refugia had on current bumble bee population differentiation.Finally, our results can contribute to current conservation management of restricted bumblebees. The absence of genetic structure within the declining species suggest that the European agricultural landscape is no barrier for gene flow possibly due to queen dispersal. However, as the latter seems unlikely considering multiple studies showing low dispersal abilities within these speciesB. ruderarius, B. soroeensis, B. sylvarum, B. hortorum, B. hypnorum, B. lapidarius, and B. pascuorum) were collected from these five locations. These specimens were already genotyped with 16 microsatellites to study temporal stability of genetic diversity16. All bumblebees were sampled during straight ahead transect walks using a net, and during suitable weather conditions for pollinators at three and four days during the bumblebee foraging season of 2013 and 2015, respectively. For the two Estonian locations; Harjumaa and Põlvamaa, which are separated 210 km, 345 specimens of the same seven bumble bee species were sampled during the bumblebee foraging seasons of 2015 and 2017  loci. These 16 MS loci gave reliable signals in previous research using different bumblebee species47: BL13, BT02, BT23, BT24, BL02, BT04, BT05, BT08, and BT1048; B100, B11, B126, and B13249; and 0294, 0304, and 081050; , were performed with the method as described in Maebe et al.51. The fragments were examined and scored manually using Peak Scanner Software v 2.0 (Applied Biosystems).DNA extraction of individual bumblebee workers were performed on one middle leg using a Chelex DNA extraction protocol as described in Maebe 0; Table . MS were52, GenAlEx v6.553, and Microchecker54, respectively. As described in Maebe et al.47, we removed all specimens which could not be scored in a reliable manner for at least 10 loci, and retained only one sister per colony by detecting full-siblings with the programs Colony 2.055 employing corrections for genotyping errors (5% per locus), and by the 2 allele algorithm and consensus method implemented in Kinanalyzer56.All populations were tested for genotypic linkage disequilibrium, deviations from Hardy-Weinberg equilibrium (HW) and the presences of null alleles using the program Fstat 2.9.3HE) and the observed heterozygosity (HO)57 were determined with GenAlEx v6.553 for all populations per species. Furthermore, we estimated the sample size-corrected private allelic richness (AR) with the program Hp-Rare 1.158 normalized to 10 gene copies.Nei’s unbiased expected heterozygosity (AR and HE in RStudio59 with R package lme4 version 1.1–1060. The model included country as fixed factor and microsatellite loci as random factor to account for inter-locus variability62. R package multcomp was used to perform Tukey HSD post-hoc comparisons63.Differences in genetic diversity levels between countries were investigated per species by linear Mixed Models (LMMs). LMMs were performed for both Bombus species was inferred by estimation of pairwise FST and Dest64 with 999 permutations using Genalex v6.553. Furthermore, Principal Coordinates Analysis (PCoA) were made using standardized genetic distance matrix to check for population substructuring.Population differentiation within each 65. The number of best fitting populations (K) was explored using the admixture model which was set with 500,000 burn-in steps and 1,000,000 samples. For each species, K-values ranged from 1 to 10, and were repeated 9 times. The best K-value was determined by the Evanno method66 imbedded in the program Structure Harvester v. 0.6.9467. A final bar plot for the best K-value was created by using the replicate structure runs at this K-value in CLUMPP68. Membership coefficients were depicted using Distruct v.1.169.Per species population structuring was also investigated by performing a Bayesian clustering algorithm imbedded in the software Structure v. 2.3.3Bombus species was also inferred with another Bayesian clustering method, Geneland 4.0.670. Geneland adds the effect of geographic location on the estimation of best fitted K-values, by estimation of K including the spatial coordinates into the model. Population assignment model, with correlated allele frequency and null allele correction, was run for K ranging from 1 to 10 with 1,000,000 iterations, 100 thinning and 1,000 burn-in, and a spatial coordinate uncertainty of one. All other parameters were set as default.Finally, population structure within each Supplementary datafiles