Aedes albopictus is a highly invasive disease vector with an expanding worldwide distribution. Genetic assays using low to medium resolution markers have found little evidence of spatial genetic structure even at broad geographic scales, suggesting frequent passive movement along human transportation networks. Here we analysed genetic structure of Aedes albopictus collected from 12 sample sites in Guangzhou, China, using thousands of genome-wide single nucleotide polymorphisms (SNPs). We found evidence for passive gene flow, with distance from shipping terminals being the strongest predictor of genetic distance among mosquitoes. As further evidence of passive dispersal, we found multiple pairs of full-siblings distributed between two sample sites 3.7 km apart. After accounting for geographical variability, we also found evidence for isolation by distance, previously undetectable in Ae. albopictus. These findings demonstrate how large SNP datasets and spatially-explicit hypothesis testing can be used to decipher processes at finer geographic scales than formerly possible. Our approach can be used to help predict new invasion pathways of Ae. albopictus and to refine strategies for vector control that involve the transformation or suppression of mosquito populations. Aedes albopictus, the Asian Tiger Mosquito, is a highly invasive disease vector with a growing global distribution. Designing strategies to prevent invasion and to control Ae. albopictus populations in invaded regions requires knowledge of how Ae. albopictus disperses. Studies comparing Ae. albopictus populations have found little evidence of genetic structure even between distant populations, suggesting that dispersal along human transportation networks is common. However, a more specific understanding of dispersal processes has been unavailable due to an absence of studies using high-resolution genetic markers. Here we present a study using high-resolution markers, which investigates genetic structure among 152 Ae. albopictus from Guangzhou, China. We found that human transportation networks, particularly shipping terminals, had an influence on genetic structure. We also found genetic distance was correlated with geographical distance, the first such observation in this species. This study demonstrates how high-resolution markers can be used to investigate ecological processes that may otherwise escape detection. We conclude that strategies for controlling Ae. albopictus will have to consider both passive reinvasion along human transportation networks and active reinvasion from neighbouring regions. Aedes albopictus, is one of the world’s most dangerous invasive species . It has been implicated in recent outbreaks of chikungunya [Ae. albopictus with pesticides has proven increasingly difficult due to insecticide resistance, particularly among populations within the native distribution of this species [The Asian Tiger Mosquito, kungunya  and dengkungunya  in the tkungunya , 4, and kungunya , 6. Mini species –10, whic species .Wolbachia has been proposed as a viable alternative to pesticide-based population suppression [Ae. albopictus in Guangzhou, China, that has undergone releases of Wolbachia-infected males to suppress populations at two locations since March 2015. Guangzhou region is within the native distribution of Ae. albopictus, and experiences occasional dengue outbreaks despite local absence of the primary vector of dengue, Ae. aegypti [Aedes albopictus females in Guangzhou are normally superinfected with two Wolbachia strains, wAlbA and wAlbB [Wolbachia-based population suppression has been conducted by releasing males that carry an additional strain, wPip, that has been transferred from Culex pipiens (Diptera: Culicidae) [Wolbachia releases are able to suppress Ae. albopictus populations sustainably over a large geographic region depends on the frequency at which suppressed sites are reinvaded by mosquitoes dispersing into the sites from outside. This reinvasion determines the frequency and intensity at which releases need to be repeated to maintain population suppression.Modification of mosquito populations using the endosymbiotic bacterium pression . This st aegypti . Aedes and wAlbB , and Wollicidae) . This poAe. albopictus is needed. Dispersal in Ae. albopictus is generally thought to represent a combination of short-range active flight of adults and long-range passive movement of immature stages along human transportation networks [Ae. albopictus as an invasive species likely reflects its ability to disperse along human transportation networks such as shipping routes [Ae. albopictus populations also show low differentiation within their native range [To estimate the susceptibility of a region to reinvasion an understanding of basic dispersal parameters in networks , 15–18. g routes  and roadg routes –23, withg routes , 24. Forve range , 26. Somve range , though Ae. albopictus samples within countries [Ae. aegypti, the primary dengue vector [Ae. albopictus are comparable to those in Ae. aegypti . Howevemosquito .Ae. aegypti at genome-wide single nucleotide polymorphisms (SNPs) discovered through double-digest restriction-site associated DNA sequencing  have prddRADseq , 42, 43,ddRADseq . Until nellites , with an additional step of RNAse treatment. From the 12 sample sites, we selected 152 individuals for ddRAD sequencing.DDsilico [in silico digestions of the Ae. albopictus genome assembly AaloF1 [DDsilico calculates how many sequenceable fragments of a given bin size can be produced for each enzyme pair. Two frequent cutter enzymes, MluCI and NlaIII, produced an optimal number of fragments for a library size of 50 within a fragment length range 350–450bp and desired average read depth > 20. This enzyme combination has also been used to construct ddRADseq libraries in Ae. aegypti [We used the program DDsilico  to perfoy AaloF1  using di aegypti –33, 43.MluCI and NlaIII restriction enzymes , NEB CutSmart buffer, and water. Digestions were run for 3 hours at 37°C with no heat kill step, and the products were cleaned with 60 μL Ampure XP paramagnetic beads . These were ligated to modified Illumina P1 and P2 adapters overnight at 16°C with 1000 units of T4 ligase , followed by a 10-minute heat-deactivation step at 65°C.We performed an initial digestion of 100 ng of genomic DNA in a 40 μL reaction, using 10 units each of Ae. albopictus were sequenced in three Illumina HiSeq2500 lanes using 100 bp paired-end chemistry.We performed size selection with a Pippin-Prep 2% gel cassette  to retain DNA fragments of 350–450 bp. Final libraries were created by pooling eight 10 μL PCR reactions per library, each consisting of 1 μL size-selected DNA, 5 μL of Phusion High Fidelity 2× Master mix  and 2 μL of 10 μM standard Illumina P1 and P2 primers, run for 12 PCR cycles. These were cleaned and concentrated using an 0.8× concentration of Ampure XP paramagnetic beads  to make the final libraries. Three libraries containing a total of 152 Ae. albopictus reference nuclear genome AaloF1 [Ae. albopictus mitochondrial genome [Wolbachia strains wAlbB [wPip [Ae. albopictus and the two Wolbachia genomes. We allowed for up to 3 mismatches in the alignment seed, and uniquely aligned reads were analysed with the Stacks pipeline [We processed raw fastq sequences within the customized pipeline of Rašić et al. , using te AaloF1  followedl genome , and thens wAlbB  and wPipbB [wPip , with albB [wPip . Note thpipeline , which wwPip was necessary as one of the sampling sites, Shazi Island (Site 11), had undergone releases from March 2015 of Ae. albopictus males carrying this Wolbachia strain in addition to the naturally occurring wAlbA and wAlbB. Although mosquitoes were irradiated before release to ensure any females remaining in the sample could not reproduce and introduce the wPip strain into the population [wPip genome than other study sites. Dadaosha Island (Site 12) also underwent wPip male-releases, but these began in March 2016 after the sampling for our study had taken place.The alignment to pulation , there wAedes genome is thought to contain approximately 2.1 megabases per cM [The Stacks program Populations was used to export VCF files for additional filtering with the program VCFtools . We firss per cM , 250 kbps per cM . Our fink [k > 0.1875 are full-siblings, and those with 0.1875 > k > 0.09375 are half-siblings, if each pair is assigned the most likely kinship category [Analyses of population structure are generally biased when closely-related individuals such as full-siblings are included in the analyses . To idenk  using thk . First ak , 62–64, category . We sampAe. aegypti full-siblings have been caught in traps up to 1.3 km apart [Ae. albopictus [k was more likely than the next most likely kinship category, followed by tests that assumed that the kinship category assigned using k was less likely to be correct. Thus, for pairs with k > 0.1875, tests would determine whether the pair were full-siblings or half-siblings, while for pairs with 0.1875 > k > 0.09375 tests would help determine whether the pair were full-siblings, half-siblings or unrelated. Tests were run using 10,000,000 simulations of random genotype pairs for each.We were also interested in observing related pairs at different sampling sites. Larval km apart , well abbopictus , 34–37. bopictus  to perfoWe first identified local geographical features that could potentially act as either dispersal barriers or as conduits for passive dispersal. Potential dispersal barriers were high capacity highways and major river tributaries and conduits for passive dispersal were rivers, highways and ports/shipping terminals. High capacity highways were designated following the key of the “World Street Map” basemap file in ArcMap 10.3.1 from ESRI . Major r2 = 0.695, P < 0.001). The highway network was constructed based on the “Highways” shapefile from MapCruzin (http://www.mapcruzin.com/free-china-country-city-place-gis-shapefiles.htm). Positions of sample sites relative to each network are shown in To investigate passive dispersal along the river, highway and port networks we first generated a score for each individual for each of the three network types describing its isolation from the network. Isolation from the river network (“River Isolation”) was calculated as the log-transformed Euclidean distance to the nearest river segment, while isolation from the port network (“Port Isolation”) used the distance to the nearest of five shipping terminals . We assessed isolation from the highway network (“Highway Isolation”) by constructing a metric as the square root of the total area within a 1 km radius not covered by the highway network, assuming an average highway width of 30 m. This approach was used rather than distance to the highway network because it was considered to better represent highway activity near a site. A similar metric calculated for the railway network was omitted due to high correlation with the highway network  dispersve range .http://www.gzcdc.org.cn/). We averaged Breteau Indices from 85 locations over the three months prior to sampling, then interpolated the scores using Ordinary Kriging in ArcMap 10.3.1 [http://www.arcgis.com/home/item.html?id=2354af91ee294bd3825c27dfa914a9a7), assigning values from -1 (no vegetation) to 1 (completely vegetated). The two estimates of habitat quality were positively correlated, but not at 95% confidence .We calculated the Breteau Index from fortnightly data available on the Guangzhou Centre for Disease Control and Prevention website (p 10.3.1 . KrigingD [a [amova (R package “pegas” [mantel) to investigate correlations between genetic distance, geographical distance and each of the five landscape variables. We then used paired Mantel tests (function mantel.paired) to investigate the contribution of each variable with the effects of geographic distance removed, and vice versa (testing the effect of geographic distance after removing each landscape variable).We used SPAGeDi to calculate Nei’s D  as a meaD [a  for a meD [a  with the “pegas” ) to part “pegas” . We perf “pegas” , partial “pegas”  and dist “pegas”  to assespcnm to transform the matrices of geographical distance and additive network isolation into principal components (PCs). We built two dbRDA models: the first treating geographic distance as an explanatory variable (dbRDA1), and the second where geographic distance effects were partialled out (dbRDA2). We constructed dbRDA1 using the first two PCs from each of the distance and network matrices. In dbRDA2, we performed an initial dbRDA of the PCs of distance on genetic distance and retained the four PCs that were significant  were used for dbRDA, significance testing with ANOVA and P-value adjustment, respectively.Terms were added to each model sequentially using the adjusted Rared (η2 ) as a mea showed significant spatial autocorrelation potentially indicating IBD , with accession numbers SAMN07738910—SAMN07739061. Geographical coordinates of each sample have also been deposited and are retrievable with the above.Aligned sequences for 152 k ≤ 0.474, 0.10% of pairs) and a single probable half-sibling group  with members spread between two sample sites 3.657 km apart  were definitely full-siblings (P < 0.001) and not half-siblings , while the remaining three (0.224 < k < 0.248) could be of either relationship category. Sites 8 and 9 were connected by highways which may facilitate passive dispersal between them.Comparisons across sample sites revealed four probable full-sibling kinship groups  and 7 pairs (0.82%) were half-siblings (0.105 ≤ k ≤ 0.183). A histogram of k scores showed fewer scores near k = 0.1875, the full-sibling/half-sibling category boundary, with the number of full-sibling pairs increasing sharply with k  were full-siblings . A simple Mantel test on matrices of individual genetic distance and log-transformed geographic distance showed a small but significant correlation (The AMOVA showed significant genetic structuring among sampling sites (P < 0.001), accounting for 8.1% of the observed variation , with considerable variability at small spatial scales. However, these broad-scale analyses could be potentially biased by the two sites in the south, Shazi Island (Site 11) and Dadaosha Island (Site 12), as in addition to them being distant from the northern sites, they were also semi-rural as opposed to urban, and scored more highly for “Highway Isolation” (7.98 ± 3.47) than the other sites (2.72 ± 1.15). Therefore, for an analysis containing all pairwise comparisons, we could not separate the effects of spatial and non-spatial influences on genetic structure.Nei’s D scores with several subsets of sites, as detailed in D scores 75.8% higher than the average for all other sites. This site showed an IBD pattern  but it was due entirely to the distances between this site and Sites 11–12. We excluded this site from analyses, leaving the two southern sites (Sites 11 and 12) and the nine northern sites . As “Highway Isolation” showed no spatial dependence among the northern sites , we could investigate patterns of IBD among these sites which would likely not be confounded by the highway network. Likewise, by investigating IBD between the northern sites and Sites 11 and 12 in isolation, we could avoid potential bias caused by discontinuous sampling between the northern and southern sites, or potential structuring between urban sites (northern sites) and semi-rural sites (southern sites).To explore this further, we investigated the spatial dependence of pairwise Nei’s 2 = 0.136, P < 0.027) at distances of 3.66–26.98 km. We then performed separate analyses between the northern sites and Site 11 (blue squares) and Site 12 (yellow diamonds), which showed strong IBD at distances of 17.23–37.08 km  and 28.57–49.34 km  respectively. These results suggest a pattern of IBD that is unconfounded with the effects of highway, port or river networks, and unbiased by discontinuous sampling.We first analysed the nine northern sites only (white crosses on grey), which showed mild IBD  individuals with all individuals, there was no statistically higher rate of alignment to wPip in Shazi Island . “River Isolation”  had a negative but nonsignificant correlation with the Breteau Index and “Port Isolation”  showed no correlation. The same general pattern was observed between the NDVI and “Highway Isolation” , “River Isolation”  and “Port Isolation” , though none of the relationships were significant at the 95% confidence level. These results suggest that as connectivity to the highway network increases there is a corresponding decrease in Ae. albopictus habitat quality.The Breteau Index was strongly and positively correlated with “Highway Isolation” , genetic distances increased with spatial distances irrespective of whether the northern sites were analysed among themselves or whether they were analysed in relation to either of the two southern sites (Sites 11 and 12). As these northern sites were all highly urbanised and their isolation scores from each of the highway, river and port networks showed no spatial structuring, it does not appear that this pattern of IBD is confounded with either an urban/rural cline or any of the human transportation networks. However, the two distant southern sites, both of which were less urbanised and more isolated from the highway network than the northern sites, exhibited higher genetic distances that could be due to any combination of reduced active dispersal leading to IBD, reduced gene flow along highways, or reduced gene flow between urban and rural areas, as has been proposed [The structure observed between populations in this study (8.1%) is comparable with , 27 or h markers –23 that  markers , 28. Ourproposed .Ae. albopictus separated by tens of kilometres than that observed in a study of an urban Ae. aegypti separated by less than 3.5 km  [Ae. albopictus is only slightly greater than that of Ae. aegypti [Ae. albopictus may reflect higher dispersal rates along human transport networks in this mosquito. We found that individuals sampled greater distances from shipping terminals were generally more genetically distinct than those sampled nearer to either network. Guangzhou has recently taken several steps to reaffirm its position as a major regional shipping hub [Ae. albopictus collected near the ports are due to the local movement of vessels between ports, or to a common source of imported mosquitoes that are distributed to all shipping terminals.Mantel tests on individual genetic distances showed only marginally higher spatial dependence  among  < 0.05) . Conside aegypti , 88, theping hub , and maiAe. albopictus along highways is thought to facilitate dispersal inland from coastal invasion sites [Ae. aegypti imply a similar dispersal process [Ae. albopictus have been conducted in areas much less urbanised than Guangzhou, such as within Madagascar and Réunion [Ae. albopictus density. Thus, while highly connected sites may have higher than average migration rates, the total number of migrants along the network will be low  and in Kuala Lumpur by Wolbachia Malaysia http://repository.imr.gov.my/wolbachia/. These programs aim to permanently infect local populations with virus-inhibiting Wolbachia [Drosophila melanogaster [Ae. albopictus males carrying multiple infections of Wolbachia are released to mate with wild females, which then produce inviable embryos, leading to local population crash [Ae. aegypti that exhibited seasonal fluctuations in density, resulting from either active dispersal or human transportation along roads [Ae. albopictus [The findings from this study inform future control projects that rely on releases of sterile individuals ( O'Neill ) and impolbachia  transinfnogaster . This dion crash . For eitng roads . In Guanbopictus , and alibopictus .Ae. albopictus in Guangzhou, facilitated by human transport networks. Similarly-sized cities could show similar genetic patterns, though this will likely depend on whether the local highway network occupies areas of suitable Ae. albopictus habitat. Genetic differentiation may be weaker in recently invaded cities due to founder effects, though this would depend on the frequency of repeated introductions [Ae. albopictus range.Our findings point to the complex processes of gene flow among ductions  and theiductions , allowinS1 Table(CSV)Click here for additional data file.S2 Tablea and any of the variables representing barriers or network isolation.Mantel tests found no significant relationships between Rousset’s (XLSX)Click here for additional data file.S1 FigColour codes are the same as in (TIF)Click here for additional data file.


Haematobia exigua is an obligate bloodsucking ectoparasite of livestock. As an initial step towards understanding its population structures and biogeographic patterns, we characterized partial cytochrome c oxidase subunit I (COI) and cytochrome b (Cytb) sequences of H. exigua from three distinct geographic regions in Southeast Asia. We detected two distinct mitochondrial haplogroups of H. exigua in our surveyed geographic regions. Haplogroup I is widespread in the Southeast Asian mainland whereas haplogroup II is generally restricted to the type population Java Island. Both haplogroups were detected co-occurring on Borneo Island. Additionally, both haplogroups have undergone contrasting evolutionary histories, with haplogroup I exhibited a high level of mitochondrial diversity indicating a population expansion during the Pleistocene era dating back to 98,000 years ago. However, haplogroup II presented a low level of mitochondrial diversity which argues against the hypothesis of recent demographic expansion.Uncovering the hidden diversity and evolutionary history of arthropods of medico-veterinary importance could have significant implications for vector-borne disease control and epidemiological intervention. The buffalo fly  Particularly, the discovery of distinct genetic structures has immense epidemiological implications because different populations of vectors may present variable susceptibility levels to pathogen infections3.Empirical knowledge of population genetics and the evolutionary background of arthropod vectors can be used to understand vector and pathogen interactions, anticipate risks, and develop control strategiesHaematobia exigua is an obligate bloodsucking ectoparasite of livestock, specifically cattle and buffalo in the Australasian and Oriental regions5. To better understand this notorious pest at a molecular level, several genetic approaches have been conducted to resolve the taxonomic boundaries between H. exigua and its congener H. irritans7. While H. exigua has been recognized as a distinct species, its population genetics and evolutionary history have not been characterized so far.The buffalo fly H. exigua where this species was first described on the island of Java, Indonesia4. In the past few decades, the demographic history of certain organisms in Southeast Asia has been a topic of intense interest for many researchers12. During the last glacial period, several regions such as northern and eastern Borneo, northern and western Sumatra, and the Mentawai islands in South East Asia were the refugium sites for some organisms while the mainland areas—Thailand and peninsular Malaysia were severely affected by the Pleistocene drought9. Nevertheless, there is convincing evidence for the existence of glacial refugia on the mainland10. However, the responses of H. exigua in Southeast Asia to these major historical climate changes, are yet to be investigated.The Southeast Asia is home to the type locality of H. exigua from four countries across a geographic range of over 2,600 km in Southeast Asia , cytochrome b (Cytb) and NADH dehydrogenase subunit 5 (ND5) genes were found to be more variable and informative in resolving the intra- and inter-specific relationships between H. exigua and H. irritans. These three genes were therefore adopted in the present study for a preliminary assessment of the genetic divergence of H. exigua collected from various geographic regions. However, the ND5 gene appeared to be insensitive at a species level because it provided a less-resolved topology that was incongruent with the COI and Cytb genes. Hence, further analyses were performed by using the latter two genes as molecular markers in this study.Of several mitochondrial and nuclear genes tested in our previous studyHaematobia taxa. The ML tree for the concatenated sequences of COI and Cytb is shown in Fig. H. exigua: haplogroup I is composed of populations from the Southeast Asian mainland , and Borneo; whereas haplogroup II includes populations from the islands of Java and Borneo. Interestingly, both haplogroups were detected in our samples from Borneo, albeit with only one specimen assigned to haplogroup II. The congener H. irritans formed a well-supported basal assemblage (Table Maximum likelihood (ML), maximum parsimony (MP), and neighbor-joining (NJ) phylogenetic analyses led to similar hypotheses for the evolutionary assemblages of ge Table .Figure 2Haematobia spp. PTP analysis differentiated H. exigua into two distinct OTUs, corresponding to the identified haplogroups. However, GMYC analysis recognized all H. exigua populations as single OTU. Both analyses identified H. irritans as a valid species  and generalized mixed yule-coalescent (GMYC) analyses revealed discordant results with respect to the numbers of operational taxonomic units (OTUs) within ies Fig. .r = 0.6461; P = 0.0007)  (data not shown).The Mantel test for isolation by distance suggested a significant correlation between genetic distance and geographic distance (07) Fig. . ComparaST = 0.198) but there was a high gene flow (Nm = 2.03) between populations from the mainland and Borneo. In contrast, high levels of genetic differentiation and low gene flow were identified between populations from the mainland and Java , as well as between Borneo and Java  , suggesting that sampling was complete and additional sampling was not required. Accordingly, the genetic divergences and demographic histories of the two haplogroups were compared in the subsequent analyses.Haematobia exigua haplogroup I differed from haplogroup II by 0.12 to 0.95% and from H. irritans by 2.37 to 2.84%. Haplogroup II differed from H. irritans by 2.31 to 2.67%. The intra-specific distances ranged from 0.06 to 0.71%  but low nucleotide diversity (0.002) in haplogroup I, whereas low haplotype (0.002) and nucleotide (0.001) diversities were found in haplogroup II  and R2 statistic  from mismatch distribution tests , a high Raggedness index value  , but lower bootstrap values are expected within a species or closely related taxa16. Nevertheless, two species delimitation analyses revealed different taxonomic entities within H. exigua. PTP analysis recognized haplogroups I and II as two distinct OTUs, however, GMYC treated both haplogroups as a single OTU. If both haplogroups deserve species status, their genetic divergence should be taken into consideration such as is comparable to the divergence observed between closely related and uncontroversial species pairs17. The genetic distances between two haplogroups, however, were relatively low (0.12–0.95%), and were actually much lower than the differences between H. exigua and H. irritans (2.31–2.84%). Given these relatively slight differences, we tentatively conclude that H. exigua represents a single species, rather than two distinct species.Assessment of the species status of Simulium nobile De Mejiere also demonstrated similar genetic pattern on the mainland and islands in Southeast Asia18. Perhaps, a lack of genetic diversity is an ordinary characteristic of island populations, possibly because of the bottleneck effect, genetic drift, and isolation20.Haplogroup I exhibited higher genetic diversity than did haplogroup II. Haplogroup I revealed 49 unique haplotypes , high haplotype diversity (0.964), and genetic distances up to 0.71%. In contrast, haplogroup II revealed only six unique haplotypes , with extremely low haplotype diversity (0.002) and 0.36% genetic distances. The diversity of haplogroup I on the Southeast Asian mainland was greater than that of haplogroup II on Java Island. Our results are consistent with previous findings, in which a common simulid black fly H. exigua in Southeast Asia. A Mantel test detected a pattern of isolation by distance, revealing a significant relationship between pairwise genetic and geographic distances for the studied regions.The present study showed that geographic distance could have significant effects on the genetic structure of 21. The Java Sea is likely to be a barrier to gene flow between H. exigua on the mainland and Java, and between Java and Borneo. This hypothesis is supported by the high genetic differentiation and low gene flow in our datasets. Indeed, the oceanographic barrier to dispersal and gene flow has been suggested as a key factor driving diversification in several insects22. Nevertheless, the South China Sea did not have a limiting effect on gene flow for H. exigua on the mainland and Borneo. The observed moderate genetic differentiation could be due to the recurrent gene flow across both geographic regions or the sharing of a recent common history23 (see below). On the contrary, we certainly cannot exclude the possibility of gene flow via human-mediated transportation of fly-infested animals. Previous studies elsewhere have suggested that the natural dispersal ability of livestock ectoparasites could occur in parallel with human-mediated dispersal, leading to genetic admixture and high gene flow25.Java and Borneo islands are substantially segregated from the Southeast Asian mainland by the South China Sea and Java Sea, and this could be a factor associated with intra-specific genetic discontinuitiesH. exigua to historical climate change events, we conducted a series of demographic analyses based on mitochondrial DNA, and we detected remarkable differences between the two haplogroups of H. exigua based on multiple lines of evidence. A “star-like” network, a unimodal mismatch distribution, low values of the Raggedness index and the R2 statistic from mismatch distribution tests, along with the significant negative values of neutrality tests suggested that haplogroup I has a historical expansion pattern through the late Pleistocene dating back to 98,000 years ago. In the past few decades, several insects in Southeast Asia have also demonstrated demographic expansion during the Quaternary glaciation period27. The black fly S. angulistylum Takaoka & Davies in Thailand has the oldest demographic expansion for insects dating back up to 930,000 years ago28, whereas the Thai S. nododum Puri has the youngest history dating back to only 2,600–5,200 years ago29.To examine the response of 30. An extremely low level of genetic diversity, with low haplotype diversity and nucleotide diversities are also associated with bottleneck effects32, thus lending support to our hypothesis of a recent bottleneck in these populations.By contrast, haplogroup II has rejected the hypothesis of recent demographic expansion, as evidenced by all demographic analyses. Additionally, we also observed a multimodal mismatch distribution and this pattern could be an indicator of a recent bottleneckHaematobia taxa are neither protected nor endangered species, hence, no specific permits were required for this study.All experiments were performed in accordance with relevant guidelines and regulations of the University of Malaya. The research protocols were regulated and approved by the University of Malaya. H. exigua were collected from cattle farms in four countries across a geographic range of over 2,600 km in Southeast Asia including the mainland , Borneo , and Java (Indonesia) , University of Malaya, Malaysia.The congener Total DNA was isolated from each adult specimen, using the i-genomic CTB DNA Extraction Mini Kit . DNA was eluted in 50 μL of elution buffer and stored at −20 °C until further analyses. DNA amplifications were performed by polymerase chain reaction (PCR) using an Applied Biosystems Veriti 96-Well Thermal Cycler .et al.6. The PCR products were then sequenced in forward and reverse directions using BIG DYE Terminator v3.1 by an ABI 3730XL Genetic Analyzer . DNA sequences generated in this study are accessible from the National Center for Biotechnology Information (NCBI) GenBank under accession numbers KU599938-KU599978 for COI and KU599979-KU600012 for Cytb.Two sets of primers were used to amplify the COI and Cytb gene regions as described in Low 33. To examine whether each COI and Cytb dataset could be concatenated into a single dataset, statistical congruence was calculated using a partition homogeneity test implemented in PAUP 4.0b1034. No significant differences were found among separate gene regions (P = 1.00). Hence, COI and Cytb sequences were concatenated for all subsequent data analyses.COI and Cytb sequences were assembled using ChromasPro 1.7.6  and edited using BioEdit 7.0.9.035. An automatic model selection was implemented based on the Akaike information criterion (AIC). The best-fit model was the general time-reversible (GTR) model with a proportion of invariable sites of 0.676 and with a gamma shape parameter of 0.887. The MP tree was constructed using MEGA 6.036 with 10 random sequence additions and tree bisection reconnection (TBR) branch swapping. The MP bootstrap values were computed with 1000 resamplings. The NJ tree was constructed using PAUP 4.0b10. NJ bootstrap values were estimated using 1000 replicates with Kimura’s two-parameter model of substitution (K2P distance). The house fly, Musca domestica Linnaeus (KM200723) was used as an outgroup.Representative haplotype sequences were subjected to phylogenetic analyses. The ML analysis was performed on an on-line web-based server PhyML 3.037. A maximum likelihood solution (PTP_ML) model was applied, and analysis was run with 100,000 Markov chain Monte Carlo (MCMC) generations, thinning set to 100 and burnin at 0.1.To compare the discriminatory power with the species boundaries defined by the conventional phylogenetic analyses, we performed two species delimitation methods: poisson tree processes (PTP) and generalized mixed yule coalescent (GMYC). PTP analysis was performed with the bPTP web-server38 available in R 3.2.1.For GMYC analysis, the ultrametric tree was generated from the representative haplotypes in BEAST 1.8.236 using a relaxed lognormal clock, coalescent (constant size) prior and GTR + I + G model of DNA substitution. The analysis was run for 20 million generations, with a sampling frequency of every 100 generations. The output tree was analyzed in TreeAnnotator 1.8.2 with a 10% burn-in. The data were analyzed using a single threshold model in the software package SPLITS39. The correlation between genetic distance (FST) and geographic distance (km) was examined using a Mantel test40 implemented with the program Isolation by Distance Web Service 3.2341.Levels of genetic differentiation and gene flow were assessed using DnaSP 5.0p pairwise genetic distances were estimated using PAUP 4.0b10.To assess levels of variation among the delimited taxa based on PTP and GMYC analyses, uncorrected 42 in the program Network 4.6.Haplotype and nucleotide diversities were assessed using DnaSP 5.0. Haplotype network reconstructions based on haplogroups were performed using a median-joining algorithm43, Fu’s Fs44, Fu & Li’s D*45, Harpending’s raggedness index46, R2 statistic of Ramos-Onsins & Rozas47, and mismatch distribution tests were performed using DnaSP 5.0. If an expansion event has occurred, the time since expansion can be calculated using a mismatch calculator48. The expansion time was estimated according to a divergence rate of 2.3% per 1,000,000 years for insect mitochondrial DNA49.To test for population equilibrium and signature of population expansion, Tajima’s D


Gracilaria vermiculophylla (Rhodophyta) into estuaries in coastal western North America, the eastern United States, Europe, and northwestern Africa by genotyping more than 2,500 thalli from 37 native and 53 non‐native sites at mitochondrial cox1 and 10 nuclear microsatellite loci. Overall, greater than 90% of introduced thalli had a genetic signature similar to thalli sampled from the coastline of northeastern Japan, strongly indicating this region served as the principal source of the invasion. Notably, northeastern Japan exported the vast majority of the oyster Crassostrea gigas during the 20th century. The preponderance of evidence suggests G. vermiculophylla may have been inadvertently introduced with C. gigas shipments and that northeastern Japan is a common source region for estuarine invaders. Each invaded coastline reflected a complex mix of direct introductions from Japan and secondary introductions from other invaded coastlines. The spread of G. vermiculophylla along each coastline was likely facilitated by aquaculture, fishing, and boating activities. Our ability to document a source region was enabled by a robust sampling of locations and loci that previous studies lacked and strong phylogeographic structure along native coastlines.The identification of native sources and vectors of introduced species informs their ecological and evolutionary history and may guide policies that seek to prevent future introductions. Population genetics provides a powerful set of tools to identify origins and vectors. However, these tools can mislead when the native range is poorly sampled or few molecular markers are used. Here, we traced the introduction of the Asian seaweed  Predicting the environmental and evolutionary processes that facilitate invasions is one of the major goals of invasion biology  the lack of robust sampling of native and non‐native populations and (2) the lack of appropriately variable population genetic tools  Papenfuss (Rhodophyta), which has spread from its native distribution in the northwestern Pacific Ocean to virtually every high‐salinity, temperate estuary in Europe and North America , and 35 non‐native sites along the coastlines of western and eastern North America and Europe , whereas, in the non‐native range, there was a spectrum of sites ranging from fully attached to fully free‐floating G. vermiculophylla thalli  and incubated for 15 min at 37°C followed by 15 min at 80°C. Four microliters of 2 μmol/L primer was added to each product and sequenced in the forward direction commercially by Eurofins Genomics .coxI fragment, which delineated among several haplotypes and could be genotyped using the restriction enzyme Af1III  at the 945th base pair within the mitochondrial 2.22.2.14Peaks , aligned with the haplotypes from Kim et al. .A phylogeny of the haplotypes from Kim et al.  and new 2.2.2GenClone ver. 2.0  of the same genet.The number of repeated identical multilocus microsatellite genotypes (MLGs) was computed using F‐statistics in order to avoid distorting these estimates .Studies on the population genetics of clonal organisms remove repeated MLGs before calculating heterozygosity and other 2.2.3HE) was calculated using GenAlEx, ver. 6.5  was computed using rarefaction implemented in the program HP‐Rare, ver. 1.0  at the smallest sample size  was estimated using rarefaction in the R package poppr, ver. 2.2.1  and allele size (ρST) among sites along each of four coastlines: Japan, WNA, EUSA, and EU using genepop ver. 4.4 , a multivariate analysis that avoids making strong assumptions about the underlying genetic model  that explained 87.8% of the total variance for subsequent DAPCs . Based on this cross‐validation with the s Figure a.compoplot function in adegenet. Posterior group memberships were utilized in order to indicate admixture or the misclassification when prior groups are used to conduct the DAPC. Based on the mitochondrial SNP, we divided the native range into the “C” haplotype group and the “T” haplotype group corresponding to the break between ~35°N in Japan and South Korea in which the two SNPs dominated to the south and north, respectively  only the native sites and (2) sites from the native range and two of the three introduced coastlines. We transformed “new data” using the centering and scaling of training data  the native range alone or (2) the native range and the two introduced coastlines). Using the same discriminant coefficients, we predicted the position of the new individuals  all introduced sites and (2) the one introduced coastline not used in the training data).Next, we predicted the assignment of thalli from one region to another using supplementary individuals that were not used in model construction as implemented in Gracilaria vermiculophylla are out of Hardy–Weinberg equilibrium  and chose the value of K at the point at which the curve reached an asymptote. The lower the DIC value, the better fit of the model used . Second, we used the number of independent chains out of 20 that generated the major mode and the highest mean similarity score from clumpak.We determined the optimal number of R packages ape ver. 3.5  tree based on Jaccard distance using the 33.1cox1 haplotypes  of the thalli were “T” haplotypes and were dominated by haplotype 6 .Within the native range, microsatellite genotypes distinguished northern sites dominated by “T” n Figure . “T” vern Figure . At K = s Figure  showed sFST) and allele size (ρST), was high on average , but not with allele size  in the native range. Genetic differentiation in the native range, as measured using allele identity  thalli from the northern Japanese sites and other introduced shorelines along the second principal component axis, which itself explained ~19% of the variation Figure . The Bris Figure c, while e Figure e.FST~ 0.33 and ρST ~ 0.20; Table FST~ 0.15 and ρST ~ 0.18; Table FST; Figure ST, Figure The strength of differentiation among populations along a shoreline differed across non‐native coastlines. Within WNA and EU shorelines, sites exhibited greater levels of genetic differentiation , Californian (bob and tmb), Elkhorn Slough (elk), and Ensenada (ens) sites were composed of different genetic clusters Figure . SimilarAlong the EUSA coastline, most sites were composed of a homogenous set of genetic constituents, regardless of the number of genetic clusters Figure . The excAlong the EU coastline, Bayesian clustering revealed differences between sites sampled in Germany and Denmark  versus a group of French (frl) and Portuguese populations (far), while the remaining populations in Ireland, the United Kingdom, France, Spain, Portugal, and Morocco reflected admixture and a similar set of genetic constituents Figure . The NJ HE, AE, and eMLG) versus latitude along the EUSA and for genetic diversity metrics (HE and AE) versus latitude : Soukanzan (sou), Mangoku‐ura (mng), and Akkeshi . The strongest evidence of secondary introduction came from the three sites from Long Island Sound and Narragansett Bay . Bayesian clustering at 5 Figure  and the 5 Figure  suggeste5 Figure . For exa4Gracilaria vermiculophylla, reflecting low levels of contemporary gene flow. Introduced populations of North America and Europe exhibited mitochondrial and nuclear genotypes largely indistinguishable to those of the Pacific coastline of northeastern Japan . Because this area historically served as the principal source for oyster exports worldwide, we suggest that oysters were the key vector for the G. vermiculophylla invasion. We discuss each of these findings in detail below.Using a combination of mitochondrial and microsatellite genotyping, we discovered profound phylogeographic structure in the native range of 4.1In comparison with well‐studied biogeographic provinces, such as those in northeast (NE) Atlantic, less is known about the evolutionary history of the organisms that inhabit the northwest (NW) Pacific and it is not clear whether hypotheses drawn from patterns in other regions apply  as compared to Honshu and Hokkaido populations . Finally, the similarity of thalli sampled at Shikanoshima (shk) to thalli sampled from putative source sites  is likely due to the frequent fishery transport between Hokkaido and Kyushu , of which similar patterns have been found in the red seaweed Gelidium elegans . First records now align with the same decades in which Crassostrea gigas was introduced to WNA and EUSA estuaries. Mineur, Le Roux, Maggs, and Verlaque , Elkhorn Slough (elk), Puget Sound (ptw), and British Columbia  were composed of different genetic cohorts of G. vermiculophylla. This is consistent with the anecdotal histories of oyster introduction and cultivation in these locations  and Narragansett Bay (ris) and the other to the outer coast of Virginia and the Chesapeake Bay Figure . The firGracilaria vermiculophylla only date back to 1998, this alga likely occurred in the Chesapeake Bay and along New England coastlines for longer than currently thought and was misidentified as the native congeneric G. tikvahiae , Tomales Bay (tmb), and San Diego . Grosholz and Ruiz  and has subsequently been identified as G. vermiculophylla .Our genetic data suggest different patterns of secondary spread once and Ruiz  documentRelative to the case along the WNA coastline, the magnitude of secondary spread along the EU and EUSA coastlines is less speculative. Along the EUSA, the high levels of diversity observed in the sites studied along the eastern shore of Virginia Figure  stronglyG. vermiculophylla thalli from Loix (frl) and Marennes (fme) belonged to different genetic cohorts  to the Mediterranean . Nevertheless, some EU sites, such as Heiligenhafen (hei), were near marinas and could point to accidental within‐coastline transport by sailboats. Nyberg and Wallentinus . Birds have also been known to use gracilarioid seaweeds in nests . Along the EUSA, spread of G. vermiculophylla may be via shrimp nets and crab pots, as G. vermiculophylla is known to be a nuisance in some estuaries to shrimpers (Freshwater et al., The vector of secondary spread along the EU and EUSA coastlines is uncertain. Natural current patterns may contribute to the natural spread of thalli. Spread of Rueness, . Other sRueness, ; howeverlentinus  suggeste Arnold, , includi5Gracilaria vermiculophylla is now recognized as one of the most widespread and abundant marine invaders in the Northern Hemisphere (Kim et al., G. vermiculophylla has largely invaded, or the fact that cryptic species are common in seaweeds (Krueger‐Hadfield, Magill, Mieszkowska, Sotka, & Maggs, Codium fragile spp. tomentosoides colonized sites around the world for at least 100 years longer than previously reported from contemporary sampling.Gracilaria vermiculophylla invasion, in particular. Previous studies have suggested introduced populations evolved greater tolerance for heat stress and resistance to herbivory during the invasion (Hammann, Wang, Boo, Aguilar‐Rosas, & Weinberger, Our identification of a source region has implications for understanding the evolutionary ecology of the More broadly, Carlton  argued cNone declared.SAKH, NMK, and EES conceived the study; SAKH, NMK, JEB, MH, SJS, RT, FW, and EES collected samples; SAKH, NMK, and SJS extracted DNA; SAKH, NMK, SJS, TWG, and DM generated data; SAKH, AES, and EES analyzed data; JEB and AES contributed to discussions; SAKH and EES wrote the manuscript; all authors approved the final manuscript. Click here for additional data file. Click here for additional data file.


Glossina pallidipes is a major vector of both Human and Animal African Trypanosomiasis (HAT and AAT) in Kenya. The disease imposes economic burden on endemic regions in Kenya, including south-western Kenya, which has undergone intense but unsuccessful tsetse fly control measures. We genotyped 387 G. pallidipes flies at 13 microsatellite markers to evaluate levels of temporal genetic variation in two regions that have been subjected to intensive eradication campaigns from the 1960s to the 1980s. One of the regions, Nguruman Escarpment, has been subject to habitat alteration due to human activities, while the other, Ruma National Park, has not. In addition, Nguruman Escarpment is impacted by the movement of grazing animals into the area from neighboring regions during the drought season. We collected our samples from three geographically close sampling sites for each of the two regions. Samples were collected between the years 2003 and 2015, spanning ~96 tsetse fly generations.e estimates averaged 594 in Nguruman Escarpment and 1120 in Ruma National Park. This suggests that genetic diversity is similar to what was found in previous studies of G. pallidipes in Uganda and Kenya, implying that we could not detect a reduction in genetic diversity following the extensive control efforts during the 1960s to the 1980s. However, we did find differences in temporal patterns of genetic variation between the two regions, indicated by clustering analysis, pairwise FST, and Fisher’s exact tests for changes in allele and genotype frequencies. In Nguruman Escarpment, findings indicated differentiation among samples collected in different years, and evidence of local genetic bottlenecks in two locations previous to 2003, and between 2009 and 2015. In contrast, there was no consistent evidence of differentiation among samples collected in different years, and no evidence of local genetic bottlenecks in Ruma National Park.We established that allelic richness averaged 3.49 and 3.63, and temporal NG. pallidipes population genetics, and reinforces the importance of long term monitoring of vector populations in estimates of parameters needed to model and plan effective species-specific control measures.Our findings suggest that, despite extensive control measures especially between the 1960s and the 1980s, tsetse flies in these regions persist with levels of genetic diversity similar to that found in populations that did not experience extensive control measures. Our findings also indicate temporal genetic differentiation in Nguruman Escarpment detected at a scale of > 80 generations, and no similar temporal differentiation in Ruma National Park. The different level of temporal differentiation between the two regions indicates that genetic drift is stronger in Nugruman Escarpment, for as-yet unknown reasons, which may include differences in land management. This suggests land management may have an impact on The online version of this article (10.1186/s13071-017-2415-y) contains supplementary material, which is available to authorized users. Glossina) are the major insect vectors of Human African Trypanosomiasis (HAT) and Animal African Trypanosomiasis (AAT), serious animal and human diseases in sub-Saharan Africa [Tsetse flies  and Ruma National Park (Ruma), that share similarities in ecology and evolutionary processes, and a history of successful suppression in the 1960s to the 1980s [G. pallidipes population dynamics. This information will help in making empirically derived vector control and monitoring recommendations for these regions in southwestern Kenya that have proven difficult to manage and that are at risk of reemergence of HAT from neighboring regions to the northwest.In this study, we use 13 microsatellite loci to describe temporal patterns of genetic variation in he 1980s –23 with he 1980s , 25. Howhe 1980s –29, wherhe 1980s . Here, w2 area that lies north of the Kenya/Tanzania border that is managed for community use [G. pallidipes population density in 1987 [2 protected area east of the Kenya/Uganda border that is managed for wildlife conservation [The samples used in this study were collected from Nguruman Escarpment and Ruma National Park in southwestern Kenya Fig. . The Ngunity use . Recent  in 1987 , but the in 1987 , 16, 19.ervation . Past coervation , 22, butervation .Fig. 1MaG. pallidipes were collected using bi-conical or Ngu traps that were set in clusters of 3–5 traps separated by less than 5 km. Collected flies were preserved in 80% ethanol, transported for a maximum of 5 days at room temperature, and stored at 4 °C. Later, a subsample was chosen for DNA extraction and microsatellite screening. For Nguruman, we screened an average of 38 individuals per site, collected from three locations spaced < 22 km apart , 0.5 μl each of 10 mM forward and reverse primers, 1.1 μl of 25 mM MgCl2, 1.1 μl of 10 mM dNTP mix, and 0.1 μl of 5 U/μl GoTaq DNA polymerase. Additional file G. pallidipes [G. morsitans or G. fuscipes [G. pallidipes [G. pallidipes [G. pallidipes prior to their inclusion in this study, we tested them in two individuals from four sampling sites using PCR amplification protocols used in other tsetse species [. For all markers, PCR products were multiplexed in groups of two or three loci . Alleles were scored using the program GeneMarker v 2.4.0 . For all 13 markers, to ensure repeatability of genotype calls, we manually edited the automatically scored peaks twice independently following agreed upon binning rules  or the Qiagen DNAeasy blood and tissue  extraction kits, following the manufacturer instructions. We used the Promega GoTaq kit  together with fluorescently-labeled primers for a 15 μl PCR reaction as follows: 1 μl of DNA template, 6 μl of distilled Hllidipes   and expected (HE) heterozygosity were estimated using Arlequin v3.5 [IS) and deviations from HWE expectations were tested using FSTAT v2.9.3 [e) using the two-sample temporal method [To assess patterns of genetic diversity for all samples singly and grouped by time point, we estimated allele frequencies using GenAlex v6.502 , and alluin v3.5 . InbreedT v2.9.3  based onl method  developel method  with thel method . We usedl method  because l method , 44, 46,We also evaluated the occurrence of recent bottlenecks for all samples singly and grouped by time point using the unilateral Wilcoxon test for heterozygosity excess implemented in the program BOTTLENECK v1.2.02 . These tTo assess genetic structure among samples, we used the Bayesian clustering method implemented in STRUCTURE v2.3.4 . This meST in Arlequin v.3.5 [P-values. With the resulting F-statistics converted to FST/(1-FST), we tested for isolation by distance, both geographically (km) and temporally (generations), using Rousset’s procedure [To assess levels of genetic differentiation among both geographically and temporally spaced samples, we estimated pairwise Fin v.3.5  with Wriin v.3.5 , followiin v.3.5  and usinrocedure  implemenrocedure . Geograprocedure , and therocedure . Temporarocedure –64). Temd to FST/-FST, we rocedure  with 10,rocedure . Allele MICROCHECKER indicated null alleles in GpB6B and Gmm8. Results from tests for per-locus deviations from HWE and LD are presented in Additional file E) and observed (HO) heterozygosity was similar among replicates between sampling points, with HO ranging between 0.406–0.504 . Alleli 3.2–5.6 , and thipansions . Anothere estimates were similar to those from other studies either on the same [G. fuscipes fuscipes [e estimates.Nthe same , 25 or afuscipes –73. Estifuscipes , could pe generations ago [G. pallidipes in previous studies [G. pallidipes, severe bottlenecks can probably be detected as far back as ~1400 generations, or 175 years, assuming Ne is close to the mean of ~700, as reported in other studies [Results from tests for bottlenecks do not provide strong evidence of significant genetic bottlenecks in either region. Although the methods used can only detect extreme reductions in population sizes that occurred more recently than 2–4 Nions ago , 76, the studies , 75. In  studies –73, and  studies –64. Inde studies  were sigG. pallidipes, we assessed levels and patterns of geographical and temporal genetic differentiation among samples from the two regions. We found no significant FST estimates or differnces in allelic or genotypic frequencies among geographically spaced samples collected during the same time interval in each region (Tables G. pallidipes studies [G. F. fuscipes, where significant FST estimates were found at a spatial distance of just 5 km [G. pallidipes moves greater distances than G. F. fuscipes, or that the external environment in Nguruman and Ruma have facilitated gene flow in these regions.To evaluate the long-term population dynamics of n Tables , 5, and n Tables . Althougn Tables  and leve studies , this reust 5 km , 55. TheG. pallidipes by Ouma & Krafsur [G. fuscipes fuscipes [G. pallidipes and can be detected at a scale of > 80 generations under some conditions. These findings also suggest that previous studies could not detect temporal differnetioan in Nguruman [We identified significant temporal genetic differentiation in Nguruman, but not in Ruma. In Nguruman, we found significant genetic differentiation between samples collected before and after 2009 Tables . These r Krafsur  and Ouma Krafsur , and in fuscipes , 57, whifuscipes  and Oumafuscipes  studies fuscipes , 57 studfuscipes  focused Nguruman  because e, and tests for bottlenecks indicate a similar response to intensive control efforts between the 1960s and the1980s between Nguruman and Ruma. There was no evidence of significantly reduce genetic diversity, and estimates were similar to those reported in other regions without a history of intensive control measures [G. pallidipes, even massive control efforts have failed to have a long-term influence on genetic diversity and allele frequency. This could be because control measures were not maintained for long enough to impact the genetic diversity, or because there were recolonizations from neighboring regions after the control measures were discontinued.Genetic diversity, Nmeasures , 25. FurG. pallidipes habitats in Nguruman in ways that did not occur in Ruma, where land is fully protected from human use. We suggest that alteration of tsetse habitats due to human use [However, we did find differences in the results of the bottleneck tests and levels of temporal genetic differentiation between these two regions. Nguruman displayed higher levels of differentiation Fig. : Fig. S4uman use –29 may buman use , 80 and uman use  can helpuman use .Table 6FG. pallidipes, even massive control efforts have not had lasting influence on genetic diversity, and that temporal genetic differentiation occurs in G. pallidipes under some circumstances, such as human land use. These findings are important because they enhance our understanding of the process underlying the local persistence of G. pallidipes populations in southwestern Kenya over the past four decades, stress the importance of long-term monitoring and sustained control efforts in control of G. pallidipes in southwestern Kenya, and suggest that different habitat management can play a significant role in shaping levels of genetic differentiation in this vector. In addition, they also point out important knowledge gaps which can be addressed by future research, such as the need of densely spaced genomic markers and of a sampling design that includes both target and neighboring populations. This would facilitate estimates of key demographic parameters and reconstructions of recent and past gene flow levels and patterns among different sampling sites. Improved estimates will increase our ability to identify the ecological, evolutionary, and/or human-mediated process underlying the genetic changes between temporally spaced G. pallidipes samples.Our findings suggest that for


Jehlius cirratus across a broad portion of its geographic distribution using data from the mitochondrial cytochrome oxidase I (COI) gene region. Despite sampling diversity from over 3,000 km of the linear range of this species, there is only slight regional structure indicated, with overall Φ CT of 0.036 (p < 0.001) yet no support for isolation by distance. While these results suggest greater structure than previous studies of J. cirratus had indicated, the pattern of diversity is still far more subtle than in other similarly-distributed species with similar larval and life history traits. We compare these data and results with recent findings in four other intertidal species that have planktotrophic larvae. There are no clear patterns among these taxa that can be associated with intertidal depth or other known life history traits.We evaluate the population genetic structure of the intertidal barnacle  Haplotypes were coded by sample location and by regions separated by the iterative AMOVA results that maximize ΦCT to visually identify components of diversity associated with each regional group. Population diversity was also assessed at each sampled location; nucleotide diversity (π) and haplotype diversity (H) are estimated at each location using Arlequin.After quality control and alignment of sequence data using CodonCode Aligner v6.0.2 (CodonCode Corporation), data were formatted for analysis using Arlequin v3.5.2.2.  to identdistance ; this waKX014910 –KX015034. Site-specific diversity is presented in ST are presented in ST were very low and in general not statistically significant (p 0.245).New sequences were archived in GenBank under accession numbers nificant ; the onlJ. cirratus , there was statistical regional structure detectable with the increased power of sampling at that scale. Our implementation of spatial AMOVA  and sites to the north from all locations to the south; and Pichilemu (44°S) and all sites to the south from all locations to the north. No significant ΦSC was exhibited in these comparisons. If K = 3 groups are chosen using these same delineations, ΦCT was comparable .Although negligible structure was exhibited along the Chilean coast in al AMOVA  recovereocations . These lFrom these results, a haplotype network (minimum spanning tree) is presented in J. cirratus. Previous efforts had also noted that using alternate statistics such as ST and pairwise exact tests of population differentiation—suggests little actual spatial variation but sufficient sampling to identify the differential representation of regional samples in the 2 dominant haplotypes found  as well as the low intertidal (A. psittacus and C. concholepas). The two species that exhibit significant structure, each with two primary lineages and evidence for isolation by distance within each lineage, are in the high-to-middle intertidal  have at least some signal associated with the 30–32° oceanographic transition in upwelling (P. purpuratus and abalone C. concholepas do not. The association of genetic structure with the southern biogeographic boundary near 42°S (Mytilus chilensis, show little spatial structure at mitochondrial or other putatively neutral markers (L Besch & K Bockrath, 2015, unpublished data; Clearly a sample of only five taxa is insufficient for statistical consideration. However, what we can indicate is that all three barnacles (pwelling ; in contear 42°S  is far mThere is an expanding interest in exploration of genetic diversity within and among regional populations of intertidal species along the coast of Chile see , to infoN. scabrosus and J. cirratus, which are ecologically nearly indistinguishable (N. scabrosus exhibits significant phylogeographic structure (N. scabrosus appear to require longer times in the plankton and longer times for cyprid metamorphosis than J. cirratus (What remains unsatisfying is our ability to predict—based on what we know of life history, ecology, and other parameters of a given taxon—which species are likely to exhibit structure across a certain region, or why some species are able to spread across boundaries that others cannot . Haydon,uishable  with littructure , the larcirratus . Whether


Batrachuperus tibetanus, for its conservation, a phylogeographical survey was performed based on mitochondrial DNA and morphological data. The mitochondrial data revealed three lineages of B. tibetanus in the Qinling Mountains. A lineage present in the northwestern Qinling Mountains groups with the Tibet lineage of B. tibetanus, and the remaining Qinling populations are eastern and western lineages that separated ~3–4 million years ago (Ma). The eastern and western Qinling lineage delineation is supported by three morphological variables . The divergence of the two major lineages was likely caused by orogenesis of the Qinling Mountains during the late Cenozoic, and the two lineages were subsequently affected at different levels by Pleistocene climatic oscillations showing different signals of demographic expansion. A large suitable area of B. tibetanus through the Qinling Mountains since the last glacial maximum (LGM) indicated the adaptation of this species to the climatic changes. However, low genetic diversity within populations indicate the urgency of preserving the vulnerable populations and endemic lineages.The Qinling Mountains of China provide an excellent study area for assessing the effect of Pleistocene climatic oscillations and paleogeological events on intraspecific diversification. To assess genetic diversity of an endemic stream salamander,  In China, the continuing uplift of the Tibet Plateau, the highest plateau on earth, and associated climatic fluctuations appear to be the most important factors driving the geographic genetic diversification of populations in southwest China6, which is one of the most important biodiversity hot-spots in the world. Similar to the Tibet Plateau, the geographically adjacent Qinling Mountains provide another excellent area of China for evolutionary study of species. However, the Qinling Mountains have been less studied than the Tibet Plateau.Modern patterns of intraspecific genetic diversity presumably reflect cyclical Pleistocene climatic oscillations and Meso-Cenozoic intracontinental orogenesis. Most notably, cyclical Pleistocene climatic oscillations have caused extinction and repeated changes in the distributions of those species that survived in Europe and North America8, are a major mountain range extending over 1600 km from the east to the west in southern Shaanxi province of China. To the west is the northern edge of the Tibetan Plateau, while to the east are the plain and hilly areas of eastern China. The Qinling Mountains are an important natural barrier for the northern temperate regions and the semi-tropical southern ones, and form the watershed for the Yangtze and Yellow Rivers. Taibai Mountain is the highest peak of the Qinling Mountains (3767 m) and considered to be the center of glaciation in the Qinling Mountains with limited Late Pleistocene ice-cover13. The Qinling Mountains are located in an important geographical position with complex topography and variable climates and habitats, contributing to the biodiversity of the Eastern Asian flora and fauna by harboring many endemic species14, such as the giant panda (Ailuropoda melanoleuca) and the golden takin (Budorcas taxicolor bedfordi). In recent years, phylogeographical studies revealed that the Qinling Mountains probably served both as a major barrier and glacial refugium for plants and animals21.The Qinling Mountains, formed during the Mesozoic and Cenozoic periodsBatrachuperus tibetanus (family Hynobiidae) is endemic to China. It usually inhabits fast-flowing montane streams in the eastern edge of the Tibetan Plateau and the Qinling and Daba Mountains from 1600 to 4300 m above sea level22. It is threatened by habitat loss and over-hunting for traditional Chinese medicine and food, and thus listed as a vulnerable species in the IUCN  Red List category23. The stream salamanders are not only indicators of overall environmental health as are other amphibians24, but also are ideal species for evolutionary research on account of potentially strong phylogeographical signal and ease of sampling. Due to weak dispersal ability, stream salamanders tend to be highly structured genetically over short geographical distances26 and retain high-resolution genetic signals of historical processes that have shaped current phylogeographical patterns26. The closely related species of stream salamanders occurring at different elevations in southwest China may have experienced different evolutionary histories driven by topography and responses to glaciation26. For example, the stream salamanders living in the western high-elevation regions seem to have experienced colonization and population declines due to the last glaciation, while those in the eastern low-elevation regions appear to have experienced fragmentation during the extensive glacial period26. However, it is unclear how the population-genetic diversity of B. tibetanus in the Qinling Mountains was structured by historical processes and affected by topography, glaciation and drainage.The alpine stream salamander 16 and west-east or west-central-east breaks29, indicating that Qinling Mountains may have played different roles in evolutionary history of different species in this region. The current genetic patterns of stream-associated amphibians may have been shaped by drainage systems34. Thus, drainage systems ascribed to the Yangtze River and Yellow River may have influenced the distribution and population structure of B. tibetanus in the Qinling Mountains, and then generated a north-south break. This hypothesis appears to be supported by the distinct climates and habitats at both slopes of the Qinling Mountains that serve as the boundary of the Palearctic and Oriental realms. However, the Qinling Mountains could serve as a major barrier to generate the north-south break for species generally distributed in the low altitude localities of the northern and southern sides (e.g. <1200 m above sea level)16. In contrast, for species generally distributed in the high altitude localities of the Qinling Mountains, tectonic changes, Pleistocene climatic fluctuations and population history likely have resulted in the remarkable west-east and/or west-central-east breaks29, given that these species generally have weak dispersal abilities. The stream salamanders are generally distributed in the montane streams in the Qinling Mountains (>1200 m above sea level), and thus possibly affected by orogenesis of the Qinling Mountains and Pleistocene climatic oscillations13 resulting in a west-east break.Interestingly, there are two completely different phylogeographical patterns reported in the Qinling Mountains, i.e. north-south breakB. taibaiensis, which is distinguished from geographically neighboring species, B. tibetanus, by its large size  and the inverted V-shaped vomerine teeth35. However, the morphological characters of the stream salamanders are very conservative, and the allozyme data do not support the validity of B. taibaiensis, which corresponds to the eastern lineage of B. tibetanus25. Note that the allozyme data seem to lack sufficient variation to support the separation of B. taibaiensis and B. tibetanus25. Considering the complex and controversial history of species delimitation for the genus Batrachuperus, we provisionally treated all Qinling Mountain samples  explore the phylogeographical pattern of B. tibetanus in the Qinling Mountains to test north-south and west-east distribution break hypotheses, (ii) examine the driving forces that generated the phylogeographical structure, and (iii) infer demographic history and assess the effect of glacial climate on the distribution of B. tibetanus.Previously, the stream salamanders distributed in the Qinling Mountains were described as a new species Cyt b gene sequences used in our analysis was 814 bp located 14, 258–15, 071 of the Genbank sequence NC_00808536, with 111 (13.6%) nucleotide sites being polymorphic in the total data, of which 105 were parsimony-informative. No indels were observed. Among the 281 sequences in B. tibetanus, there were 37 haplotypes with their frequencies ranging from 0.4% (one sequence) to 32.7% (92 sequences). Eleven haplotypes were unique, 14 were shared among local populations. The most abundant haplotype (92 sequences) was shared by nine local populations.The length of the mitochondrial 37, the divergence time of the two lineages was about 3.5 million years ago (Ma) , as dated using BEAST 1.8.038. We did not detect significant levels of gene flow with Nem being 0.302 and 0.365, or less than one migrant per generation, for bidirectional migration between the two lineages using the coalescence approach as implemented in Migrate 3.5.139. The two lineages were distributed in the eastern and western Qinling Mountains, respectively, and co-occurred in four populations, i.e. DP, HSP, ZH and NSG  were grouped with the Tibetan lineage of B. tibetanus .All phylogenetic analyses revealed almost identical tree topologies. Thus, we only show the maximum-likelihood (ML) tree with supported values Fig. . All haph = 0.861) and nucleotide diversity (π = 0.0242) were high, indicating high genetic diversity of B. tibetanus in the Qinling Mountains. The genetic diversity of the four populations possessing haplotypes from both the eastern and western lineages was generally larger than the other populations . The western group consisted of the population 1–6, the eastern group contained the population 8–20, and the third group only contained the QLC population  between genetic distance and geographical distance , estimates of both haplotype diversity .The coalescence-based Bayesian skyline plot (BSP) provided additional details on demographic changes through time. The western and eastern Qinling lineages of ory Fig. . AssuminB. tibetanus with the average AUC (the area under the curve) for the twenty replicate runs being 0.934, indicating a good model performance. The predicted current suitable area was markedly similar to the currently known distribution of B. tibetanus  predicted accurately the distribution area of nus Fig. . The mosB. tibetanus, i.e. the eastern edge of the Tibetan Plateau, in our ENM analyses, but also tested the differences in habitat suitability between the Qinling and Tibetan lineages as well as the eastern and western Qinling lineages using ENMTools40. The identity test indicated that the predicted habitat suitability of the Tibetan and Qinling lineages of B. tibetanus exhibited statistically significant ecological differences (P < 0.01). The observed values for I (0.62) and D (0.32) were significantly lower than those generated from replicates. However, there was not an environmental transition between the distribution ranges of the Tibetan and Qinling lineages revealed by the range-break test (P < 0.68). For the western and eastern lineages in the Qinling Mountains, the differences between the habitat suitability were not significant (P = 0.07) with the observed values for I and D being 0.59 and 0.31, respectively.We not only included the distribution area of the Tibetan lineage of Cytb lineages determined by phylogenetic methods and the other populations  between different categories using 13 variable features is illustrated in Table B. tibetanus in the Qinling Mountains. The two major lineages were distributed in the eastern and western Qinling Mountains, respectively, and co-occurring in the middle of the Qinling Mountains  and therefore would contribute to north-south phylogeographical structure, which we did not observe. Instead, rivers do not appear to have acted as barriers to gene flow among the Qinling lineages of B. tibetanus, which is consistent with the previous result that divergence of Batrachuperus species was not correlated with river drainage system42.Thus, the hypothesis of the drainage system’s influence on genetic patterns of B. tibetanus. Note that there were some lineages grouped with the Qinling lineages  together contributed to the deep split between the Tibet and Qinling lineages of B. tibetanus, probably occurring during the late Miocene. In contrast, orogenesis of the Qinling Mountains played a key role on the divergence of the two Qinling lineages of B. tibetanus, considering statistically non-significant ecological differences between the habitat suitability of the two Qinling lineages (P = 0.07) and the large suitable area since the LGM. It probably occurred during the Pliocene at 3.5 Ma, which corresponded to the orogenic period of the Qinling Mountains during the late Cenozoic. As barriers to gene flow, the Taibai Mountain (3767 m), the highest peak of the Qinling Mountains, might have contributed to the split between the two Qinling lineages.Given that the main phylogeographical patterns are along the west-east axis, we speculate that historical isolation due to orogenesis of the Qinling Mountains during the late Cenozoic might have caused the genetic divergence between the two Qinling lineages of 29 and animals21, indicating the prevalent trend of west-east and/or west-central-east breaks in this region instead of a north-south break. Different factors appeared to play different roles on driving genetic differentiation of different species living in this region, resulting in distinct genetic differentiation patterns. For example, glacial refugia and local adaptation after dispersal probably generated a deep split in the Chinese endemic freshwater crab Sinopotamon acutum in the middle of the Qinling Mountains without overlap area21, whereas multiple lineages distributed from west to east with extremely limited overlap area detected in the frog Feirana taihangnica, perhaps resulted from tectonic changes and Pleistocene climatic fluctuations20. Our study suggests that the Qinling lineages of B. tibetanus possibly resulted from orogenesis of the Qinling Mountains and were affected at different levels by Pleistocene climatic oscillations.Similar west-east and/or west-central-east breaks in the Qinling Mountains have already been commonly reported in plantsB. tibetanus exhibited surprisingly obvious signals of demographic expansion detected by various approaches  occurring in 9 of the 13 eastern localities and its star-like topology in the network. It suggested that the Pleistocene climatic changes might have had more impact on the demographic changes of the eastern Qinling lineage. In contrast, the western Qinling lineage experienced a long period of constant population size (0.25 Ma–0.05 Ma) followed by a recent expansion (about 50 kyr) during the last glacial epoch, indicating that the western Qinling lineage was not severely suppressed by the LGM (~21 ka). Considering restricted distribution of most haplotypes, the expansion of the two Qinling lineages probably resulted in the secondary contact in four localities with high genetic diversity, i.e. DP, HSP, ZH and NSG 44, considering the geographic conditions in and around the distribution areas of the Qinling lineages of B. tibetanus. First, the presence of the Tibetan lineage of B. tibetanus in the northwestern Qinling Mountains revealed in this study indicate the possible dispersal from the Tibet Plateau to the Qinling Mountains. Second, the recent rapid uplift of the Tibet Plateau potentially contributed to the expansion of B. tibetanus from the Tibet Plateau to the Qinling Mountains. The recent rapid uplift of the Tibet Plateau (~10–8 Ma) is broadly consistent with the divergence of the QLC and the other Qinling populations (95% HPD: 6.5–15.0 Ma). Dispersal from the Qinling Mountains to the Tibet Plateau was not supported in our study, such as the ENM analyses. The B. tibetanus distributed in the eastern edge of the Tibetan Plateau might be severely suppressed at the LGM  survived through the past great mass extinctions, many species are currently at risk globally due to various factors such as rapid ecological and climatic changes50. Habitat loss, fragmentation and over-hunting might cause reductions in population size of B. tibetanus, and then decrease genetic diversity within and among populations51. In this circumstance, it is important to assess genetic diversity of B. tibetanus for designing conservation strategies. B. tibetanus in the Qinling Mountains has maintained a high level of total genetic diversity with h and π being 0.861 and 0.0242, respectively, and exhibited surprisingly obvious signals of recent demographic expansion  in future conservation strategies. Our intraspecific units identified here do not meet Moritz’s strict criteria for ESU, which require both significant divergence at nuclear loci and reciprocal monophyly of mtDNA52. Given that the allozyme data seem to lack sufficient variation to identify the lineages corresponding to mtDNA units25, additional research employing polymorphic nuclear DNA markers, such as non-coding nuclear sequences53, may clarify it. However, the two genetic units of B. tibetanus are supported by our morphological data and meet Fraser and Bernatchez’s criterion of a lineage demonstrating highly restricted gene flow from other such lineages within the higher organizational levels (lineages) of the species54. The three lineages in the Qinling Mountains generally have low genetic diversity and thus deserve more surveillance for protection, especially for the QLC population and the eastern lineage (Table Nipponia nippon), a number of nature reserves  have been established in the eastern Qinling Mountains during the past fifty years. Tree cutting and hunting are prohibited in these areas, and the habitat of B. tibetanus in the nature reserves is generally in a favourable condition. Thus we should pay more attention to habitat across the large areas outside of the nature reserves by comprehensively assessing the conservation status of habitat patches and removing anthropogenic pressures. The areas in the middle of the Qinling Mountains where the two lineages co-occur also warrant protection to increase genetic variation and to maintain adaptation and evolutionary process55.The past and current connectivity between populations of 56. All experimental procedures and animal collection were conducted under the permits (No. IOZ14001) approved by the Committee for Animal Experiments of the Institute of Zoology, Chinese Academy of Sciences, China.The methods were performed in accordance with the guidelines of the American Society of Ichthyologists and HerpetologistsB. tibetanus were collected at 20 localities of Shaanxi province across its main distribution range in the Qinling Mountains between 2008 and 2010  gene was amplified using designed primers (pn1F: 5′-ATTCGAAAAACTCACCCATTA-3′ and pn1R: 5′-AATGTTAAGCTGCGTTGTT-3′) based on the complete mitochondrial genome of B. tibetanus (Genbank sequence NC_008085). Amplifications were performed in 30 μl reactions containing 15 ul Taq Polymerase Enzymes mixture , 0.3 μM of each primer, and 100 ng of the template DNA. PCR involved 5 minutes at 94 °C, then 35 cycles of 94 °C for 30 s, 50 °C for 30 s and 72 °C for 45 s, and finally an extension at 72 °C for 10 minutes. The reaction mixture was amplified using an MBS Satellite thermal cycler . The amplified DNA products were purified, and automated DNA sequencing was performed on an ABI3730 with an ABI PRISM BigDye terminator Cycle Sequencing Ready Reaction Kit (Perkin Elmer Biosystems). All individuals were sequenced from both strands. Sequence data were carefully inspected by eye using BioEdit 7.1.3.058, and sequences immediately next to the sequencing primer were excluded.After measurements of morphological variables, the tail of each salamander individual was removed and stored in 95% ethanol for DNA analysis. Genomic DNA was isolated from muscle tissues of the tail using standard phenol-chloroform procedures59. The best-fit model of nucleotide substitution for Cytb fragment of B. tibetanus was TPM1uf + G. We used PhyML 3.060 to perform ML analyses. The pruning and regrafting (SPR) option was used to estimate better ML tree topology. The non-parametric bootstrap with 1000 replicates was used to estimate the support for each internal branch of the ML phylogeny. We used the program MrBayes 3.2.161 to perform Bayesian phylogenetic inference. Markov chains were run for 107 generations with two independent runs including one cold and three heated chains. We examined two convergence diagnostics, i.e. the average standard deviation of split frequencies and the potential scale reduction factor (PSRF). As runs converged, the average standard deviation of split frequencies should be lower than 0.01 and PSRF should approach 1.0. Trees were sampled every 1000 generations, and the initial 25% of trees were discarded as burn-in. The remaining trees (15002) were used to estimate the majority-rule consensus tree and the Bayesian posterior probabilities (BPP). We performed three replicate analyses. The Qinling lineages were previously described as B. taibaiensis35. Thus, haplotypes from QLC population, which were grouped with the Tibetan lineage of B. tibetanus  and Bayesian inference (BI) methods. The best-fitting substitution model was determined under the Bayesian information criteria (BIC) using jModelTest 2.1.1Cytb lineages was estimated by a mean substitution rate method in BEAST38. An uncorrelated lognormal clock model was used, with a mean value of 0.0062 substitutions per site per million years based on the evolutionary rates of Cytb estimated in salamanders37. We used a coalescent tree prior modelling constant population size through time that was appropriate for sequences sampled from the same population and/or species38. Markov chains were run for 109 generations with a sampling interval of 105 generations, and the first 10% of the trees were discarded as burn-in. Convergence of the parameters sampled was checked using Tracer 1.662.The divergence time between the 5 recorded steps, a sampling interval of 100 and a burn-in of 108 steps. Static heating scheme was used with four chains and temperatures that are . Runs were repeated three times to examine consistency of estimates, and convergence was also checked using effective sample size (ESS). The effective number of immigrants per generation (Nem) of the most likely migration model was calculated by estimated mutation-scaled population sizes (θ) and immigration rates (M), Nemj→i = θi × Mj→i.Levels of gene flow between the cytb lineages were estimated by the coalescence approach in Migrate. The Bayesian search strategy comprised one long chain with 10h) and nucleotide diversity (π) using DnaSP 5.10.0163. Pairwise sequence differences among the haplotypes were calculated using Arlequin 3.5.1.264. The exact test of population differentiation was performed using Arlequin. Isolation by distance (IBD) was examined by testing the relationship between pairwise population genetic distances and geographical distances using Mantel test in Arlequin. Genetic distances between populations used in the Mantel test were calculated by MEGA 5.265. To explore general pattern of variation, a median-joining network of haplotypes was constructed using NETWORK 4.6.1.066.Genetic diversity within populations was estimated by haplotype  due to differences between population groups. For each user-defined number of groups (K), FCT was estimated and evaluated to select the optimal number of genetic groups. The number of initial conditions was set to 100 with K = 2–15. Statistical significance was tested using 1000 random permutations of the data.We used SAMOVA 2.0Cytb lineages was investigated by summary statistics Tajima’s D68 and Fu’s Fs69 using DnaSP. Significantly negative values of Tajima’s D and Fu’s Fs are evidence for an excess of rare variations potentially due to population growth. We performed the mismatch distribution analysis to detect recent population expansion by comparing the distribution of the number of pairwise differences between haplotypes and their theoretical distribution expected under a model of sudden (stepwise) demographic expansion. The SSD and raggedness index70 were used to test goodness of fit. We also used a coalescent-based method in LAMARC 2.1.871 to estimate the exponential growth rate (g) for each Cytb lineage and total samples. The Bayesian search strategy comprised 10 short chains of 5000 steps and two long chains of 200,000 steps, and a sampling interval of 20. Runs were repeated ten times to examine consistency of estimates. Finally, we estimated past population dynamics using coalescence-based Bayesian skyline plots72, as implemented in BEAST. The best-fit model with an uncorrelated lognormal clock was used. Markov chains were run for 108 generations with a sampling interval of 104 generations, and the first 10% of the trees were discarded as burn-in. The Tracer was used to summarize the results and check convergence of the Markov chain.Historical demography of the B. tibetanus and to infer its potential distribution during the Quaternary (21 kya) using climate data and known sampling localities of this species. We used two models for the LGM (21 kya): the Community Climate System Model (CCSM) and the Model for Interdisciplinary Research on Climate (MIROC), originally developed from the Paleoclimate Modelling Intercomparison Project Phase II (PMIP2). Nineteen bioclimatic variables were downloaded from the WordClim website (www.worldclim.org) at 2.5 arc-min (~4 km) resolution. After downloading, we defined a study area spanned from 29.671 N to 36.536 N and from 99.420 E to 114.030 E, a larger spatial range than the current distribution range of B. tibetanus. Note that the distribution area of the Tibetan lineage of B. tibetanus, distributed in the eastern edge of the Tibetan Plateau, was included in our ENM analyses. We performed a correlation analysis between the nineteen climatic variables with ArcGIS 9.3 (ESRI) in the defined area, and then selected eleven uncorrelated variables (r < 0.85): bio1-Annual Mean Temperature, bio6-Min Temperature of Coldest Month, bio8-Mean Temperature of Wettest Quarter, bio9-Mean Temperature of Driest Quarter, bio10-Mean Temperature of Warmest Quarter, bio11-Mean Temperature of Coldest Quarter, bio12-Annual Precipitation, bio13-Precipitation of Wettest Month, bio14-Precipitation of Driest Month, bio17-Precipitation of Driest Quarter, bio19-Precipitation of Coldest Quarter. Species occurrence data consisted of 62 sampling localities, 32 of which were described25. The ENM analyses were performed using the maximum entropy algorithm in Maxent 3.3.373 due to its appropriateness for presence-only data and good performance74. Maxent was run for twenty replicates with default parameters except for using 25% of occurrence data to test the model. We used the area under the curve (AUC) of the receiver operating characteristic (ROC) plot to evaluate model performance.We performed ecological niche modelling (ENM) to evaluate the present suitable area of 75. The I statistic and Schoener’s D were used to measure overlap of predicted habitat suitability of the lineages. Both I and D ranged from 0 (completely discordant niches) to 1 . Statistical significance was tested using 100 replicates simulated in ENMTools.We used ENMTools 1.4.3 to perform the identity test and range-break test for testing the differences between the Qinling and Tibetan lineages as well as the Qinling lineages. The identity test is used to ask whether the predicted habitat suitability for the lineages is more different than expected if they are generated at random from a pooled data set. The range-break test used the same pooled data set to ask whether geographic boundary between the lineages is associated with an environmental transitionSAMOVA, respectively.The following fourteen morphological variables were examined on 120 collected specimens  with vernier calipers to the nearest 0.1 mm: body mass, snout-vent length, tail length, total length, head length, head width, snout length, trunk length, interocular space, eye diameter, tail height, forelimb length, hind limb length, axilla-groin length. Measurements were taken from adults, as determined by the body size and weight. These morphological variables, with snout-vent length being a covariate variable to avoid the impact of body size, were analysed using analysis of covariance by SPSS 13.0. This method examined whether means of a variable are equal across different groups taking into account variability of other variables. Our analysis of covariance considered two categorical variables, i.e. population group and sex, and one covariate (snout-vent length). Here, we considered the differences between the two population groups determined by phylogenetic methods and We also used a multivariate technique, i.e. factor analysis, to describe variability among the fourteen morphological variables. It was used to visualize the distance matrix generated from morphological data. We used principal-component analysis to compute a distance matrix, and varimax rotation to minimize the complexity of the components.Cyt b) gene of the stream salamanders in the Qinling Mountains are available in the Genbank (The accession numbers: KX548391-KX548427).The sequences of cytochrome b (Supplementary Info