Heteropsis oculus, a high elevation shola-grassland specialist restricted to the southern Western Ghats, and Mycalesis patnia, found more continuously distributed in lower elevations. In all analyses, as per expectation the sky island specialist H. oculus exhibited a greater degree of population genetic structure than M. patnia, implying a difference in geneflow. This difference in geneflow in turn appears to be due to the natural fragmentation of the sky island complexes. Detailed analysis of a subset of H. oculus samples from one sky island complex  showed a surprising genetic break. A possible reason for this break could be unsuitable conditions of higher temperature and lower rainfall in the intervening valley region. Thus, sky island species are not only restricted by lack of habitat continuity between montane areas, but also by the nature of the intervening habitat.High elevation montane areas are called “sky islands” when they occur as a series of high mountains separated by lowland valleys. Different climatic conditions at high elevations makes sky islands a specialized type of habitat, rendering them naturally fragmented compared to more continuous habitat at lower elevations. Species in sky islands face unsuitable climate in the intervening valleys when moving from one montane area to another. The high elevation shola-grassland mosaic in the Western Ghats of southern India form one such sky island complex. The fragmented patches make this area ideal to study the effect of the spatial orientation of suitable habitat patches on population genetic structure of species found in these areas. Past studies have suggested that sky islands tend to have genetically structured populations, possibly due to reduced gene flow between montane areas. To test this hypothesis, we adopted the comparative approach. Using Amplified Fragment Length Polymorphisms, we compared population genetic structures of two closely related, similar sized butterfly species:  One of the most extreme examples is that of genetic diversification over a small spatial scale in the jumping spider The high elevation areas of the Western Ghats mountain range in southern India form one such sky island group. The Western Ghats (WG) is a 1600 km long mountain chain, which extends from north to south along the west coast of peninsular India. The mountain chain is broken by only one large gap: the 40 km long Palghat Gap. The southern Western Ghats are on an average much higher than the northern Western Ghats, with Anaimudi in south Kerala being the highest peak, with an elevation of 2295 m. These high elevation montane regions have an altitude of over 1900 m and are characterized by a special type of vegetation - the shola-grassland complex. The sholas are stunted forests with an upper story of trees, a twisted second story and a dense shrub layer of saplings; they occupy ridges between mountaintops. The shola forests are surrounded by undulating grasslands, consisting of fire and frost-resistant species of grasses Brachypteryx major), a bird endemic to the shola forests of the Western Ghats, showed maximal genetic differentiation across the widest valley in the Western Ghats - the 40 km wide Palghat Gap The sky islands of the Western Ghats exhibit a high degree of endemism, with fifty endemic plant genera, half of which are monotypic, and with almost 50% of India’s 206 amphibian species endemic to this region These studies suggest that species confined to sky islands tend to have structured populations, ostensibly due to reduced gene flow across the sky islands. However, most of these studies have looked at a single sky island species, and more importantly, have not compared it with non-sky island species. Comparing species which inhabit the naturally disjunct sky island habitat, with similar species that inhabit the more continuously distributed low and mid elevation areas, can offer some insights into whether sky island species are capable of maintaining connectivity between different populations.Parnassius smintheusErebia melampusButterflies in the Western Ghats make an interesting system to address such questions, because the composition of the butterfly community changes drastically between the mid-elevation and montane areas. Genetic structure as a result of habitat specialization has been shown in butterflies earlier, especially in the case of montane species, like in the high altitude meadow butterflies Heteropsis oculus is an endemic species found only to the south of the Palghat Gap in the Western Ghats, and restricted to montane areas above 1200 m. The closely related Mycalesis patnia is a generalist woodland species that occupies lower and mid elevation areas. The two species are similar with respect to all traits that affect dispersal in butterflies, except for the kind of habitats they occupy In this study, we looked at the population genetic structure of two closely related butterfly species from peninsular India, both from the subtribe Mycalesina . Heteropsis oculus will have more geographically structured populations, because of the spatial orientation of montane forests (disjunct habitat) along the Western Ghats. Mycalesis patnia, being more continuously distributed in the lower elevations, will have a more homogenous population structure. Such a result will provide greater support to the hypothesis that sky island species tend to have structured populations due to reduced gene flow across suitable habitat patches. We sampled both species along the Western Ghats, and also sampled Heteropsis oculus intensively across one mountain range, the Anamalais, to enumerate gene flow between sky island populations separated by short distances.In this study, we predict that the sky island specialist M. patnia and H. oculus belong to subtribe Mycalesina, which is part of subfamily Satyrinae and Family Nymphalidae. The subfamily Satyrinae in peninsular India has about 20 species in the low and mid elevation areas, which are almost completely replaced by just two species in the higher elevation areas Heteropsis oculus (henceforth HO) to the south of the Palghat Gap, and Heteropsis adolphei to the north of the Palghat Gap. Both Heteropsis species are endemic to the sky islands to the north and south of the Palghat Gap respectively Mycalesis patnia (henceforth MP) is a generalist woodland species endemic to the Western Ghats and Sri Lanka that occupies evergreen, deciduous and scrub forests in the lower and mid elevation areas. HO belonged to the genus Mycalesis until recently, when a molecular phylogenetic study placed it in Heteropsis, another genus in the same subtribe Both Both study species were collected from across their range in the Western Ghats: MP from northern Karnataka to south Kerala, and HO from the south of the Palghat Gap in Kerala and Tamil Nadu. We conducted active searches and also set up traps using fermented bait made from a mixture of over-ripe bananas, sugarcane juice and rum. For intensive sampling of HO, three hill complexes that are high enough for shola forests south of the Palghat Gap were demarcated, using an elevation map of the Western Ghats. These included the Anamalai-Palni complex (ANA), the Meghamalai-High Wavies complex (MEGH) and the Agastyamalai complex (AGA)  panel C.MP was sampled from the low elevation areas corresponding to the above shola complexes see  panel B.c oxidase subunit I - COI, and control region). All these markers did not show any intraspecific variation within the specimens we had from the Western Ghats. So, we decided to use the Amplified Fragment Length Polymorphisms (AFLPs) technique instead. The AFLP protocol is known to be sensitive to contamination, especially from microbial DNA, which is abundant in the digestive system of the insect et alWe first tried out sequencing of mitochondrial DNA markers . The restriction-ligation reaction was carried out at 37 degrees for 4 hours. The products were diluted with 90 µl Tris-EDTA before the next step. The pre-selective PCR used the EcoRI primer E/A (5′-GACTGCGTACCAA TTCA-3′) and the MseI primer M/C (5′GATGAGTCCTGAGTAAC-3′), with the PCR amplification parameters as follows: 72°C for 2 min, 30 cycles of denaturing at 94°C for 30 sec, annealing at 56°C for 30 sec, extension at 72°C for 2 min, and final elongation at 60°C for 10 min.The restriction and ligation reactions were accomplished in a single step. The total DNA was digested with 1 unit of MseI (New England Biolabs) and 5 units of EcoRI (New England Biolabs), along with the adaptors. The MseI adaptors were 5′-GAC GAT GAG TCC TGA G-3′ (forward) and 5′-TAC TCA GGA CTC AT-3′ (reverse). The EcoRI adaptors were 5′-CTC GTA GAC TGC GTA CC-3′ (forward) and The product of the pre-selective PCR was run on a 2% agarose gel to check for amplification, indicated by a smear in the 100 to 1000 bp range. Successful samples were diluted with 100 µl using Tris-EDTA, and used in the selective amplification. AmpliTaq Gold (Applied Biosystems) was used during the selective PCR to minimize amplification error. The PCR parameters were: 94°C for 2 min, and 36 cycles of denaturing at 94°C for 30 sec, annealing for 30 sec and extension at 72°C for 2 min. Annealing was initiated at 65°C and then reduced by 0.7°C per cycle for the next 12 cycles, and maintained at 56°C for the next 23 cycles.Four selective primer pairs were chosen, after testing over 20 combinations of primer pairs. Selective primers with both 2 and 3 extra nucleotides than the preselective primers  and 12 µl of Formamide. The plate was centrifuged to mix the contents, and then the DNA denatured by heating at 95°C for 3 min, followed by a quick chill on ice. The Applied Biosystems Standard Dye Set D was used to detect peaks. The electropherograms were visualized, and edited where necessary, using Peak Scanner (Applied Biosystems). The sizing table, containing information on the intensity and size of the peaks, was obtained from Peak Scanner, and imported into RawGeno In order to minimize error, the same person (SS) did all the lab work, from extraction to loading the samples into the sequencer. All the samples could not be worked on at the same time, because the field work was done in batches. To ensure that between run variability did not affect results, positive and negative controls were run and error rates checked at the start of each batch of runs. When needed, all the electropherograms from one primer pair were normalized before analyses using the R package AFLPScore M.patnia (n  = 57), and the HO dataset, with all the individuals of H.oculus (n  = 99). Additionally, since we sampled the Anamalais region intensively for HO, we performed all the analyses for a reduced dataset of HO, which included only individuals collected from the Anamalais  while performing the clustering of genotypes Two permutation tests were used to test for positive and negative spatial autocorrelation: the Gtest , and Ltest . The PCA was performed in the package ade4 version 1.4 n = 58), Agastyamalai  and Meghamalai . The HO-ANA dataset clustered into seven groups (see panel A of n = 9), Mannavan shola , Akkamalai , Rajmala , Vaguvaraiyar shola , Mathikettan shola  and Kodaikanal . The MP dataset had five groups (see panel A of n = 15), samples from Meghamalais and Periyar , samples from Agastyamalais , samples from northern Karnataka  and samples from Wayanad and Coorg .In order to carry out the population-based analyses, we grouped samples from each dataset into populations by putting individuals from the same area together. For deciding the cutoff for placing individuals to a group, we used the first quartile from a distribution of geographic distances between sampling coordinates. This gave rise to three groups in the HO dataset , the chance of correct allocation to the second population is high. In some cases, the software cannot place an individual into any of the populations with high confidence; in such cases, the individual is considered an immigrant from outside the sampled metapopulations.Assignment tests were carried out in AFLPOP r = 0.004, P = NS; HO first distance class, 0–50 km, r = 0.003, P = 0.003) while the HO dataset did, though of very low magnitude. The third distance class (100–150 km) was significant in the HO dataset, but the r was low (0.008). However, the spatial autocorrelation correlograms of MP and HO did not differ significantly  = 0.253, P = NS; Omega = 11.08, P = NS). In the HO-ANA dataset, the first four distance classes do not show significant spatial autocorrelation. However, the fifth and sixth distance classes (above 40 km) showed significant negative spatial autocorrelation. The complete results of the spatial autocorrelation analysis are given in The MP dataset did not show significant spatial autocorrelation in the first distance class . The graphs for the Mantel test are presented in r = 0.218, P = 0.0005), with an elevated r value at a Euclidean distance of 0.3 − 0.4.Both the MP and HO datasets exhibited significant IBD; however, the correlation value for HO was more than twice that of MP (MP Mantel I = 0.655) was retained. There were no significant clusters retrieved in this analysis  = 0.044, P = NS).Based on an examination of the screeplot of sPCA values of the MP dataset see , part A,ysis see , and botI = 0.868)  = 0.017, P = 0.189). However, the significant global structure did not translate into any geographic structuring  was retained, since it was far higher than all the others  = 0.030, P = 0.498). In For HO-ANA, the first sPCA eigenvalue  was similarly uniform, ranging from 0.15 to 0.17; the total heterozygosity was 0.162. In HO, the PLP was about 42% in the ANA and MEGH populations, but as high as 51.6% in the AGA population. The total heterozygosity was 0.115, with eHranging from 0.105 to 0.12. There was higher variation in genetic diversity among sub populations in the HO-ANA dataset: the PLP varied from 38.5% in AKK, to about 71% in MATH. The total heterozygosity was 0.167, with eHvarying from 0.14 to 0.19.The genetic diversity parameters for all the datasets are summarized in STF of 0.0217, P<0.0001 .STF value was 0.002, at P<0.0001; see STF between KODI and the other sub populations is the major contributor to the overall STF value. STF is 0.034 between KODI and MATH, and KODI and VAG, while the STF among other sub-populations is 0. Similar patterns can be seen with Nei’s D  and ban. The remaining five individuals were assigned with high probability to populations they were not sampled from: two from ANA were assigned to MEGH, two from WAC to MEGH and one from MEGH to NKAR.Of the 99 individuals in the HO dataset, 16 could not be assigned to any one population with confidence. 70 samples were assigned to the population from which they were sampled. However, simulations showed that the remaining 13 individuals had the highest probability of being assigned to the population they were sampled from.In the HO-ANA subset, 9 out of the 58 individuals could not be assigned to one population with confidence, and only 15 of the remaining 49 individuals were correctly assigned: 9 to KODI, and 6 to MATH. But, simulations showed that all the individuals except one were assigned with high probability to the population they were sampled from. Only one individual from AKK was assigned to MATH with high confidence.eH values from this study are comparable to the values obtained in other studies that have used AFLP In this study, we compare the population genetic structure of two butterfly species that occupy habitats with different levels of continuity. Among these species, HO is a sky-island specialist distributed in naturally disjunct habitat, and MP is distributed in relatively more continuous lowland forests. The two species are similar in all other traits that affect dispersal ability; thus a difference in genetic structure can be attributed to a difference in habitat continuity. We first established that the overall genetic diversity in both species was not significantly different. The two AFLP datasets can thus be compared meaningfully. Importantly, the Spatial autocorrelation was not observed in MP, while HO exhibits significant spatial autocorrelation, even though the correlation value is very low. The clustering analysis sPCA did not retrieve clusters in either MP or HO. However, the sPCA analysis of HO showed a positive global structure (significant G test), indicating significant positive spatial autocorrelation, as opposed to the lack of global structures in MP. Genetic differentiation was not significant in MP, and significant, though low, between the three populations of HO. The same pattern was observed in the assignment tests, with the algorithm unable to confidently assign individuals to the correct populations in MP, because of a homogenous genetic structure. There were, however, a high percentage of correct assignments in HO, showing more restricted dispersal. Taken together, these results indicate that HO, the sky island species, showed a higher population genetic structure than MP, the mid and low elevation species. A summary of the analyses is given in The difference between the genetic structure of MP and HO can be attributed to the spatial orientation of the habitats they occupy, because the two species are similar in all other respects. HO, the sky island specialist inhabiting a naturally disjunct habitat exhibits more geographic structuring than MP, which inhabits the more continuously distributed low and mid elevation forests in the Western Ghats. Thus our results support the hypothesis that sky islands tend to have structured populations due to reduced gene flow across the sky islands.Erebia melampusErebia EuryaleParnassius smintheus from the Canadian rockies Similar results of reduced gene flow among sky islands have been observed in the montane butterflies, Chazara briseisMelanargia galatheaAs mentioned above, MP seems to posses a uniform genetic structure across the Western Ghats. More intense sampling may show different patterns; but, MP has been sampled across most of its range in the Western Ghats, and the genetic diversity values are comparable to global values. This indicates that sampling has not been a problem. Such a lack of genetic structure has been observed in other butterfly species, especially among Satyrines: examples are Parnassius apolloAlso, some butterfly species can have an innate ability to disperse over long distances, depending on the spatial distribution of resources necessary for their survival: sites where males and females can find each other and mate, for oviposition where larval food plants are proximately distributed, and where adults can find food and survive to be able to perform both these activities STF measures and Nei’s D) in the HO-ANA dataset is low, but the overall values are contributed by the differentiation between KODI and the other sub-populations. Even in assignment tests, only one individual was assigned to a population from which it was not sampled.Within HO, an interesting pattern was revealed. In the HO-ANA dataset, KODI samples formed a distinct cluster in the PCA plot when the first and third axes were used. Also, KODI samples formed a distinct cluster in the sPCA analyses, indicating differentiation between KODI and all other sub-populations  are closely related to the individuals from Munnar, and well differentiated from the Kodaikanal samples. It is possible that similar forces are at play here. Anthopogenic habitat fragmentation is probably causing songs to diverge because populations are getting isolated (though with no corresponding genetic differentiation yet) in the white-bellied shortwing, and genetic differentiation in H.oculus.The presence of such genetic structuring over a short distance of about 40–50 km is further evidence of the reduced connectivity between sky islands, which is limited in comparison to connectivity between lower elevations. In the white-bellied shortwing, a bird species also found in the sky islands of the Western Ghats, a study of song structure The reasons for a break in gene flow between Kodaikanal and Munnar can only be speculated upon. The following information was obtained from the high resolution vegetation map The main difference is the amount and seasonality of rainfall in both places, which manifests as a strong west-east gradient in the number of dry months, from Munnar to Kodaikanal. Munnar experiences the Allepey-Mangalore rainfall regime, characterized by heavy monsoon showers in June, July and August, with 2000 to 5000 mm rainfall annually, (mean of 3594 mm), spread over 144 rainy days, and an average dry season length of 3 months per year. As one moves east to Kodaikanal, there is a succession of different rainfall regimes: 1) a strip of the Shimoga regime , and 2) the Madurai-Pollachi regime , until Kodaikanal, which is a special case of the Madurai-Pollachi regime due to increased rainfall over a few days . This probably means that HO, being adapted to the high rainfall and low temperature in Kodaikanal, is unable to disperse to Munnar due to the intervening dry area.This brings to light an important fact: apart from the spatial orientation of suitable habitat patches, the nature of the intervening habitat is equally important in determining whether dispersal (and thus gene flow) can occur in a particular species. Replicating studies of this kind with other taxa across the Munnar – Kodaikanal gradient, and in other areas of the Western Ghats that show such a strong gradient, like the Nilgiris, will help further our understanding of habitat connectivity between sky islands. This assumes further importance given the high degree of endemism in the sky islands of the Western Ghats, especially in the case of plants. While there may be a difference between species based on species biology, comparative studies such as these lay the ground for making generalizations regarding the ability of a species to maintain genetically viable populations.There is now information regarding two species that inhabit the sky islands of the Western Ghats: an endemic bird, and an endemic butterfly. Both studies show that gene flow is restricted at these high elevations. The high elevation areas of the Western Ghats have been systematically converted into plantations from British times: tea plantations in Munnar started in the 1870s, and the replacement of grasslands with timber trees  in Kodaikanal started in the early 1900s. The montane shola forests and grasslands have been swamped with invasive exotic species that have changed the composition of native vegetation Figure S1Mantel test for a) HO-FULL and b) HO-ANA showing variation in r in different distance classes.(PDF)Click here for additional data file.Figure S2Eigenvalues and screeplots for the sPCA analyses.(PDF)Click here for additional data file.Table S1Sampling locations for both species.(PDF)Click here for additional data file.Table S2Full results of the spatial autocorrelation analysis.(PDF)Click here for additional data file.Table S3Band-based STF values between populations in all datasets.(PDF)Click here for additional data file.


Ceracris kiangsu, were examined with 16S rDNA and amplified fragment length polymorphisms (AFLPs). In this study, no conspicuous phylogeographical structure was discovered from either Maximum parsimony (MP) and Neighbor-joining (NJ) phylogenetic analyses. The effect of geographical isolation was not conspicuous on a large spatial scale.At smaller spatial scales local diversity of some populations within mountainous areas were detected using Nei's genetic distance and AMOVA. There is a high level of genetic diversity and a low genetic differentiation among populations in the C. kiangsu of South and Southeast China. Our analyses indicate that C. kiangsu is a monophyletic group. Our results also support the hypothesis that the C. kiangsu population is in a primary differentiation stage. Given the mismatch distribution, it is likely that a population expansion in C. kiangsu occurred about 0.242 Ma during the Quaternary interglaciation. Based on historical reports, we conjecture that human activities had significant impacts on the C. kiangsu gene flow.Geographic distance and geographical barriers likely play a considerable role in structuring genetic variation in species, although some migratory species may have less phylogeographic structure on a smaller spatial scale. Here, genetic diversity and the phylogenetic structure among geographical populations of the yellow-spined bamboo locust,  Highly migratory species are usually expected to have minimal population substructure over their distributional ranges because strong gene flow can counteract the isolating effects of geographical distance and physical barriers Locusta migratoria, an infamous pest insect with exceptional migratory ability, and discovered its minimal population substructure. However, most other grasshoppers do not have excellent ability of flying to undergo such rapid climatic change. For instance, limitations due to resources like food may have prevented large-scale colonization by insects Oxya hyla intricate was separated into three deep monophyletic clades with no shared haplotype in a study by Li et al. O. hyla intricate populations, and that past geological events and climatic fluctuations are the most important factor in shaping the population genetic diversity and structure of the species.The Quaternary glaciation period played an important role in shaping the history of global fauna and flora. In the past few decades, glacial cycles have been considered one of the most important factors in shifting population genetic structure and promoting floral and faunal diversification Ceracris kiangsu Chai, is one of the most severe bamboo pests endemic to China L. migratoriaO. hyla intricate C. kiangsuThe yellow-spined bamboo locust, C. kiangsu and infer demographic processes. AFLPs have been shown to provide phylogenetic resolution among recently and rapidly radiating groups in which sequence data have failed Heliconius species based on AFLPs revealed pronounced genetic structure in both H. erato and H. melpomeneover at small spatial scales C. kiangsu.Here, we use Amplified fragment length polymorphisms (AFLPs) and 16S rDNA datasets to obtain more information about the population histories of C. kiangsu, how long has geographical distance influenced the gene flow between different local populations? (2) Does geographical isolation affect the genetic structure of C. kiangsu in modern times? (3) If this species experienced a genetic bottleneck and/or a population explosion, did Pleistocene climate cycles play a significant role in shaping the history of C. kiangsu, similar to O. hyla intricata or other organisms? Additionally, we also estimate the minimum age of this bamboo locust based on pairwise mtDNA sequence divergence. Our results illuminate the population structure in the bamboo locust C. kiangsu and provide essential insights for future work focused on the forest grasshopper's response to climate changes.In this study, we compare the resolution of both marker types and address the following questions: (1) In the context of the unregularly phylogeographic structure of This species of grasshopper in this study is a famous agricultural pest in China, need to control. Collections of samples were permitted by the authority of each forestry center . For collection locations no specific permits were required for the described field studies because sample collection did not involve endangered or protected plant species or privately-owned locations.C. kiangsu were collected from 24 locations in the field covering nearly all of the species' distribution range between 2007 and 2011 . Furthermore, there is a special bamboo species, Bambusa textiles McClure, in Guangning County, while the species in all of the other locations is the bamboo Phyllostachys heterocycla (Carr.) and/or others. Two individuals of the green-spined bamboo locust C. nigricornis collected in Shuangpai County were used as outgroups. All samples were stored in 100% ethanol upon capture.A total of 393 individuals of and 2011 ; Table 1Genomic DNA was extracted from femur samples using Wizard® Genomic DNA Purification Kit  following the manufacturer instructions, and stored at −30°C until needed. All DNA extracts for AFLP were run on 1% agarose gels, and samples that did not have high concentrations of high molecular weight DNA or that appeared excessively sheared were not included in AFLP analysis 5′- CCGGTCTGAACTCAGATCACGT-3′) and LR-N-13398 (5′-CGCCTGTTT AACAAAAACAT-3′). PCR reactions were carried out in 50 µL volumes which included 1 µL template DNA , 5 µL 10×buffer, 3 µL MgCl2, 4 µL dNTPs, 1 µL of each primer and 0.25 µL rTaq . PCR cycling conditions included an initial 5 min at 94°C, 30 cycles of 95°C for 30 sec, 56°C for 30 sec, 72°C for 1 min,plus a final extension at 72°C for 10 min.A 483 bp segment of the 16S rRNA gene was amplified in a subset of 393 individuals with primers given in Liu & Jiang (2004): LR-J-12887 . Alignments are available on request. To confirm the identity of the mtDNA sequences, the amino acid sequences were inferred using GeneDoc 2.6.02 based on the invertebrate mitochondrial code.2, 1.6 µL dNTPs, 0.4 µL rTaq (TAKARA) and 1 µL EocRI+N primer and 1 µL MseI+N primer, up to 30 µL with ddH2O. The thermal cycling parameters for preselective amplification were 2 min at 94°C, 30 cycles of 30 sec at 94°C, 1 min at 56°C, 1 min at 72°C, followed by 10 min at 72°C. The ligations were diluted 1∶20 and 2 µL of the diluted preselective amplification product was used in the selective amplification. Selective amplification was conducted in a total volume of 20 µL with 2 µL diluted preselective amplification product, 2 µL 10× buffer, 1.6 µL MgCl2, 1.6 µL dNTPs, 0.6 µL rTaq (TAKARA) and 1 µL EocRI+3 primer (labeled with FAM) and 1 µL MseI primer, up to 20 µL with ddH2O. Four primer combinations  were used in this step. Selective amplification products were visually measured on an ABI 3700 DNA analyzer .We applied the original AFLP protocol of Vos et al. (1995) with a few modifications Fragment data were analyzed with GeneMarker version 2.20 (Demo). We scored fragments of size 50–500 bp as present or absent. Minimum fragment signal intensity was initially used for all fragments. The signal intensity was measured as relative fluorescent units (RFU) of 500 or 1000 depending on the primer set The mitochondrial DNA sequence data were assembled and corrected in SeqMan II version 5.08 . We then carried out alignments in MEGA 5 d) and the number of variable sites were analyzed in DnaSP v5.10 ST and the p value in the AMOVA function of ARLEQUIN v3.11 The number of haplotypes (h) as well as haplotype diversity , by the Median Joining method ST (Pairwise genetic distance) and p value  with 1000 bootstrapping replicates were produced using AMOVA analysis in ARLEQUIN. And we also run a genetic structure test with the same groups we shown in 16S rRNA.Fragmentized information was exported as 0/1 popmatrix by GeneMarker and transformed in format in the AFLPDAT program Using AFLP-SURV C. kiangsu. POPGENE v1.31 The percentage of polymorphic loci (P), observed number of alleles (Na), effective number of alleles (Ne), gene diversity (He) K subgroups that had distinctive allele frequencies without a priori population information, and a K index was set from 2 to 16. The output, Pr (X|K), was used as an indication of the number of groups To further investigate population structure, the assignment test and population structure examination were conducted with Bayesian assignment analysis implemented by the program STRUCTURE v2.3 Hd is only 0.001. Most individuals assembled into two haplotypes (Hap2 and Hap5), and the most common haplotype (Hap2) has 288 individuals, equal to 73.28% of all the samples. For all individuals, the average number of polymorphic sites (S) and haplotype diversity (Pi) were 122 and 0.06, respectively , and variance of ectively . In geogectively . And theectively .C. kiangsui geographical groups is 0.140 in AMOVA (p = 0.000)  is in the Taojiang group (0.157)  . And negions see . In the  (0.157) . The tesThe median-joining network  displaysThe Neighbor-Joining tree appears to have an unclear topological structure . Two indIn the MP tree , with thNa/Ne) in each population is above 1.0 (I) were from 0.179 (Guangning) to 0.019 (Nanjing)  are all 0, and the respective p values are all high (p>0.5), except Huarong – Menglun (p = 0.188)  however Nanjign has the least polymorphic loci (11) . Observebove 1.0 . Nei's gbove 1.0 . The higbove 1.0 . ShannonNanjing) .In the p188) see .C. nigricornis, the outgroup, are not separated from C. kiangsu individuals but instead share the same branch with Guangde  and the mitochondrial gene (16S). Furthermore, the variation tendency in both AMOVA and mismatch analysis were consistent with each other. The phylogenetic analysis highly supported monophyly of C. kiangsui . However, when using AFLP and 16S as markers, there is no clear phylogeographic structure in either the neighbor-joining or the maximum parsimony tree. Instead, some populations from distant geographic areas appeared on the same branch. Despite the possibility of some basic structure in the NJ and MP trees, there is currently little support for the branches in either tree. The results in our study, taken together, support the hypothesis that the C. kiangsu population is in a primary differentiation stage.Our study, despite some contradictions between AFLP and mitochondrial DNA, reveals that there is a high level of genetic diversity and a low genetic distance among the individuals in the 16S mtDNA from 5 populations of Rammeacris kiangsu Tsai (i.e. C. kiangsu). Four of their sampling locations were the same as ours, with the exception of Yongchang, which is not far from Jinyun Mountain. Their findings support our conclusion that no apparent population differentiations exist among these five geographical populations. Their NJ tree was constructed using 5 populations and O. chinensis as outgroup. Only the populations in Changning and Taojiang had some divergence from each other C. kiangsu.Jiang et al. (2011) amplified 506 bp of C. kiangsu, high levels of gene flow among populations and orderless phylogeographic relationship are perhaps convincing C. kiangsu from east to southeast of China. Most of our samples were assembled and clustered into one big clade. Weak differentiation signs can be found in the whole C. kiangsu population. Besides, the result of STRUCTURE , effective number of alleles (Ne), Nei's gene diversity (H) and Shannon's Information index (I). All of these index values were second only to those of the Mengla group. In addition, in this study, only one location (Guangning) has the bamboo species B. textilis, it is hard to explain the complicated genetic relationship within the Guangning population. In the light of the high migration ability of C. kiangsu, a difference in host plants is perhaps not one of the factors generating hereditary difference. However, in the purpose of further clarifying the problem, high density sample data aimed at Guangning and typical locations of other host plants is specially needed in the future.Some parasite species may have host-based genetic structure, like C. kiangsu individuals from these places had experience a recent selective pressures resulting from human activities and conduced genetic variation in population.Some insecticide treatments may lead to nichetargeting selected and modified the genetic structure of injurious insect Heliconius butterflies in Brazil's Atlantic Forest Palingenia longicauda, and decrease genetic diversity Tadarida brasiliensis mexicana) P. pubescebns, had been transplanted from southern China to northern. For example, Henan province import first batch of P. pubescebns from Guangxi province in 1966, and from 1968 to 1976, 34 cities of Henan province set up hundreds of small nurseries, and cultivated 16.3 hm2 of bamboo plants 2. Then, about 10000 bamboo individuals in Heze county were transplanted into Beijing, Taiyuan, Lanzhou, Wuhan (one of our sampling sites), and Chengdu cities as greening plants 2 transplanted bamboo C. kiangsu spawn into root soil of bamboo and bamboo species introduction and transplantation technical requirements, so large amounts of transplanting may spread the eggs of C. kiangsu from one geographical population to others. In these locations, it is hard to prevent extraneous haplotypes from being introduced. In consideration of the graph shown in 16S results , and 203 individuals were examined using AFLPs. Our results indicate that there is a high level of genetic diversity and a low genetic distance among the C. kiangsu populations. Although the broad geographic range in this study covers a large part of the habitat of C. kiangsu, our study did not reveals a clear geography-related population structure in C. kiangsu.Generally, geographic distance and geographical barriers probably play a considerable role in structuring genetic variation within species, although some migratory species may have less phylogeographic structure on smaller spatial scales C. kiangsu should be considered a monophyletic group. All our results supported the hypothesis that C. kiangsu populations are in a primary divergent stage. There are several potential reasons for this result. The most likely factor is that there is little geographical isolation along most parts of our sampling range. Additionally, human activity, host plant selection and sexuality relativity factors also potentially affect the species' phylogeographic structure. More research is required to determine the strength of these three factors.According to our analyses, C. kiangsu, and our mismatch analysis indicated that the population explosion likely occurred about 0.242 Ma. The Quaternary glaciation events may have been responsible for this population explosion. According to the phylogenetic trees and haplotype distribution, Mengla of Yunnan province, Changning of Sichuan province and Guangning of Guangdong province are possible refugia of C. kiangsu. Furthermore, those populations colonizationed in Mengla may have been separated from the other two refugia after the Quaternary glaciation. Because of the subsequent lack of physical barriers in East and South China C. kiangsu. And in our study, we first discovered human activity may have a significant impact on C. kiangsu population structure, which may be the most fundamental reason of current geographical population pattern. Our future work may focus on finding ancestor of different geographical populations.The Tajima's D and Fu's Fs values identified in the 16S rRNA, which were unexpectedly below zero, reveal that there was a population explosion during the species history of Figure S1C. kiangsu.NJ phylogenetic tree based on 16S rRNA gene sequences of 25 geographic populations of (TIF)Click here for additional data file.Table S1STF values  and p values  based on mtDNA data.Computing conventional F-Statistics from haplotype frequencies, population pairwise (DOCX)Click here for additional data file.Table S2STF values  and p value  based on AFLP data calculate from Arlequin software.Population pairwise (DOCX)Click here for additional data file.Table S3Nei's genetic distance after Lynch & Milligan method calculate from AFLPsurv software.(DOCX)Click here for additional data file.


Biologists studying adaptation under sexual selection have spent considerable effort assessing the relative importance of two groups of models, which hinge on the idea that females gain indirect benefits via mate discrimination. These are the good genes and genetic compatibility models. Quantitative genetic studies have advanced our understanding of these models by enabling assessment of whether the genetic architectures underlying focal phenotypes are congruent with either model. In this context, good genes models require underlying additive genetic variance, while compatibility models require non-additive variance. Currently, we know very little about how the expression of genotypes comprised of distinct parental haplotypes, or how levels and types of genetic variance underlying key phenotypes, change across environments. Such knowledge is important, however, because genotype-environment interactions can have major implications on the potential for evolutionary responses to selection.full diallel breeding design to screen for complex genotype-environment interactions, and genetic architectures underlying key morphological traits, across two thermal environments  in the Australian field cricket, Teleogryllus oceanicus. In males, complex three-way interactions between sire and dam parental haplotypes and the rearing environment accounted for up to 23 per cent of the scaled phenotypic variance in the traits we measured , and each trait harboured significant additive genetic variance in the standard temperature (27°C) only. In females, these three-way interactions were less important, with interactions between the paternal haplotype and rearing environment accounting for about ten per cent of the phenotypic variance . Of the female traits measured, only ovary mass for crickets reared at the cooler temperature (23°C), exhibited significant levels of additive genetic variance.We used a Our results show that the genetics underlying phenotypic expression can be complex, context-dependent and different in each of the sexes. We discuss the implications of these results, particularly in terms of the evolutionary processes that hinge on good and compatible genes models. This tibility -12. In stibility ,7. Thus,tibility ,9.The contribution and relevance of good versus compatible genes in determining offspring genetic quality has been ardently debated for over a decade, but remains unclear -12. ThisIn 2005, Neff and Pitcher outlined a quantitative genetic framework that enables a simultaneous assessment of the potential for good and compatible genes processes to operate within a given population. They pointed out , reinforSeveral studies have now applied this quantitative genetic framework to assessing the potential for good and compatible genetic models simultaneously -28. ThesIt is well known that the prevailing environment has a pervasive influence on the link between the genotype and the phenotype. This has been reinforced repeatedly across taxa and trait types , via studies showing that trait values associated with particular genes or genotypes frequently vary across environments ,29-32. TTeleogryllus oceanicus). We take a quantitative genetic approach, applying an incomplete full diallel breeding design to eight inbred lines, generating 38 outbred F1 offspring genotypes consisting of various reciprocal combinations of parental haplotypes. F1 offspring of each genotype were then reared at two different temperatures until adulthood, when measures of body mass and size and gonad mass were obtained. This approach enables us to assess the reaction norms of each genotype across environments, examining whether the effect of the paternal haplotype, maternal haplotype, or the interaction between parental haplotypes, on each trait changes across environments. The design also enables us to partition the genetic variance underlying each trait into additive and non-additive contributions , and to examine the magnitude of any maternal and paternal effects across environments. We discuss the results in light of their potential to impact on good or compatible gene processes that might be operating within the studied population.In this study we explore GEIs, and changes in genetic architecture across environments, in the expression of some classic fitness-related morphological traits in male and female Australian field crickets  after five generations of such inbreeding is 0.672. All inbred lines were reared across two separate 5 L containers for most of their development. At their penultimate moult into adulthood, they were sorted by sex (one container per sex).The crickets used in the experiment were the immediate descendents of a sample (n > 100) of wild type adults collected from a banana plantation in Carnarvon, north-west Western Australia in 2006. The founder population was maintained in the laboratory at 27°C on a 12 h light: 12 h dark photoperiod in multiple replicate 10 L plastic containers, with Inbreeding apparently affected productivity, with each line producing an average of only 14 pairs of adult offspring following five generations of inbreeding. This number was only sufficient to sustain an incomplete 8 × 8 full diallel reciprocal crossing scheme, performed in duplicate (the two weakest lines had to be discarded). Thus, for each of the remaining eight lines, a virgin adult dam was mated once to a virgin sire from one of the other seven lines, in all possible dam × sire line combinations. When possible (depending on available numbers of crickets), each line combination was replicated. We omitted inbred combinations from the crossing scheme - that is, we did not cross females from a given inbred line to males from the same line. After mating, each female was placed in a plastic container (16 × 12 × 5 cm) for two weeks (or until death), which contained food and a moist cotton pad for oviposition (replaced every 7 days).ad libitum access to food and water. To mitigate potential density-dependent effects, we added two egg cartons to each container, and capped the maximum density of crickets at 30 per container. Nymphs were then exposed to one of two temperature treatments. Half of the nymphs per replicate line combination were placed at 27°C (standard rearing conditions for our laboratory culture) and the other half at 23°C. These temperature treatments fall well within the range of temperatures that T. oceanicus crickets experience within their native Australian distribution [The resultant nymphs of each replicate per line combination were distributed in equal densities across separate 5 L containers with ribution .Gryllus firmus (15 of 42 cells lost). Missing cells might affect the variance component estimates through a general loss of statistical power, or if the missing cells were distributed throughout the diallel in a non-random way. However, unless the missing cells consistently involved lines with intermediate breeding values (an unlikely scenario since it is likely that the weaker line combinations will have been the ones that failed to produce F1 offspring), then any bias in the genetic variance estimates will be in a downward direction, and our estimates can therefore be considered to be conservative [We lost a number of cells from the diallel crossing scheme due to reproductive failure and mortality of the inbred parents involved in the crosses. This resulted in some crosses in the diallel not being represented at all, and others being represented by only one of the two replicates Figure . Roff anervative ,45.ad libitum access to food and water. Focal individuals spent nine to 13 days in these containers, after which point they were frozen at - 20°C. Each focal daughter was provided with a male from the stock population with which to mate freely over six hours, and then frozen. We then measured a number of fitness-related morphological traits in up to 10 individuals of each sex per line combination and replicate , with requency . Further ability  and is u ability . While lceanicus , studiesceanicus ,51. Fina females , but exh females .1 offspring, and 2) the underlying genetic architecture of these traits when reared in the different thermal environments.We took a two-step approach to partitioning the phenotypic variance of each trait, allowing us to examine 1) complex GEIs in the phenotypic expression of each trait in the F1,1042 = 11.92 p = 0.0006; pronotum width F1,1043 = 358.91 p = < 0.0001, Table D. melanogaster indicate that the genetic architecture of each of these traits differs across the sexes. These findings reinforce our decision to analyze pronotum width and body mass separately by sex in this study.In all analyses, we tested male and female data separately, even for traits that are shared across sexes (i.e. body mass and pronotum width). This is because these traits are sexually dimorphic , for each focal trait. This was done using Restricted Maximum Likelihood Analysis (REML) in the MIXED procedure in SAS . Sire and Dam effects were treated as random effects in the model, with individual line combination replicates nested within Sire × Dam combinations. The thermal treatment was treated as a fixed effect, and all interactions as random effects.Bio model described by Cockerham and Weir [To discern the underlying genetic architecture of each trait at each thermal treatment, we applied the and Weir  and Lyncand Weir  to the dijkl Yis the trait of the l'th offspring from the k'th replicate of the cross between sire i and dam j, and μ = the trait mean of the population. i Nand j Nare the additive effects of the nuclear genes contributed by i and j, independent of sex; ij Tis the interaction of the haploid nuclear contributions; Mj is the maternal genetic and environmental effects of line j when used as dams; Pi is the paternal genetic and environmental effects of line i when used as sires; Kij is the interaction between maternal and paternal effects; Rk(ij) is the effect of k'th replicate cross within the dam line × sire line combination and Wl(k(ij)) is the unique effect of individual l within a replicate cross [where te cross ,23,59. T2n: nuclear additive variance = 1/2 FVA + 1/4 F2VAA, where VA is the additive genetic variance, and VAA the additive-by-additive epistatic variance, and higher order epistasis is ignored for simplicity [AA is small, and VA can then be estimated as 2σ2n /F. Consistent with good genes models.1) σmplicity . Thus, t2t: nuclear interaction variance = 1/2 F2VAA + F2VD + F3VAD + F4VDD, where VAD and VDD are the additive-by-dominance and dominance- by-dominance epistatic variances. Thus, the term includes epistatic and dominance variation. Again, if we make the assumption that the epistatic terms are small, then we can estimate VD as σ2t/F2. Consistent with compatible genes models.2) σ2m: maternal effect variance VM, including both maternal genotype and environment effects, and possible interactions between maternal nuclear and maternal extra-nuclear effects.3) σ2p: paternal effect variance VP, including both paternal genotype and environment effects, and possible interactions between paternal nuclear and paternal extra-nuclear effects. Significant paternal effect variance might in theory be consistent with good genes models under the assumption that the paternal effects are genetic in origin.4) σ2k: non-reciprocal interaction variance, VK, of paternal and maternal effects, and of nuclear and extra-nuclear effects. Consistent with compatible genes models under the assumption that the non-reciprocal interaction variance is genetic in origin.5) σ2rep : variance among replicate crosses within line combinations.6) σ2w: variance among individuals within replicate crosses.7) σA = 100(√VA)/trait mean [Coefficients of genetic variation (CV) for each variance component estimate were calculated by scaling the causal variance components by the trait mean; e.g. CVait mean .All traits exhibited normal distributions of raw data and residuals, with few if any outlying datapoints.1 offspring was typically determined by complex interactions involving each parental haplotype and the environment in which these haplotypic combinations were expressed. A further analysis of Sire and Dam effects within each of the two thermal environments shows that Sire × Dam interactions abound in each environment, for most of the examined traits  were affected by a Sire × Dam × Treatment effect, explaining between 16 and 23 per cent of the phenotypic variance in those traits , were influenced by Sire × Treatment interactions that explained seven to 12 per cent of the phenotypic variation in those traits  underlying all of the male phenotypes (Table 2k) in the standard, but not cooler thermal treatment (Table The es Table  when reaes Table . In contes Table . Only mant Table  and 4. W2t) in the high temperature treatment. If we assume no epistasis, then we can estimate the coefficient of dominance variance for this trait at 9.2 (Table 2p), with a related CV of 1.9  displayed a significant additive genetic variance component (CV = 23.5: Table Complex GEIs (haplotype × haplotype × environment) existed for all three of the male traits that we measured. In contrast, female phenotypes were in part shaped by interactions involving only the sire haplotype and environment. Furthermore, the relative contributions of additive and non-additive genetic variance underlying these same traits commonly changed across environments. We suggest that these results are likely to have implications on our understanding of several evolutionary concepts.1trait expression that were general across environments. Likewise, in no case did we find additive main effects of the maternal or paternal haplotype on F1 trait expression that were general across environments.Firstly, our results indicate that trait expression in male and female offspring is influenced by different levels of genetic complexity. In males, all traits were generally shaped by the specific combination of haplotypes that the offspring inherit from their parents in interaction with the environment; whereas in females, all traits were influenced by the sire effect only in interaction with the environment. Notably, across both sexes, the genetic effects were completely contingent on the environment in which the offspring were reared in. That is, in no case did we find Sire × Dam effects on FThe general lack of main effects of the parental haplotype on offspring phenotypes, and the prevalence of paternal haplotype × environment interactions for female traits, and the more complex paternal haplotype × maternal haplotype × environment interactions for male traits, adds a previously underappreciated level of complexity to our understanding of evolutionary dynamics within populations. The fact that no particular paternal haplotype resulted in greater phenotypic expression across all maternal haplotypes and environments is consistent with a resolution to the Lek Paradox  based on GEIs -68, as wHaplotype × haplotype × environment interactions are arguably more consistent with genetic compatibility models of quality, and it is worth asking whether such interactions might promote the evolution of mechanisms that allow females to discriminate between males on the basis of their genetic compatibility. Genetic compatibility models have risen to prominence in recent times ,7-10, wiT. oceanicus [T. oceanicus breeds year round [The thermal treatments that we used fall within the thermal range of the native distribution of ceanicus , as wellar round ,73, it igood and compatibility genetic models to phenotypic expression, particularly given the paucity of information that currently exists as to the relevance of genetic compatibility models on adult trait expression . Models of good genes and genetic compatibility are almost always posed in the context of sexual selection, typically addressing the question of whether females might acquire good or compatible genes through mate choice. Therefore, it is worth asking whether the set of morphological traits that we measured might be used in mate choice or male-male competition for matings. Body and pronotum size are clearly traits whose expression might be readily assessed by the opposite sex, and as previously mentioned, studies in the closely related species T. commodus show that male body size is indeed under sexual selection [T. Oceanicus [T. oceanicus , thereby providing females with a mechanism by which to choose males on the basis of large ejaculate investment. Moreover, molecules produced by the testes clearly have important downstream effects on female reproductive biology in Teleogryllus. In T. Commodus, the testes generate an enzyme complex, Prostaglandin synthetase, that contributes to the production of the chemical messenger Prostaglandin, which is transferred to the females in the seminal fluid [Although the traits that we assessed in this study were all morphological, the available evidence suggests that each is under selection and closely tied to fitness in males and females (see Methods). In this regard, these traits therefore provided a good opportunity to assess the relevance of genetic models, such as the election ,48. On tceanicus . Body anceanicus , thus moceanicus ,52. On tceanicus ,51, and al fluid . These pal fluid ,77, as wal fluid , and posWhen it came to assessing the genetic architectures of the traits at hand, we generally found additive genetic variance for each male trait in the lab standard thermal environment (27°C), but not in the cooler environment (23°C). However, in females, we generally detected no such additive variance, with the exception of ovary mass at 23°C. This result is generally encouraging for good genes models based on mate choice, because it suggests that male candidate traits that are under sexual selection also exhibited an underlying genetic architecture consisting of standing additive variance. The disclaimer is that this genetic additively was only detected at 27°C, meaning that females might only draw benefits of discriminative mate choice if they can control or predict the environments in which their offspring are raised.T. oceanicus. While Simmons's results for pronotum width were consistent with our results in males and females [As for testes and ovary mass were different in magnitude to those measured in the current study. Specifically, at similar temperatures to that of the high temperature treatment in this study, Simmons found lower levels of additive variance for testis mass (CVA = 7.18 compared to 14.23). In contrast, he did find higher additive variance for ovary mass than we did in our study (32.05 vs. 10.06). These discrepancies are not surprising, and can be reconciled by considering that the two studies were separated in time by about a decade, and each study exhibited differences in their respective technical designs .Previously, Simmons (2003) used a paternal half-sibling analysis to measure the coefficients of additive genetic variance in male testes and pronotum width, and female ovary mass and female pronotum width in  females , the meaA for ovary mass at 23°C. Although 27°C represented the standard rearing condition for crickets in our study, the crickets had only recently been sourced from the field population where they breed year round [T. oceanicus breeds all year round in the field, it is clear that neither of the treatments is novel to the crickets, although it is likely that the cooler temperature was more stressful given that peak cricket abundances in the field occur during the warmer seasons [As mentioned above, almost all of the detectable significant genetic variance for the morphological traits was found in the 27°C treatment, and we detected only CVar round , and hadar round -39, usua seasons . Finally2t, an estimate of the reciprocal nuclear interaction variance (dominance or epistatic genetic variance), and σ2k, an estimate of complex non-reciprocal non-additive variance . Breaking down the non-additive variance components into these two estimates provided us with a more detailed picture of the genetic architecture of the traits at hand. The consequence of doing this, however, is that it decreases the power of finding significant non-additive variance components , because it uses information from both sires and dams to calculate the additive variance [Biomodels. This indicates that additive variance is indeed present, but is swamped by more complex Sire × Dam × Treatment interactions in the GEI analyses.The presence of haplotype × haplotype × environment interactions, and haplotype × haplotype interactions within each environment (see test statistics in Figure variance ,26-28. Tvariance . AccordiT. oceanicus, and used these to generate 36 focal genotypes. Although these 36 genotypes represent a random sample of the total genetic variation segregating within the T. oceanicus population in question, it is important to realize that these genotypes nonetheless constitute only a tiny fraction of the total pool of possible genotypes within the population. This has implications. First, it is entirely possible that the parental genotypes that acted additively in our set of diallel lines, may not act additively in the wild population when matched against the complete pool of possible genotypes. Similarly, genotypes acting non-additively in our sample of genotypes, might exhibit additivity among the total pool of genotypes [Our study offers valuable insights into the likely complexity of gene by environment interactions in natural populations, and the evolutionary implications of these interactions. To generate these insights, we originally captured eight random parental genotypes from a wild population of T. oceanicus, and this result suggests that genetic compatibility models might be relevant to overall genetic quality. However, our quantitative genetic Biomodels also show that there is some additive genetic variance underlying key male traits that are likely shaped by sexual selection. Thus, the combined results suggest that there is at least the potential, genetically, for females to utilize a good and/or a compatible genes process when choosing mates to procure genetic benefits for the offspring, based on these morphological traits, at least at the standard rearing temperature. Whether females actually exhibit such mating preferences for the traits measured here, requires experimental testing. For example, despite the existence of the non-additive genetic variance required for compatibility models to operate, questions must remain about the significance of mate choice based on compatibility in driving trait evolution, at least in the context of sexually dimorphic morphologies, such as body and pronotum size. This is because mate choice for compatibility will exert balancing selection on these traits, whereas sexual dimorphism would seem most likely to evolve under sex-specific directional selection. Finally, we note that the relevance of our findings to natural populations of crickets will also hinge on the effectiveness by which crickets, when developing in their natural habitat, can mitigate the effects of environmental fluctuations of the magnitude encountered in our study via microhabitat selection.In sum, we have demonstrated that complex GEIs make a significant contribution to offspring phenotype expression in MN, DKD and LWS designed the experiment, MN and DKD conducted the lab work. MN measured morphologies, MN conducted statistical analyses. MN, DKD, and LWS wrote the manuscript. All authors read and approved the final manuscript.


Arctotheca populifolia and Petrorhagia nanteuilii. Using microsatellite data, we identified the source for each introduction, estimated genetic diversity in native and introduced populations, and calculated the amount of diversity retained in introduced populations. These values were compared to those from a literature review of diversity in native, confamilial populations and to estimates of genetic diversity retained at introduction. Gene diversity in the native range of both species was significantly lower than for confamilials. We found that, on average, introduced populations showing evidence of adaptation to their new environments retained 81% of the genetic diversity from the native range. Introduced populations of P. nanteuilii had higher genetic diversity than found in the native source populations, whereas introduced populations of A. populifolia retained only 14% of its native diversity in one introduction and 1% in another. Our literature review has shown that most introductions demonstrating adaptive ability have lost diversity upon introduction. The two species studied here had exceptionally low native range genetic diversity. Further, the two introductions of A. populifolia represent the largest percentage loss of genetic diversity in a species showing evidence of substantial morphological change in the introduced range. While high genetic diversity may increase the likelihood of invasion success, the species examined here adapted to their new environments with very little neutral genetic diversity. This finding suggests that even introductions founded by small numbers of individuals have the potential to become invasive.Some introduced populations thrive and evolve despite the presumed loss of diversity at introduction. We aimed to quantify the amount of genetic diversity retained at introduction in species that have shown evidence of adaptation to their introduced environments. Samples were taken from native and introduced ranges of  Biological invasions present one of the greatest environmental challenges of our time, yet the drivers of successful invasion remain poorly understood. The concept that genetic diversity in the founding population is positively related to the probability of invasion success is one of the oldest hypotheses in invasion biology  for the introductions for both species. This information is important for the accurate comparison of the genetic characteristics of the introduced populations from the actual source populations in their native ranges. Second, we characterized genetic diversity in the native and introduced ranges of both species. Finally, we surveyed the literature to determine (1) whether the levels of genetic diversity we found in the native range of both species were typical of other species within those families and (2) whether our species retained similar levels of genetic diversity at introduction compared with other introduced species showing evidence of rapid evolution in their introduced environments. We expected that genetic diversity in the species studied here would not be low relative to their families because they had demonstrated the ability to undergo morphological change in their introduced environments. We also expected the change in diversity between the native and introduced populations in our study species to be similar to that of other introduced species showing evidence of rapid evolution.We aimed to select species that had shown potential for rapid evolution through postintroduction morphological change. We chose species with restricted native and introduced ranges so that we could comprehensively sample across their distributions. Annual or short-lived perennial species with sexual reproduction were selected, because these species have had more generations since introduction, increasing the opportunity for evolution to occur in the introduced range. We avoided selecting crop and pasture species that were likely to have been introduced many times.Arctotheca populifolia . This was determined using herbarium specimens following methods described by Buswell et al.  using GS-500 (Liz) in each capillary as a size standard. Allele sizes were estimated on GeneMapper, version 3.7 (Applied Biosystems).Microsatellites were developed using next-generation sequencing on the GS-FLX 454 platform  following methods described by Abdelkrim et al. . QDD v 0rlequin, version 3.5.1.2  for each value of K between one and ten. We ran ten replicates for each value of K, each run having a burn-in period of 100,000 Markov chain Monte Carlo steps followed by 106 iterations. The most likely number of genetic groups was inferred using Evanno et al.'s  conducted in GenAlEx v. 6.3 , unity , and two . To calculate NA, R, and HE for each sample, we used FSTAT, version 2.9.3.2 .Many authors have stressed that a spectrum of diversity measures gives the best summary of diversity Pielou . Therefo2 Goudet , 2002, aU-tests to compare within-population diversity levels between the samples identified as sources for Australian introductions of both species because these data could not be made normal by transformation. Three approaches were used to assess diversity between populations. Pairwise FST values were calculated in Arlequin for comparison with other studies that quote this measure. Pairwise values for Shannon's mutual information index (SHUA) were calculated in GenAlEx. Compared with FST, mutual information is known to be more robust to a wide range of population sizes and dispersal rates , which avoids some serious problems that occur with other between-population measures , which gives an estimate of diversity retained after introduction, assuming no changes in diversity have occurred in the introduced range. For this calculation, we only used estimates of HE generated from microsatellite data because the absolute values of diversity estimates differ according to the marker used, and we wanted to directly compare these results to those generated in the current study.We surveyed the literature regarding Petrorhagia nanteuilii in the introduced range showed a significant increase in log10 height through time that was not driven by region sampled  significantly deviated from Hardy–Weinberg equilibrium and were excluded from downstream analyses. The remaining ten loci showed no significant departures from equilibrium. Petrorhagia nanteuilii has previously been reported to be tetraploid . The second group contained native samples from the eastern edge of the range to Kei Mouth and also included samples from Western Australia . Two genetic groups were identified in P. nanteuilii: One group consisted of most sampling localities in Spain and France  and a second group  contained samples from two localities in Spain , Corsica, Sardinia, and Australia. The samples from Corsica, Sardinia, and Australia had membership proportions for group B2 in excess of 0.97, whereas those from Spain were lower .The Sups Fig. . One grotructure results. Arctotheca populifolia samples from group A1 , while in the introduction to Western Australia, HE was not different between native and introduced samples . Diversity was low within the second introduction: We found a single genotype across all seven loci in one A. populifolia sample from the northeastern extreme of the native range  and three samples from Australia . Assuming a single introduction of P. nanteuilii to Australia, the estimated HE in the native samples was not different to that of introduced samples . Values of R were similarly low in both species .In the introduction to eastern Australia, native samples of HE Table  than didHE in 28 Asteraceae species from 28 different genera ranging from 0.22 to 0.88  and both were significantly lower than the mean of these values for each family .We found microsatellite estimates of HE). In these studies, the ratio of diversity in the introduced range to the diversity in the native range was an average of 0.81 . However, RHE for A. populifolia was much lower than estimates found in the literature search . In fact, both introductions of A. populifolia had the lowest ratios of any example we found.We found 19 examples in the literature of species that had demonstrated evolutionary change in their introduced environment and where genetic diversity had been estimated in both the native and introduced range. Eight of these studies used allozymes, half of which found higher genetic diversity in the native range Table . Of the Genetic diversity has been demonstrated to be positively correlated with invasion success  harbored very low genetic diversity at Amplified Fragment Length Polymorphism markers despite displaying significantly different phenotypes in a common garden setting . This suggests that neutral genetic diversity is not important to adaptive potential in introduced species.The review we have conducted specifically examines loss of genetic diversity at introduction in species where some evidence of adaptive change has been documented in the introduced environment. It would be useful to compare the associated change in genetic diversity in this group with that of a group of species which has been introduced but has shown no evidence of adaptation to novel environments; we might anticipate that the latter would show more loss if diversity is important to adaptive potential. Unfortunately, there is a bias in reporting which makes this difficult. However, we can compare the results of our review (19% loss of GD in the introduced range) with that of Dlugosch and Parker , who fouThe ability of populations with low current “neutral” diversity to evolve could be due to (1) retention of greater adaptive than neutral genetic variation due to either chance or balancing selection on adaptive variation (Reed and Frankham Passer domesticus) and speculated that epigenetic variation may provide a mechanism for adaptation over the short time scales relevant to invasions.Recent research suggests that epigenetic modifications (DNA methylation) may also play an important role in invasion success. Using the invasive Japanese knotwood populations discussed above, Richards et al.  demonstrA. populifolia. Identifying the source of an invasion assures that observed differences between introduced and native populations are not the result of diversity within the native range and prevents actual differences from becoming obscured  and the Subtropical Seashore Vegetation (Group A2) described by Mucina and Rutherford . Variation was even lower in the introduced range of A. populifolia than the already low variation in the native range, suggestive of a small number of founders.Low genetic diversity in introduced populations can reflect a genetically impoverished source . However, because the ability to evolve in response to a novel environment may depend on the level of adaptive variation present, the relevance of neutral markers variation has been questioned (Reed and Frankham QST) and microsatellite variation (FST), quantitative variation is usually higher  speStebbins , and iiiStebbins .Considerable effort has been invested in identifying drivers of invasion success, including the importance of genetic diversity to invasiveness. While genetic diversity may be related to invasion success in some species (Crawford and Whitney


Schizolobium parahyba(Fabaceae), which includes two varieties with a disjunct distribution, from Southern Brazil to Central America. Neotropical rain forests, focus on four largest wet forests: Atlantic forest, Amazonian forests, Andean forest and Central America forest. The genetic diversity and differentiation of populations among S. parahyba populations using sequences of three cpDNA regions  and one nrDNA region (ITS) were analyzed. The presence of the significant phylogeographic structure was inferred by testing if GST and NST were significantly different and a spatial analysis of molecular variance was made with both markers.Using cpDNA (matK) sequences of the S. parahyba and other Fabaceae species and fossils, we estimated de divergent time for Schizolobium clade and using the average ITS substitution rate reported for a range of woody plants, w estimated the divergence time between the two varieties. The high levels of genetic diversity in some populations of S. parahyba and two centres of genetic diversity that correlate with the two known varieties: one in the southeast Atlantic forest, and the other in the Amazonian basin. In contrast, the populations from Northeast Atlantic forest and Andean-Central America forests showed low level of genetic diversity and divergent haplotypes, probably because the founder effect after dispersion.The results suggest dispersion from southeast Atlantic forest to Amazonian, Andean and Central America forests. We verifya high level of genetic structure, with 68% (nrDNA) and 82% (cpDNA) of the total genetic diversity due to differences among populations. Twenty-one haplotypes were found with cpDNA and four with nrDNA and no haplotypes were shared between varieties.The age for Schizolobiumclade using matK sequences was estimated ranging from 8.4-23.0 My and the divergence between two varieties using ITS sequence variation was of the 6.5 My. In conclusion, the variation pattern of cpDNA  and nrDNA  markers provides different insights into the phylogeographic structure and gene flow in S. parahyba. This comparative analysis of cpDNA and nrDNA markerscan help a deeper understanding of the dynamics responsible for both ancient and more recent events that have shaped the current distribution of genetic variability in Neotropical plants. Theresults are relevant to conservation efforts and ongoing work on the genetics of population divergence and speciation in these Neotropical rainforests. Also, for the long-term conservation of the genetic diversity of S. parahyba, including the divergent lineages of the two varieties, it would be important to design strategies that aim to preserve most of its lineages.This work aims to analyze the phylogeography of


Reticulitermes chinensis Snyder is an important pest of trees and buildings in China. Here, we characterized genetic structure and reproductive modes of R. chinensis from China for the first time. A total of 1,875 workers from 75 collection sites in Huanggang, Changsha and Chongqing cities were genotyped at eight microsatellite loci. Analysis of genetic clusters showed two subpopulations in Chongqing city. The Huanggang population showed a uniform genetic pattern and was separated from the other populations by the largest genetic distances (FST: 0.17–0.20). In contrast, smaller genetic distances (FST: 0.05–0.12) separated Changsha, Chongqing-1 and Chongqing-2 populations. Chongqing-1 was the only population showing a genetic bottleneck. Isolation by distance among colonies in the Huanggang population indicated limited alate dispersal or colony budding. Lack of isolation by distance among colonies within the populations of Changsha, Chongqing-1 and Chongqing-2, suggested long-range dispersal by alates and/or human-mediated transport. Overall, extended family colonies (73.91%) were predominant in all four populations, followed by simple (20.29%), and mixed family colonies (5.80%). Most simple families were headed by inbred related reproductive pairs in the Changsha population, while most simple families in the Chongqing-1 population were headed by outbred unrelated pairs. Simple families in the Huanggang population were a mixture of colonies headed by outbred or inbred reproductive pairs. The sample size of simple families in the Chongqing-2 population was too small to yield significant results. Extended families in all four populations were headed on the average by ≤10 neotenics. Mixed families likely originated from pleometrosis. Presence of heterozygote genotypes showed that all neotenic reproductives collected in addition from five field colonies in Wuhan city were sexually produced, suggesting that these colonies did not undergo parthenogenesis. This study contributes to better understanding of the variance of genetic structure and reproductive mode in the genus Reticulitermes.The subterranean termite  Reticulitermes speratus and R. virginicus can use conditional parthenogenesis, where primary queens produce secondary queens by parthenogenesis , but use sexual reproduction to produce workers Reticulitermes spp.An increasing number of studies have employed molecular markers, such as microsatellites, to investigate population genetic structure and colony breeding system in termites, which has improved our understanding of evolutionary genetics, phylogeography, invasion biology, patterns and processes of dispersal, and social organization in termites Reticulitermes has received much attention among the Isoptera when it comes to population and colony genetic studies, but almost all the species used in these studies were from America and Europe. In Asia, only colony genetic structure of R. speratus from Japan was studied using a small number of colonies on a limited spatial scale Reticulitermes termites across different countries even within Europe et al. R. speratus and R. chinensis were close relatives within the genus Reticulitermes, belonging to the same clade. Since R. speratus is one of the species featuring AQS, knowledge of the evolution of this unusual breeding strategy could be significantly advanced by studying how widespread AQS is within the genus Reticulitermes and if the development of AQS is congruent with phylogeny. Thus, we test the hypothesis that colonies of R. chinensis undergo AQS as well.The genus R. chinensis is widely distributed in China, including Beijing, Tianjin, Shanxi and the Yangtze River drainage basin R. chinensis has been obtained through field observations and laboratory experiments, including the growth of incipient colonies, the formation of neotenics, and the time of alate swarms R. chinensis has cryptic foraging and nesting habits with hidden royal chambers, it is very difficult to find and collect reproductives. Thus, population genetic structures and colony breeding systems of R. chinensis are still poorly understood. The objectives of this study were to use microsatellite genotyping to (1) describe the population genetic structure of R. chinensis, (2) infer colony breeding system, (3) and determine whether colonies of R. chinensis undergo AQS as it has been suggested for other Reticulitermes species.The subterranean termite R. chinensis colonies from Huanggang, Changsha and Chonqing cities (P = 0.002) and marginal heterozygote excess under the stepwise mutation model (P = 0.097).STRUCTURE analysis showed that the g cities  belong tg cities  also shog cities  belongedg cities , but sigg cities . The 25 g cities  belongedg cities . Howeverg cities  and no sg cities . Therefog cities  belongedg cities . The majg cities . Interesg cities . EvidencFST) among the four populations of R. chinensis ranged from 0.05 to 0.2  confirming the existence of four genetically differentiated groups indicated by STRUCTURE analysis. Genetic distances (5 to 0.2 . The Hua5 to 0.2 . Two col5 to 0.2 . The STR5 to 0.2  confirm 5 to 0.2 .RS78) and 21 (Rf21-1) alleles were detected per locus with a mean of 14.38 per locus. The expected heterozygosity ranged from 0.69 to 0.79, and the observed heterozygosity ranged from 0.55 to 0.84 (Rf21-1 (frequency: 0.31), RS15 (frequency: 0.15) and RS68 (frequency: 0.11) in the Huanggang population and at locus Rf21-1 (frequency: 0.11) and RS78 (frequency: 0.28) in the Changsha population. Heterozygote excess was detected across all loci in Chongqing-1 possibly due to a recent genetic bottleneck (see above). No evidence for linkage disequilibrium, large allele dropout or scoring error due to stuttering was detected in any of the four populations. to 0.84 . The inbOverall, extended family colonies were predominant (55–83%) in the four populations from Huanggang, Changsha and Chongqing, followed by simple family colonies (17–31%), and mixed family colonies (0–9%). The proportion of extended, simple and mixed family colonies varied among the four populations, with the highest proportion of extended families (83%) in the Huanggang population, the highest proportion of simple families (31%) in the Chongquing-1 population and the most mixed family colonies (9%) in the Chongquing-2 population .F-statistics and relatedness values estimated from the worker genotypes in each population are shown in FIT and FIC values of simple family colonies in Changsha were significantly higher than the expected values in outbred unrelated pairs , but not significantly different from the expected FIT and FIC values for inbred related pairs , but not significantly different from the expected FIT and FIC values for outbred unrelated pairs  of neotenic reproductives representing the first generation of replacement reproductives  from breeding systems assuming three generations of replacement reproductives and/or hundreds of neotenics in at least one of the three genetic parameters  from the other breeding systems in at least one of the three genetic parameters  from all the four simulated breeding systems in at least one of the three genetic parameters  from the other breeding systems with multiple generations and/or high numbers of neotenics in at least one of the three genetic parameters  from the breeding systems involving mixing of colonies . Thus, the neotenics from these four colonies were offspring of extended family colonies headed by multiple neotenics and as such arose at least two generations after colony foundation . The most likely routes of migrants connecting Changsha and Chongqing are occasional human-mediated movement of infested material from one population to the other through roads and trade network, such as building timbers, ornamental plants, and barges travelling along rivers. Similarly, human transport was considered to be a factor in the gene flow for introduced R. flavipes populations between North American and France R. urbis between Balkans and Western Europe Coptotermes formosanus between Fukue and Kyushu islands Large-scale population genetic structure analysis revealed the existence of four populations with significant genetic differentiation in the dataset. The four populations were divided into two main genetic clusters. The population from Huanggang was separated from the other populations by comparatively large genetic distances and showed a uniform genetic pattern, suggesting that there was little contribution of alleles to or from the other populations. The sample sites from Huanggang lie north of the Yangtze River and are thus separated from the sample sites of Changsha and Chongqing, which are located south of the Yangtze River. Thus, geographical barriers, including the Yangtze River in addition to long distances, might limit gene flow between Huanggang and the other three populations. In contrast, the remaining three populations from Changsha, Chongqing-1 and -2 showed some level of gene flow among them. Surprisingly, colonies from Changsha were being assigned to the genetic clusters representing Chongqing populations and C. formosanusR. chinensis has a higher generation rate accelerating the return to mutation-drift equilibrium, the initial bottlenecks were not as severe as in C. formosanus’ intercontinental journey , and/or the small sample size prevented detection of weak bottleneck effects in the Chongqing-1 population The existence of two populations with slightly different genetic characteristics in the same area in Chongqing was peculiar. The Chongqing-1 population showed signs of a genetic bottleneck, but the Chongqing-2 population was in mutation-drift equilibrium. This difference between the two populations colonizing the same area in Chongqing might be explained by the introduction history. The first introduction to Nanshan Hill in Chongqing took place in the early 1990s when a number of ornamental plants and landscape timbers were transported to Nanshan Hill for constructing Nanshan Arboretum R. flavipes populations from France There was significant isolation by distance among colonies in the Huanggang population, indicating that dispersal by primary reproductives is relatively limited over the spatial scale studied (550 m), either because of short range mating flights by alates and/or frequent colony reproduction by budding. Similarly, significant isolation by distance has been found in two Similar to the Chongqing populations, the colonies in the Changsha population also did not show isolation by distance at the spatial scale studied (2.4 km). In contrast to the Chongqing colonies, however, simple family colonies in Changsha were headed by inbred related monogamous pairs. This result does not support the existence of long-range mating flights in this population. Alternatively, as suggested for the Chongqing population, human-mediated colony movement may play an important role in population expansion and reducing population viscosity, i.e. isolation by distance, in Changsha.R. chinensis in our study consisted of a combination of simple family and extended family colonies. A few mixed family colonies were found in all but the Huanggang population. Overall, extended families with a low number of neotenics and generation turnovers were the dominant breeding system. This finding is consistent with previous studies in R. ﬂavipesZootermopsis nevadensis nuttingiR. grasseiR. urbisC. formosanus in Guangdong, Hunan, Kauai, Maui 1 and Charleston R. ﬂavipesR. grasseiR. chinensis colonies had enough time and food to grow and develop into extended families headed by neotenics C. formosanus, which was subjected to disturbance by building and landscaping activities The four populations of R. grassei in southwestern France Z. n. nevadensis in North Carolina C. formosanus in Kyushu, Fukue and Hawaii R. flavipes in Massachusetts R. virginicus in North Carolina C. formosanus in Charleston R. grassei population in southwestern France has also reported that simple family colonies were a mixture of colonies headed by outbred or inbred monogamous pairs Simple family colonies in Changsha were headed by inbred related monogamous pairs. This result suggested that dispersal by primary reproductives is limited in the Changsha population as discussed above. Similarly, simple family colonies headed by inbred related monogamous pairs were found in studies of FIC values for the extended families in Huanggang and Changsha suggest that the mean number of neotenics in our colonies was low (≤10), and that all neotenics were inbred and ultimately the descendants from monogamous pairs of founders. Similarly, extended family colonies were found to be headed by low numbers of inbred neotenics in populations of R. ﬂavipesR. hageniR. virginicusC. formosanus in South Carolina, Louisiana, North Carolina, Hawaii, Guangdong and Hunan Z. n. nevadensisZ. angusticollis and Z. n. nuttingiFIT, FIC, and r for extended families in Chongqing-2 were not significantly different from those for the simulated breeding system based on high numbers of neotenics  for the extended families in Chongqing-2 suggested that the number of neotenics in these colonies was low (≤10). Low numbers of neotenics were also found in the extended family colonies of the other three populations .The strongly negative eotenics , Case B4Z. nevadensisNasutitermes corniger and M. michaelseniReticulitermes species reported from America and Europe R. ﬂavipesR. chinensis populations, larger sample sizes are needed to unequivocally determine the origin of mixed family colonies.Mixed family colonies in Chongqing-2 displayed breeding structure estimates consistent with pleometrosis. Evidence for mixed family colonies originating from pleometrosis was previously found in the lower termite R. chinensis colonies derived from worker genotypes, we also directly observed number and types of reproductives in nine field colonies collected from Wuhan. Four of the dissected field colonies were simple families headed by a pair of primary kings and queens, and five colonies contained multiple neotenics. Three of the five colonies had low numbers of reproductives (6–12). The range is largely consistent with the results from the genetic analyses of worker genotypes from the populations of Huanggang, Changsha and Chongqing. The percentage of our collected field colonies containing secondary kings in R. chinensis was higher than those in R. speratus and R. virginicusR. speratus, secondary kings have been found in only 6.67 percent of colonies  that exhibited parthenogenesis, except for one R. virginicus colony from South Houston (<30°N) R. chinensis colonies located further north and at higher altitudes than the ones in this study display AQS or if parthenogenesis simply does not occur in this species regardless of the local ecological conditions.Clinal variation of ecological factors, such as temperature, moisture, seasonality, availability of wood and soil composition have been shown to influence breeding structure in R. chinensis were collected from fallen trees and stumps from 75 collection sites in three geographic regions of China . The software Micro-Checker DNA was extracted from whole worker bodies using the DNeasy Tissue Kit (Beijing Dingguo Changsheng Biotech Co. Ltd). Twenty-five workers from each collection site were genotyped at 8 microsatellite loci , identifG-Statistics  et al. et al. Since colony members are close kin, only a single randomly chosen individual per colony was used for population genetic analyses to avoid bias by nonindependent genotypes. The number of genetic clusters in the three geographic regions was assessed on the basis of a comparison of the penalized log likelihoods over independent simulation runs using STRUCTURE 2.3.3 with variable numbers of assumed genetic clusters  and the ln of geographic distance (m) for all pairs of colonies within each population was determined p-values from 10,000 permutations, TFPGA v. 1.3, FST) between each pair of populations was computed based on a hierarchical analysis using the program GENETIC DATA ANALYSIS version 1.1 . Mixed family colonies would be characterized by the presence of more than four alleles at one or more loci.Referring to the previous methods F-statistics using the methods of Weir & Cockerham F values  used to infer breeding system were not confounded by higher-level genetic structure r) was determined by the average nest mate relatedness within all colonies of the respective population using the program FSTAT Colony genetic structure was analyzed by R. chinensis, we used the methods of Matsuura et al. et al. To infer reproductive mode of neotenics’ parents, that is, parthenogenesis versus sexual reproduction in We genotyped up to 20 male and female neotenics (nymphoid and ergatoid) from five field colonies collected at Shizi Hill , Houshan Hill (colony 4), and Yujia Hill (colony 5) in Wuhan city using the eight microsatellite loci and protocols described above . The latFigure S1Evanno plot derived from STRUCTURE HARVESTER for detecting number of genetic clusters.(TIF)Click here for additional data file.Figure S2Assignment of colonies to genetic clusters by STRUCTURE (K = 2).(TIF)Click here for additional data file.Figure S3Reticulitermes chinensis collected from field colonies in Wuhan City. (a), primary king (PK) and primary queen (PQ). (b), secondary kings (SK) and secondary queens (SQ).Primary and secondary reproductives of (TIF)Click here for additional data file.Table S1FST) among the four populations.Genetic distance ((DOC)Click here for additional data file.Table S2Composition of secondary reproductives in the five field colonies.(DOC)Click here for additional data file.Table S3Genotypes of secondary queens (SQ) and secondary kings (SK) from the five colonies. S: Sexually produced. Genotypes marked ‘na’ were unavailable due to failed PCR reactions. Colony numbers are the same as those in (XLS)Click here for additional data file.Table S4Latitudes and longitudes of sample sites from three geographic regions in China.(XLS)Click here for additional data file.Table S5Worker genotypes at the eight microsatellite loci from Huanggang, Changsha and Chongqing Cities. Genotypes marked ‘na’ were unavailable due to failed PCR reactions.(XLS)Click here for additional data file.