Bixa orellana L.) is a tropical American crop, commercially valuable due to its application in the food and cosmetics industries as a natural dye. The wild ancestor of cultivated annatto is B. orellana var. urucurana. Although never cultivated, this variety occurs in open forests and anthropogenic landscapes, and is always associated with riparian environments. In this study, we evaluated the genetic diversity and structure of B. orellana var. urucurana populations in Brazilian Amazonia using 16 microsatellite loci. We used Ecological Niche Modeling (ENM) to characterize the potential geographical range of this variety in northern South America. We analyzed 170 samples from 10 municipalities in the states of Rondônia, Pará and Roraima. A total of 194 alleles was observed, with an average of 12.1 alleles per locus. Higher levels of expected (HE) than observed (HO) heterozygosities were found for all populations. Bayesian analysis, Neighbor-Joining dendrograms and PCAs suggest the existence of three strongly structured groups of populations. A strong and positive correlation between genetic and geographic distances was found, suggesting that genetic differentiation might be caused by geographic isolation. From species distribution modelling, we detected that South Rondônia, Madre di Dios River basin, Llanos de Mojos, Llanos de Orinoco and eastern Ecuador are highly suitable areas for wild annatto to occur, providing additional targets for future exploration and conservation. Climatic adaptation analyses revealed strong differentiation among populations, suggesting that precipitation plays a key role in wild annatto’s current and potential distribution patterns.Annatto ( Bixa orellana L.) is a tropical American crop [Bixa  [B. orellana, is an evergreen shrub that is confined to the frost-free tropics [B. orellana and B. urucurana are shrubs, while B. arborea, B. excelsa and B. platycarpa are trees [B. excelsa might have been the wild ancestor of B. orellana, which was accepted by Schultes [B. excelsa is a tree and it is unlikely that domestication during the Holocene would transform all known populations into a shrub [Bixas allowed Moreira et al. [B.urucurana is the wild ancestor of cultivated annatto, B. orellana. They also accepted Pilger’s proposal, published by Kuntz [urucurana is a variety of B. orellana (B. orellana var. urucurana (Willd.) Kuntze ex Pilg.). The word ‘urucurana’ is derived from the Tupi language in which “rana” means false, and is often attributed to wild populations of a species with domesticated populations [Annatto  ,7, which tropics . An impore trees . Ducke [re trees  hypothesSchultes . However a shrub . Analysia et al.  to propoby Kuntz , that urulations .B.orellana var. urucurana occurs in open forests and anthropogenic landscapes, although never cultivated and is always associated with riparian environments [urucurana in northern South America [ronments ,9. WhileB. orellana var. urucurana).In order to make reasoned decisions about sampling procedures to preserve high levels of genetic diversity, researchers must know how genetic variation is organized and distributed throughout the geographic range of a species . The assB. orellana var. urucurana in northern South America, based on these Brazilian Amazonian populations and also on online databases.In this study, 170 samples from 10 populations of wild annatto in Brazilian Amazonia were collected and analyzed using 16 SSR markers, in order to answer the following questions: a) what are the levels of genetic diversity in these populations?, b) what are the genetic relationships among these populations?, c) is genetic diversity geographically structured across these populations?, and d) what is the potential distribution of wild annatto in Amazonia? We used two approaches to answer these questions: neutral genetic variation (SSR markers) for questions ‘a’, ‘b’, ‘c’, and Ecological Niche Modeling (ENM) for question ‘d’ and how it may influence ‘a’, ‘b’ and ‘c’. ENM methods approximate a climatic envelope for the environmental requirements of a taxon from a set of its occurrence localities, summarizing environmental variation across those landscapes to develop a quantitative picture of the potential distribution of the species. They have provided a powerful tool for investigating the ecology and distribution of both plant and animal species ,19, and Bixa orellana var. urucurana) were located and collected in 10 municipalities in the states of Rondônia, Pará and Roraima, in Brazilian Amazonia  following Schuelke [2, 2.5 pmol of forward and M13 labeled primers , 5 pmol of reverse primers and 1 U of Taq DNA polymerase (Fermentas).Sixteen SSR markers developed for orellana ,23 were Schuelke . PolymerPCR was carried out according to Schuelke  in a twoK) was estimated by performing ten independent runs for each K , using 1,000,000 MCMC repetitions and a 200,000 burn-in period. Correlated allele frequencies and admixture were assumed. The most likely number of clusters was evaluated with the adhoc method of Evanno et al. [Possible clusters of wild annatto were simulated using a Bayesian analysis with Structure software.The numbo et al. .Structure, we estimated parameters for genetic diversity, including number of alleles per locus (A), effective allele number (Ne), allelic richness (AR) [HO) and expected heterozygosity (HE), in addition to Wright’s [f). The apparent outcrossing rate (f) for each population [f)/(1+f). The genetic diversity indices A, Ne, HO and HE were estimated with GenAlEx 6.5 [AR and f, with confidence intervals based upon 1,000 bootstrap replicates, were obtained with diversity [Based on the original populations and the clusters identified by ess (AR) , observeWright’s  inbreedipulation , so thatAlEx 6.5 , and estiversity  and poppiversity  for R [3iversity .DCE) [http://tree.bio.ed.ac.uk/software/figtree/). A principal coordinate analysis was used to visualize the dispersion of samples as a function of genetic variation using GenAlEx 6.5 [In order to represent the relationships between individuals and populations, neighbor-joining  dendrogrDCE)  obtainedDCE) . The choDCE) . ConfideAlEx 6.5 .Nm) among populations was estimated by calculating Nm = (1—FST)/4FST [Hierarchical distribution of genetic variation within and among populations of wild annatto, and within and among groups according to the Structure analysis was evaluated using “locus-by-locus” AMOVA with GenAlEx 6.5 . Gene flST)/4FST . In addiST)/4FST  for R [3ST)/4FST . SignifiB. orellana var. urucurana was estimated using the maximum entropy algorithm of Maxent v. 3.3.3e [http://splink.cria.org.br) and Global Biodiversity Information Facility (GBIF) portal. All geographic coordinates were manually verified and incomplete or imprecise records were discarded. For each occurrence record, we obtained 19 bioclimatic variables derived from monthly temperature and rainfall from the WORLDCLIM database with resolutions of 2.5’ [The potential distribution of . 3.3.3e . Maxent . 3.3.3e . The res of 2.5’ . The 19 Fifteen model replicates were run with 75% of occurrences used for calibration and different subsets (25%) used for validation. A logistic threshold value of 10 percentile training presence was retained to separate climatically favorable areas from marginally fit areas. The accuracy of model prediction was evaluated using the area under the curve (AUC), where 1 was the maximum prediction and 0.5 suggested a random prediction . PermutaBecause we observed a high correlation between genetic and geographic distances, we tested the assumption that most of the variability is due to environmental factors.To compare the environmental characteristics of the different areas, we performed principal components analysis (PCA) with ade4  for R 33.HO) ranged from 0.158 to 0.712 across loci, with a mean of 0.385, while the expected heterozygosity (HE) ranged from 0.292 to 0.679, with a mean of 0.520. All loci had heterozygote deficits greater than 10%. The mean Shannon diversity index (I) was 0.975, ranging from 0.472 to 1.354  to 19 (BorG11) with an average of 12 alleles per locus . The obsto 1.354 .Ā) of 3.86 (HO) and expected (HE) heterozygosities for all populations were 0.382 and 0.522, respectively. Significant inbreeding coefficients (f) were detected in most populations, ranging from 0.047 to 0.565. The mean apparent outcrossing rate  included the populations from Cabixi, Cerejeiras and Corumbiara in the Guaporé River basin in southern Rondônia State. Group II  included the populations from Ariquemes and Jí-Paranain the Jí-Parana River basin, and São Francisco do Guaporé, from the Guaporé River basin, located in central Rondônia State. The groups of South RO and Central RO meet and mix at Corumbiara, in southern Rondônia. Group III (hereafter PA and RR) included all the other populations, both north of the Amazon River in Roraima and Pará, and south of the Amazon River in eastern Pará . The relationship among individuals in the dendrogram  suggests that genetic differentiation among the 10 populations is due to isolation by distance, not surprising given the long distances between Rondônia and Roraima, especially.Nm = 0.545). However, when analyzed by the a priori populations, we observed an average gene flow of 1.878 among populations from Rondônia, while the other regions presented lower values (Nm = 0.65). The populations from south Rondônia separately showed a high gene flow amongthem (Nm = 4.843).AMOVA revealed that 21% of the genetic variation was among populations, and the remaining 79% was within populations (p = 0.000), showing that, although most of the diversity is within populations, the variation due to sub-division of the populations is significant . The micThe result of the PCA using the 10 populations sampled in this study and 174 presence-only records with the 19 bioclimatic variables generated three main components that explained more than 91% of the variation. Graphical representation of climate space associated with the first two PCA axes revealed high climatic differentiation between populations from Rondônia, and Pará and Roraima along the second PCA axis . There wThe relative contributions of climatic variables to the PCA axes show that niche differentiation along Components 1 and 2 was driven primarily by precipitation requirements . PrincipB. orellana var. urucurana was estimated with a high area-under-the-curve (AUC) value (0.941) implying very low rates of false negative and positive suitability predictions  among the 10 populations were considerably higher than those in a germplasm bank  with 63 cultivated varieties of annatto using the same 16 SSR loci [This is the first genetic study with wild populations of annatto. The levels of heterozygosity averaged over all loci  observed in our study, the estimated apparent outcrossing rate  indicates the existence of strong structure among populations. Dick et al. [FST = 0.177). This may be due to the fact that tropical species are experiencing moderate to high levels of inbreeding, as a result of the association between low population density, density-dependent animal pollination, and mixed mating systems, factors that may be restricting gene flow [Plant populations are not randomly arranged assemblages of genotypes but are structured in space and time. Genetic structure results from the action of migration, mutation, selection, and drift, that operates within the historical and biological context of each plant species . In thisk et al.  reviewedene flow .B. orellana var. urucurana populations was low in this study (Nm = 0.545), since many of the populations were very distant apart, especially those from Rondônia and the ones from Roraima and Pará, but also between those from Roraima and Pará. According to Wright [Nm = 1.0 is theoretically necessary to counteract the effect of genetic drift. In this sense, our results suggest that genetic drift may have been a dominant factor determining the genetic structure of B. orellana var. urucurana populations. Gene flow among wild annatto populations may occur by seed dispersal along riversand streams [K = 7.The mean level of gene flow among y Nm = 0.5, since  streams , but als streams . All wilK = 7, indicating an intermediate area with a higher gene flow between the two groups.The structure of the Rondônia populations in two groups may occur because the southern populations of this state  are in the Guaporé River basin, while the populations from the center of Rondônia state (Ariquemes and Jí Paraná) are in the Jí-Paraná River basin, so that gene flow by the transport of seeds along the rivers between these populations is infrequent. However, mixed populations between the two groups were found at Corumbiara, in southern Rondônia, classified as a separate group at Gossypium mustelinum Miers) in the state of Bahia, the only cotton species native to Brazil. These authors found high correlation between the genetic and geographic distances using Mantel’s test .The significant correlation values obtained between genetic and geographic distances indicate isolation by distance for the wild annatto populations. In the cluster analysis, based on Cavalli-Sforza and Edwards  chord diOur results provide relevant information for conservation of annatto germplasm. Wild annatto populations may be a source of new alleles, which might be useful to increase the genetic basis of annatto in breeding programs and for conservation strategies. According to Moreira et al.  and alsoFST value (0.201), identifying strong structure among populations, is partially due to our sampling effort, but may also reflect the real and modeled distribution of wild annatto. According to the ENM, wild annatto is not uniformly distributed throughout Amazonia, with a large area in Central Amazonia  and therefore, the picture of the genetic diversity is quite partial. We also observed that in the area between the two regions, there are no predicted populations (low suitability). Therefore, the gene flow among these two different regions could not be recent, but historical, and also probably due to some other historical factors of the populations. We do not know if there are populations in Ecuador that could clarify the relationship among the two main regions studied. The ENM model results in this study implies the recommendation that further collection expeditions should be made sampling The microsatellite loci used in this study revealed high levels of genetic diversity in populations of wild annatto and this diversity is highly structured according to the geographic origin of populations. Wild annatto appears to have a mixed mating system, which may contribute to the patterns of genetic structure observed. Our map of the potential distribution of the species allowed the identification of other potential areas of occurrence in Amazonia and in northern South America. Interestingly, our ENM predicted a wide area of low suitability for wild annatto across Central Amazonia. This predicted occurrence plus increasing population fragmentation resulting from Amazonia deforestation contribute to the low genetic connectivity among disjunct populations of wild annatto. Therefore, our study demonstrates how ecological and anthropic factors may have an impact on the genetics of a native Amazonian species. New plant collections will add to a better understanding of the genetic diversity and structure of wild annatto, as well as the understanding of the crop’s domestication from these wild populations.S1 Table(TXT)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S1 Fig(TIFF)Click here for additional data file.S2 Fig(TIFF)Click here for additional data file.S3 FigK = 3.Branches are colored according to the Structure simulation for (TIFF)Click here for additional data file.


Pelophylax porosus brevipodus is distributed in western Japan and is traditionally divided into two local forms: the Okayama form in the west and the Nagoya form in the east. These two forms are genetically differentiated, but have never been defined taxonomically because their distributions are unclear to date. To complete the distributions and identify the boundary of the two forms, we genetically investigated 16 populations including eight populations located within the unexamined area. We found that the distributional boundary is located within a small area of Hyogo Prefecture where haplotypes of mitochondrial cytochrome b (cytb) and D-loop region corresponding to the two forms co-existed. On the other hand, the polymorphic site of the nuclear gene SOX3 revealed introgression over the boundary into Okayama cytb clade. These results suggest that the two forms were geographically isolated from each other in the past, and secondarily contacted and then accepted one-way introgression. As a next step of the research, taxonomic approach is expected to define the two forms.The Nagoya Daruma pond frog  Pelophylax nigromaculatus and Pelophylax porosus. The latter species is endemic to Japan and is called the Daruma pond frog. It is similar to a traditional Japanese Daruma doll with its round shape. This species is comprised of two subspecies: P. p. porosus (Tokyo Daruma pond frog), which is distributed in eastern Japan, and P. p. brevipodus (Nagoya Daruma pond frog), which is distributed in western Japan. P. p. brevipodus is traditionally divided into two distinct, local forms called the Okayama form in the west and the Nagoya form in the east , mating calls, sex chromosomes, allozymes and mitochondrial genes .In this study, we collected samples of the two major forms in western Japan and investigated sequences of mitochondrial and nuclear genes in order to assess whether the two forms are separated geographically or are distributed sympatrically with mutual genetic introgression. In particular, the eight populations in Okayama and Hyogo Prefectures are located between the known distributions of the two forms and were genetically examined for the first time in 63 years since the primary morphological study of Pelophylax porosus brevipodus, P. p. porosus and P. nigromaculatus used for sequence analyses are listed in Table 1 and their collecting locations are shown in Figure 2. We collected three frogs of P. p. brevipodus each from Aichi and Gifu Prefectures, and reared them at our laboratory, while all other tissue samples were taken from the toe-clips in the fields, and stored in 100% ethanol until use. The frogs were thereafter released to the fields. Animal care and experimental procedures were conducted under approval of the Committee for Ethics in Animal Experimentation at Hiroshima University (Permit Number: G13-3).The number of frogs of cytochrome b and nuclear SOX3 fragments were amplified in 50 μl solution including 1.0 μl of DNA solution, 0.2 μl GXL Taq polymerase (TaKaRa), 5 μl of 10× Buffer, 4 μl of 2.5 mM dNTP, and 1 μl of 12.5 mM primers at 98°C for 5 s followed by 30 cycles of 98°C 10 s, 64°C for 40 s, and 72°C for 60 s. The amplified product was purified using GFX PCR DNA and Gel band purification kit , and was used for nucleotide sequence determination with 3130XL sequencing machine (ABI).Genomic DNA was extracted from the tissue samples using DNeasy blood and tissue kit (QIAGEN) according to the manufacture’s instruction. Mitochondrial p-distance was also calculated using the above software. Primers used are forward 5′-CCA TGC ACT ACA CAG CCG ACA-3′ and reverse 5′-AGG TTT TTG CGA TAG GGC GGA-A3′ for cytochrome b , S1 5′-GTG CGC TCC TCC TGC TTC TTT-3′ and A1 5′-TCC TCA AGT TTT CTG CAT TCT GAT-3′ for SOX3 , under the accession numbers LC316654 and LC316655, respectively.Mitochondrial fragments including D-loop region (300∼500 bp) were amplified and purified by the above methods, and were cloned into pUC118 vector using Mighty cloning kit (TaKaRa) with competent cell DH5α  according to the manufactures’ instructions. One to three colonies were picked up and the nucleotide sequences were determined by the method described above. Gene trees were constructed based on the nucleotide sequence of cytochrome-b gene by the methods of maximum likelihood (ML), neighbor joining (NJ) and maximum parsimony (MP) methods using Mega 7 software . p-distafor SOX3 , and F23for SOX3 . The seqFigure 2 and Table 1). We determined the nucleotide sequences of 566 base pairs of the mitochondrial cytochrome-b gene. Ten haplotypes were identified and the gene tree was constructed using the maximum likelihood (ML) method . The haplotypes formed two distinct clades, which are designated PB-N and PB-O because they correspond to the Nagoya form and Okayama form, respectively. The genetic (p) distance between the two clades was 0.055 and that between the two subspecies was 0.054, suggesting that the genetic relationships among P. p. porosus and the two local forms of P. p. brevipodus are within almost equal range of each other. Notably, two haplotypes of PB-O and PB-N were detected in Kakogawa-YA, -YB and -I populations of Hyogo Prefecture , which were located immediately east over the Kakogawa River. Three of 30, one of six, and three of ten specimens examined in the populations had PB-O haplotypes, while the others possessed PB-N haplotypes. This indicates that the boundary between the two clades is restricted to the small area of Hyogo Prefecture.We collected samples consisting of 156 specimens  from 16 populations covering their present habitat in western Japan (P. p. brevipodus (Table 1). The repeated region comprised of repeats of two kinds of 17-bp units designated types A and B of which nucleotides at the 9th and 10th positions were different: AG and GT, respectively , while pattern ABA was observed in the Kakogawa I2, Okayama-S1 and three Hiroshima populations . In the Iga, Kobe-O and Kakogawa I1 populations , the observed patterns were ABAB, AB, and ABABAB, respectively. All the repeat patterns were thus classified into two types: AB (or repeats of AB) and ABA. The two types corresponded with the two major clades of cytochrome b: PB-N with AB or repeats of AB and PB-O with ABA, respectively. In the Kakogawa-I population (9), the specimen with the PB-N cyt-b haplotype had the ABABAB pattern while that with the PB-O haplotype possessed the ABA pattern.The D-loop region of the mitochondrial genome includes a highly repeated sequence. We cloned this region and determined the nucleotide sequences of specimens from eight populations of us Table . The repus Table . The repSOX3 gene was determined for 140 specimens from 16 populations. The nucleotide at position 233 varied by population . In the six eastern populations , all specimens were homozygous for guanine. On the other hand, in the five western populations , all were homozygous for thymine. In the other five populations  located at the intermediate regions, the specimens were heterozygous or homozygous for guanine or thymine . The frequency of guanine in these populations varied from 10 to 41%.The sequence of 860 base pairs of the nuclear cytochrome b, the two major P. p. brevipodus forms of Okayama and Nagoya were identified as distinct clades, and two major types of the D-loop region supported the cytb clades. The genetic distance  between the two forms was very similar to that (0.054) between the two subspecies. These genetic relationships are well supported by another study that used mitochondrial and nuclear genes  of Hyogo Prefecture and was where two haplotypes of the Okayama and Nagoya forms co-existed. This shows that the two forms were geographically isolated from each other in the past and have secondarily contacted at the small area after they were genetically differentiated. The molecular clock based on cytochrome b and seven nuclear genes estimates that the two forms were separated from each other around 1.3 MYA  and possibly the Okayama form is now accepting introgression from the Nagoya form. We speculate that the ancestral lineage of the Okayama form remains around the eastern edge of the range  where population declining and extinction are concerned. At a next step of the research, taxonomic definition of the two forms are expected , because they are precisely identified and the geographic boundary between the two forms is very clear based on the mitochondrial DNA. Unfortunately, the previous study on morphology (It is evident that the two local forms had been once isolated from each other and accumulated their genetic differences, and thereafter they have secondarily contacted immediately east over the Kakogawa River (rphology  used no rphology  was restIM and MO designed the study and wrote the manuscript. YN, MO, and IM performed the experiments and analyses. TD, KI, YY, TF, and J-iN collected the specimens and discussed about the results. All authors read and approved the final manuscripts.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling Editor declared a past co-authorship with the authors MO and IM.


Passer domesticus) is one of the world’s most ubiquitous bird species, as well as a successful invader. We investigated phenotypic variation in house sparrow populations across a climatic gradient and in relation to a possible scenario of an invasion. We measured variation in morphological, coloration, and behavioral traits (exploratory behavior and neophobia) and compared it to the neutral genetic variation. We found that sparrows were larger and darker in northern latitudes, in accordance with Bergmann’s and Gloger’s biogeographic rules. Morphology and behavior mostly differed between the southernmost populations and the other regions, supporting the possibility of an invasion. Genetic differentiation was low and diversity levels were similar across populations, indicating high gene flow. Nevertheless, the southernmost and northern populations differed genetically to some extent. Furthermore, genetic differentiation (FST) was lower in comparison to phenotypic variation (PST), indicating that the phenotypic variation is shaped by directional selection or by phenotypic plasticity. This study expands our knowledge on evolutionary mechanisms and biological invasions.Studying patterns of phenotypic variation among populations can shed light on the drivers of evolutionary processes. The house sparrow ( Identifying patterns of variation can provide insight into the forces driving evolutionary processes, whether natural selection, phenotypic plasticity, genetic drift – or an interplay between more than one of these processes3. Latitudinal variation in morphology and color is often explained by two important biogeographic rules5. Bergmann’s rule predicts that larger body size should be advantageous to homoeothermic animals in colder climates , due to lower surface-to-volume ratio allowing better heat conservation7. However, there is disagreement on the validity of this rule for birds (42% vs. 72% of bird species9). Gloger’s rule predicts that animals should be more heavily pigmented in humid than in arid habitats, supported by adaptive explanations . The empirical evidence for this rule is convincing, as 96% of bird species conform to this prediction8.The study of phenotypic variation among natural populations and its relation to ecology is one of the central concepts in the field of evolutionary biology12. Neutral genetic differentiation  can indicate the level of gene flow between populations. In order to determine the evolutionary mechanism, genetic differentiation of quantitative traits (QST) is compared to the neutral genetic differentiation (QST-FST comparison). Together, they point to the main evolutionary scenario: directional selection (QST > FST), stabilizing selection (QST < FST), or genetic drift (QST = FST)14. QST is difficult to measure in wild populations, since it requires rearing of animals in common garden conditions; therefore, the phenotypic divergence (PST) is commonly used as a proxy of QST17.Population genetics tools are essential for understanding evolutionary mechanisms19. Invasive species nevertheless provide an opportunity for studying evolutionary and ecological processes in real time20. Successful invaders must quickly adapt to novel environments and expand their range beyond the introduction site, eventually leading to phenotypic differentiation between populations21. For example, reduced levels of neophobia (the tendency to avoid novel objects or foods22) and increased exploratory behavior (searching behavior without immediate requirement23) may have an advantage in successful introductions24, and are therefore expected to characterize introduced populations26. However, it is not entirely understood how populations acquire such novel adjustments27. Reduction in genetic diversity is expected due to bottlenecks29, which may hinder adaptive evolution30. Furthermore, genetic evolution probably requires substantial time to operate31 (but see ref.32). Phenotypic plasticity, the ability of a genotype to express different phenotypes as a response to the environment, may therefore play an important role in the rapid habituation of introduced populations33.Biological invasions threaten biodiversity and cause major economic losses worldwidePasser domesticus) is one of the world’s most common bird species. Due to their commensal nature, and following numerous successful human-mediated introductions, house sparrows are abundant in almost every human-populated habitat34. Many well-documented introduction events exist around the world36. The exceptional success of the house sparrow as an invader, its great abundance, and the extensive knowledge on its biology and distribution, have made it a popular model in invasion biology37. One of the classic textbook study cases of rapid evolution in invasive populations was documented in house sparrows in North America39. A distinct pattern of variation in body size and color occurred within a time span of no longer than a century, corresponding to Bergmann’s and Gloger’s rules.The house sparrow  sparrows appear to be smaller and brighter compared to other populations41. Thus, it was suggested that the southern populations may have been influenced by an Oriental subspecies, P. d. Indicus, introduced by ships via the Red Sea . At the same time, due to a steep climatic gradient in Israel from north to south42, a similar pattern of variation in both size and color is expected, in accordance with Bergmann’s and Gloger’s rules. Mean annual rainfall ranges between 25 mm in the south and 1,000 mm in the north, while mean annual temperature varies from 16 °C to 25 °C, respectively.The house sparrow is native to Israel and abundant throughout the country. The local subspecies, FST, is significantly smaller than the differentiation of phenotypic traits, PST, indicating local adaptation.In contrast to other introductions of house sparrows, the assumed invasion in Israel is based on observational data alone and has not been quantitatively tested. In this study, we examined whether variation in morphology and color agrees with the expectations of the two mentioned biogeographic rules, and whether differentiation is greater between the southernmost region (Eilat) and other regions, in support of the invasion scenario. We measured behavioral variation between regions, since lower levels of neophobia and increased exploration are expected in the southernmost region, due to the potential advantage for invasive populations. We examined whether genetic structure occurs between populations, and searched for additional genetic “signatures” of invasion, such as reduced diversity. Finally, we examined whether the neutral genetic differentiation between populations, F3,667 = 98, P < 0.001; Wing length: F3,678 = 65.5, P < 0.001 . In pairwise post-hoc Tukey tests we found a strong indication for morphological divergence  between the region of Eilat and the more northern regions. Individuals from the area of Eilat were morphologically similar to the Oriental subspecies (P. d. indicus) in body size measurements44.Five morphological traits were measured for sparrows from 18 populations and from museum specimens ; therefore, in order to avoid the effects of multicollinearity, they were removed from following analyses. In a regression analysis with latitude as a predictor, all five traits showed a significant spatial pattern of becoming larger towards northern latitudes: Body Mass: F1,669 = 282.5, r2 = 0.296, P < 0.001; Wing length: F2,679 = 95.8, r2 = 0.218, P < 0.001 , we conducted separate ANOVA and regression tests . Mean values by region are listed in Supplementary Table F3,361 = 53.1, P < 0.001; Fig. F3,361 = 51.6, P < 0.001), and belly . In post-hoc analyses, the only significant difference in right cheek was between Eilat and the other three regions (P < 0.001). Left cheek differed between Eilat and the other regions (P < 0.001), and Center differed from the Negev region (P < 0.01). Belly brightness differed between Eilat and the North and Center (P < 0.001), but not from the Negev (P = 0.88), while the Negev differed from both the North and Center regions (P < 0.001). All three traits showed a significant spatial pattern of becoming darker towards the northern latitudes: right cheek , belly brightness .All three color measurements differed between regions: right cheek brightness . Neophobia levels varied among regions . Sparrows in Eilat were less neophobic than those in the North.Behavioral assays of 81 male sparrows were scored for differences in exploratory behavior and neophobia between regions. Measures of exploratory behavior greatly varied among individuals ; however, we did not find significant variation among regions (χHE) was very similar in all 14 populations (0.74 – 0.79). Estimates of allelic (AR) and private allelic richness (APR) were not lower in populations from the Eilat region than in all other populations. FIS estimates were mostly close to zero, and did not differ among populations (95% CIs comparisons). Heterozygosity excess as an indication of recent bottlenecks was non-significant in all populations but one (Hulda).We genotyped 267 sparrows  from 14 populations, for 8 microsatellite loci. Overall, measures of genetic diversity did not differ among populations (Table FST = 0.0084). Sex-specific genetic differentiation was similar for females (FST = 0.012) and males (FST = 0.010). Clustering results also revealed a lack of genetic structure, suggesting K = 1 as the most likely cluster (out of 14). Although global tests revealed an absence of genetic structure, pairwise comparisons between populations gave some significant FST values, specifically between the southernmost population and the central and northern populations , revealing a pattern of isolation by distance (IBD).AMOVA revealed that most of the genetic variation (99.16%) was explained within populations, corresponding to a low global genetic differentiation over loci . PST surpassed the global FST value for six out of eight phenotypic traits , may occur in the Eilat region.Variation in all morphological measures coincides with the prediction of Bergmann’s rule, as sparrows become larger towards the northern localities. Although evidence for the validity of Bergmann’s rule across species and its adaptive advantage are equivocal, it is considered one of the central biogeographic principles. Thus, our results indicate a possible selective pressure leading to local adaptation. Additionally, four out of five measurements revealed significant differentiation among regions, with emphasized divergence between the southernmost populations and the other, more northern, regions. This provides empirical support for the assumption that foreign populations of a different, smaller subspecies . In contrast, body mass, wing length, and bill length of house sparrows have been shown to respond to seasonal changes36.An increase in coloration along the north-south gradient was also evident, fitting the expectations of Gloger’s rule. Presuming an adaptive advantage for Gloger’s rule, the results indicate an adaptive basis for variation in plumage coloration of house sparrows. Complementary to variation in body size, differentiation between regions in color was also most significant between Eilat and the rest of the localities, with sparrows from Eilat being brighter, resembling the Oriental subspecies25, according to which proxies of behavioral flexibility are expected only in the initial stage of introduction. Furthermore, exploratory behavior and reduced neophobia may induce costs, such as the risk of being revealed to predators or ingesting poisonous foods22. Consequently, cautiousness is likely to be favored once populations have become established.Variation in exploratory behavior was evident among individuals, but we could not detect significant differences among regions. Conversely, significant but weak differences were detected in neophobic response between Eilat and the North region. Individuals from Eilat were less averse to novelty (visited decorated perches more) and spent more time in the center of the arena, as opposed to individuals from the North. Assuming that foreign populations occur in the southernmost region, this finding agrees with the hypothesis that assumes an advantage to being less neophobic in a novel habitat. The lack of difference in exploratory behavior among regions could perhaps be explained by the “adaptive flexibility hypothesis”51, dispersal could be linked to human settlements, which are sparser in the southern, arid, area of Israel compared to the rest of the country. This alone could be a cause for some of the divergence found, independent of the introduction scenario. In contrast to the invasion scenario expectation, we found no evidence of a recent bottleneck52. However, this may be due to an admixture with the local subspecies53 or by a quick recovery from the bottleneck54. Altogether, inferring whether an introduction event occurred based on genetic diversity alone is at best partial, although it can provide additional support for more concrete data.Genetic differentiation between populations was low, demonstrating a lack of structure, indicating high gene flow among populations. We did find a pattern of isolation by distance, as a substantial portion of the significant pairwise differentiation values were between the southernmost populations, and some of the populations in the north and center. This agrees with the invasion scenario, as populations influenced by foreign immigrants are expected to genetically differ from their native counterparts. However, due to strong commensalism and the extremely sedentary nature of sparrowsPST > FST), suggesting that phenotypic variation cannot be explained by genetic drift alone, but at least partially derives from natural selection. However, since the validity of the approximation of QST by PST has been largely criticized55, the results should be interpreted cautiously. Contrary to QST, which measures additive genetic differentiation under common garden conditions56, PST is calculated from phenotypic data alone, and thus it cannot distinguish between the contribution of plasticity and genetic evolution to the observed variation.Most of the variation in phenotypic traits was greater than the neutral genetic differentiation  may provide a better estimate for the genetic differentiation60. Increasing the number of markers would probably decrease the confidence limit, but will have lesser effect on the estimate. In support, a panel of 6736 variable SNPs and a panel of 14 microsatellites produced very similar FST values in a study of house sparrow populations in Norway. However, the 95% confidence limit intervals for the microsatellite markers were wider61. That said, increasing the number of markers used may generate more reliable estimates of the genetic differentiation and effect our estimation of the level of adaptive evolution.Our analyses of the genetic differentiation are based on a dataset of eight microsatellite loci. Although many studies have used comparable number of markers (6–14 microsatellite) to examine genetic differentiation and for 64. Tarsus length, which is the least likely to be affected by phenotypic plasticity, had the smallest c/h2 value, indicating that robustness of the PST - FST comparison was strongest for this trait.Since most of the documented phenotypic traits are plausibly affected by environmental conditions, some variation may be due to phenotypic plasticity. On the other hand, it is safe to assume that a genetic basis does exist for these morphological and color traits, as most of the discussed traits are heritable in house sparrows and other speciesP. d. indicus. Comparing the low neutral genetic differentiation to the phenotypic variation indicates that random evolution by genetic drift is probably not the prime cause of the observed variation. Further investigation, which may include rearing of individuals from distant populations in common garden conditions, should determine whether variation has been shaped by a process of selection or by phenotypic plasticity. House sparrows have been experiencing severe population declines in vast parts of the world in recent decades66. Thus, expanding our current knowledge of its evolution and ecology may prove to be important for future conservation efforts for this ubiquitous and endearing bird.Studying trait variation in a common species, such as the house sparrow, provides an excellent opportunity to investigate evolutionary and ecological questions. Our findings show that phenotypic variation over a climatic and latitudinal gradient agrees with recognized biogeographic rules, while also fitting the scenario of a possible introduction of foreign populations into the studied area. In order to further investigate the possibility of invasion, it may be informative to obtain genetic data from the original range of the subspecies in question, 67 ; 0.01 M NaCl; 0.5% sodium dodecyl sulphate (SDS)). All males were measured using a spectrophotometer  for analysis of color brightness, on three parts of the body: belly (bright colored feathers under the bib), and right and left cheeks (white/grey colored area beneath the eye). Color data were obtained for males only, since plumage variation is expected to be more evident in males. GretagMacbeth’s Eye-One Share v1.4 software was used to translate the data to a 380–730 nm spectrum table (http://www.brucelindbloom.com). We analyzed variation in one component of RGB (green), indicative of the relative brightness of the sample, transformed from a 0–255 scale to a scale of 0–1, where 0 = black (dark), 1 = white (bright). We also measured morphology and color traits in specimens collected over the past 80 years in Israel and vouchered at the Steinhardt Museum of Natural History, Tel Aviv University . Museum specimens were not included in the genetic analysis.A total of 486 adult house sparrows  were caught using mist nets in 18 localities during 4/2013, and between 11/2014 and 6/2015, from north to south of Israel (~420 km). All capture sites were located near livestock farms in suburban and rural settlements . The tent floor was divided into four quadrats and six artificial wooden perches were placed inside . In order to stimulate a novelty response, three perches were decorated with “novel” objects, presumed foreign to the natural habitat of the sparrows .A total of 94 males  were randomly selected for a novel environment test during 2014–2015. In order to reduce stress caused by handlingExploratory behavior was measured according to the following variables, summed to a final score: (1) Proportion of the tent explored – number of quarters visited (0 to 4), and number of perches used (from 0 to 6); (2) Location changes (each movement between quarters/ from quarter to perch/ from perch to perch); (3) Number of hops; (4) Number of flight incidents.Each variable received a score, normalized for the duration of each assay, and relative to the best result. For example, if a bird visited 6 perches during 10 minutes received the best result for this variable ( = 1), then a bird that visited only 3 perches during 20 minutes would receive a score of 0.25 out of 1. A separate score was given for neophobic behavior, measured according to the proportion of decorated perches visited , and the proportion of time spent in the center of the arena as opposed to its corners.73, Pdo574, Pdo875, CAM01, CAM02, CAM05, CAM10, CAM15, CAM17, CAM2076. Forward primers were labeled with either 6-FAM, ROX, VIC or NED fluorescent dyes and PCR reactions were performed separately for each marker. PCR Products were combined into three multiplex mixes for genotyping , according to the protocol of QIAGEN DNeasy blood & Tissue kit. DNA was amplified by polymerase chain reaction (PCR) for ten nuclear microsatellite markers: Pdo177, as well as the presence of null alleles (checked with Cervus v3.0.778). Markers Pdo8 and CAM20 were excluded from the analysis due to significant deviation from HWE and high null allele percentage . Alleles per locus ranged from 4 to 28 for the eight remaining markers. Since sample sizes in some localities were too small to obtain meaningful results, they were merged with the closest geographic locality (between 4 to 12 km distance between two merged populations), forming a total of 14 genetic populations. Genetic structure of populations was evaluated using two methods: first, analysis of molecular variance, AMOVA79, implemented in Arlequin. This is a hierarchical analysis that partitions total variance into covariance components due to intra and inter-individual differences and inter-population differences. Populations were allocated into pre-defined groups . The second method used was Bayesian clustering implemented in STRUCTURE v2.3.480. STRUCTURE assigns samples into clusters (populations) using an admixture model, assuming correlation of allele frequencies, without prior knowledge of sample locality. We ran the clustering with a 20,000 burn-in period followed by 50,000 MCMC iterations for possible K = 1–14 populations, 10 times for each run (K). In order to infer which K was most likely, we ran the results in Structure Harvester81.Occurrences of linkage disequilibrium (LD) and deviation from Hardy-Weinberg equilibrium (HWE) were tested for each population, using Arlequin v3.5.2.2FST index13, estimated using Weir & Cockerham’s θ82, and implemented in Arlequin. Pairwise FST values were used to assess whether a pattern of isolation-by-distance (IBD) exists between populations, using the Isolation by Distance Web Service v3.2383. This application implements Mantel Test84 with 10,000 randomizations, for matrix correlation between genetic distance  and geographic distance .Genetic differentiation between populations was assessed by the R) and private allelic richness (APR) in HP-Rare v1.185, compensating for differences in sample size. Variation in expected heterozygosity (HE) and FIS index86 were measured with the R package DiveRsity87. Detection of possible recent bottlenecks was achieved by measuring levels of heterozygosity excess, with BOTTLENECK v1.2.0288. We ran the software for Wilcoxon sign-rank test and mode-shift indicator89 with 1,000 replications under the two-phase model (T.P.M).Levels of genetic diversity within populations were estimated by allelic richness .The sampled populations were separated into four regions . Variation in morphology, color, and behavior among regions was estimated for each trait separately using Analysis of Variance (ANOVA) and post-hoc Tukey tests. For traits that deviated from assumptions of normality and homoscedasticity we used two alternatives, Welch’s ANOVA, and a Kruskal-Wallis test, followed by Dunn’s post-hoc test.We used linear regression analyses in order to examine the factors contributing to the variation in morphology and color (separately for each trait) with latitude and climate as predictor variables. For traits that deviated from the model’s normality assumption we applied square-root transformations.http://www.gps-coordinates.net). Arc GIS v10.3 (Esri Inc.) was used to produce climatic layers for all coordinates, extracted from the WorldClim90 database (www.worldclim.org). We ran two separate PCAs for temperature and precipitation .Exact GPS coordinates  were obtained for all localities and approximated for museum specimens using GPS-coordinates website , and heritability (h2). Phenotypic variance between (σ2B) and within (σ2W) populations was estimated using the MCMCglmm package in R91. For this analysis we used a subset of the color and morphology dataset, including only individuals for which we had genetic data as well. We constructed linear mixed models for all phenotypic traits, using population  as a random effect and sex as a fixed effect for morphological traits, and year of sampling as a fixed effect for color traits. The default priors of the R package were used . To account for the robustness of the comparison, for each trait where PST exceeded FST we calculated the critical c/h2 value, for which the upper 95% CI of FST equals the lower 95% CI of PST17.The value of All methods were carried out in accordance with the guidelines and regulations of the Israeli animal welfare law and the Israeli wildlife protection law. All capture and handling of birds, as well as all experiment protocols were approved and performed under permit (#L-14-062) granted by the Veterinary Service Center at the Sackler Faculty of Medicine, Tel Aviv University, according to the Israeli animal welfare law. The house sparrow is classified as a pest species under the Israeli wildlife protection law; therefore its capture for research purposes does not require an additional permit.The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.Supplementary materials


Sogatella furcifera (Horváth), is a destructive pest of rice in the Greater Mekong Subregion (GMS) countries including Cambodia, Laos, Myanmar, Thailand, Vietnam, and China’s Yunnan Province. Our previous study not only confirmed the immigration sources of the WBPH in China’s Yunnan Province were from Myanmar, Vietnam, and Laos, but also indicated that Cambodia was likely an additional migration source. To further clarify the migration sources and patterns of the WBPH in the GMS, we investigated the genetic structure of 42 WBPH populations using microsatellite loci markers. The analysis of genetic diversity, heterozygosity deficit, and heterozygosity excess based on the nuclear markers suggest that there is extensive gene flow between the 42 sampled populations from the GMS. The genetic structure confirmed the immigration sources of WBPH as revealed by mitochondrial markers and trajectory analyses methods in previous studies. These findings will aid in the sustainable regional management of this insect pest in the GMS.The white-backed planthopper (WBPH),  Sogatella furcifera (Horváth) (Hemiptera: Delphacidae), is one the most destructive pests in rice producing areas of the Greater Mekong Subregion (GMS) including Cambodia, Laos, Myanmar (Burma), Thailand, Vietnam, and China’s Yunnan Province. The migration sources and dispersal patterns within the region have been examined by several researchers in recent years. For example, a number of studies have begun to explore the migration sources of the WBPH based on the trajectory analyses methods6. Due to their small body size, short lifespan, and long distance dispersal capability, it has been difficult to use fluorescent marker dyes, radar monitoring or other conventional approaches to study the migration of these insects7. Molecular makers have the potential to overcome those challenges9. Using both mitochondrial genes and microsatellite loci as molecular markers, migration patterns of the diamondback moth within China have been identified from the southern to northern regions10.The white-backed planthopper (WBPH), 11. The immigration sources into Yunnan Province during April to early May were estimated to be mainly from Myanmar, while the mid-May immigrations originate from northern Vietnam12. Recently, we have used the mitochondrial cytochrome oxidase I (mtCOI) marker to determine the sources and patterns of the WBPH in the GMS13, demonstrating that the potential emigration of the WBPH from the GMS consists of three possible major routes. Those results not only confirmed that the immigration sources of the WBPH into China’s Yunnan Province were from Myanmar, Vietnam, and Laos14, but also indicated that Cambodia was a likely additional migration source. As nuclear genetic markers, microsatellite loci have been widely used in elucidating the genetic structure of insect populations, because they are inherited codominantly and have a broad distribution and high abundance throughout the genome18. Determining the genetic structure of the WBPH in the GMS based on nuclear markers will provide further insights into the gene flow and migration patterns of the WBPH in this region.Our previous studies suggested that a small number of the WBPH are able to overwinter in the low latitude paddy area in the southern part of Yunnan Province, ChinaIn the present study, we investigated the genetic structure of 42 WBPH populations using nuclear (microsatellite loci) markers, to reveal the gene flow and migration patterns of the WBPH in the GMS. These results will benefit future sustainable management programs of this insect pest in the GMS.Na) ranged from 3.375 to 8.625, and the effective number of alleles (Ne) ranged from 2.5234 to 5.0602. The expected heterozygosity (He) ranged from 0.5639 to 0.7650 while the observed heterozygosity (Ho) ranged from 0.2452 to 0.5563. The He value in each population was higher than the value of Ho. Nei’s expected heterozygosity (Nei) ranged from 0.4922 to 0.7459. The level of genetic diversity indexes was similar in most populations.The data microsatellite locus KJ7 was eliminated due to the existence of the high null allele, thus, only eight loci were used in the analysis of genetic diversity, genetic structure, and gene flow. Values of genetic diversity indexes of the populations from China’s Yunnan Province are given in Table He in Laos populations ranged from 0.5857 to 0.7222 which was similar to those from Thailand (0.6128–0.7113), Cambodia (0.7279–0.7650), Myanmar (0.5639–0.6997), and Vietnam (0.6984–0.7236). The average He value in China’s Yunnan populations (0.6707) was similar to those in the adjacent countries (0.6840) (P > 0.05)  in only three populations . The significant heterozygosity deficit in the three populations may result from demographic expansion19 because there were no significant departures from Hardy-Weinberg equilibrium (Fis) in these populations  was detected in twelve of the populations  Fst values were associated with a significant exact test (Table K = 2) , and a few of individuals from three of the Cambodian populations  could also be differentiated from the other individuals.When considering each pairwise st Table . AnalyseP = 0.8810)  Fig. , indicatP < 0.01) was small, it was significant. These results demonstrated that the variations of genetic differentiation in the WBPH are mainly from inter-populations.Significant genetic structure of the WBPH was observed at two hierarchical levels (among populations and within populations) Table . Most of9. In Cambodia, Laos, Myanmar (Burma) and Vietnam, the total migrants (Nem) ranged from 883.4 (L1) to 3322.1(M4). A high numbers of total migrants (Nem > 1000) were found in several populations, including L2, L4-L7 of Laos, C1, C3-C4 of Cambodia, V1-V4 in Vietnam, and M1-M4 of Myanmar, while, Thailand had the lowest number of total migrants, i.e., T1 (Nem = 685.9), T2 (Nem = 807.7). In Yunnan Province, the total migrants (Nem) ranged from 591.5 (CX) to 1224.5 (YUJ). A total of 7 populations had a high numbers of migrants (Nem > 1000), including MD in western Yunnan (Nem = 1020.0), YUJ and SM in central Yunnan , GM in southwestern Yunnan (Nem = 1182.1), SZ in northeastern Yunnan (Nem = 1012.5), FN in southeastern Yunnan (Nem = 1207.1), JP in southern Yunnan (Nem = 1160.2). Within the province, the number of migrants was the highest in the southeastern region (YS and FN) (average Nem = 1071.9), and the lowest in central Yunnan  (average Nem = 885.3).Based on microsatellite data, the average values of the numbers of migrants in the different countries were similar except in Thailand Table . In Chinet al. showed that most microsatellites fit TPM better than SMM or IAM20. Based on the TPM model, there is no significant heterozygosity excess in any of the tested populations, which suggests that no severe bottleneck effects exist in the GMS populations. Our study indicate that bottleneck effects have not played an essential role during the genetic differentiation of the WBPH. This may be due to the bottleneck effects on heterozygosity being transient and observable for only a few generations21.This study showed that the level of the genetic diversity in most populations originating from different countries was similar, suggesting that extensive gene flow occurs between the WBPH populations within the GMS. The heterozygosity deficit is used to test for population expansion, whereas the heterozygosity excess test is used to provide evidence of a genetic bottleneck. In this study, only three populations from China’s Yunnan Province had a significant heterozygosity deficit. The results in testing the heterozygosity excess were completely inconsistent under the TPM, SMM, and IAM models. Di Rienzo 9 showing that there are multiple immigration sources of the WBPH in China’s Yunnan Province including Myanmar, Vietnam, Laos, and Cambodia. Although the populations from central Thailand (T1 and T2 populations) were shown to have an extensive gene flow in this study, both had limited gene flow with neighboring countries, limiting the probability of immigration of these populations into China’s Yunnan Province. These results support previous results based on the trajectory analyses methods23 that the populations in central Thailand would be incapable of immigrating to Yunnan due to the lack of sufficient wind currents, incorrect wind direction and the excessive distance involved, although gene flow with the populations in Vietnam, Laos, and Cambodia would be possible23.The extensive gene flow between WBPH populations within the GMS is consistent with our previous study23. The immigration of the WBPH individuals from Cambodia into China’s Yunnan may be indirect from Vietnam or Laos, which have extensive gene flow with those in Cambodia. Whether the immigration of WBPH from Cambodia into China’s Yunnan is direct or/and indirect remains to be determined.The Cambodian populations  do have a limited gene flow with those from central Thailand but have extensive gene flows with other populations from other countries in the GMS. Our previous study showed that the specific mtCOI haplotype from Cambodia is only found outside the country in China’s Yunnan Province (BS and GM populations). The extensive nuclear gene flow also substantiates the probable occurrence. However, the trajectory analyses methods demonstrated that the emigrant population from Cambodia would not be able to migrate to Yunnan Province25. For example, Xu et al. showed that two insulin receptors in the migratory brown planthopper (Nilaparvata lugens) (Stål) (Hemiptera: Delphacidae) play an important role in controlling long versus short wing development25, providing the first evidence of a molecular basis for the regulation of wing polyphenism in insects. We had elucidated the genetic diversity of the WBPH in the GMS countries based on mtCOI and SSR markers. In future studies, it will be necessary to analyze the reliability and significance of these molecular markers relative to their consistency with WBPH biological data. With the exception of the molecular markers, the genome difference and transcriptome analyses also should be considered in a followup study. Although the 42 populations that were collected from the GMS countries help to explain the genetic diversity within somewhat limited areas, additional populations from different regions and from different seasonal occurrence in the GMS should be collected and analyzed in future studies. Additional attention needs to also be paid to more widely distributed populations, such as those from Malaysia, Indonesia, the Philippines, Bangladesh, Pakistan, India and other known occurrences of S. furcifera within Asia and outside of Asia to further explore and clarify the source population of S. furcifera in the GMS.The immigration sources and patterns of the WBPH as demonstrated by mitochondrial and nuclear markers are helpful in devising future, sustainable, regional management programs for this important pest in the GMS. However, the genetic basis for the migration should be further explored, including the influence of such factors as wing polyphenismBased on the nuclear (microsatellite) markers, the analysis of the genetic diversity, heterozygosity deficit, and heterozygosity excess suggested that there is extensive gene flow between the WBPH populations in the GMS. The genetic structure confirmed the immigration sources of the WBPH as revealed by mitochondrial markers. There is a certain gene flow between the populations in Thailand and Cambodia. It should be further explored whether the immigration of WBPH from Cambodia into China’s Yunnan Province is direct or/and indirect. These results will be helpful to the sustainable regional management of this insect pest in the GMS.Adult WBPH samples were collected from 42 locations in the GMS during 2014–2015 Table . The sam2, 0.2 μM dNTPs, 1 unit Taq DNA polymerase, 2 μL template DNA, and 0.2 μM of each primer. PCR amplification was carried out as follows: initial denaturation at 94 °C for 4 min, followed by 35 cycles of 30 s at 94 °C, 90 s at the primer-specific annealing temperature  (Table Na), the effective number of alleles (Ne), the observed heterozygosity (Ho), the expected heterozygosity (He), and Nei’s expected heterozygosity (Nei) of each of the 42 WBPH populations were calculated using POPGENE v.1.3126. The estimator of the fixation index, Fis, was performed to detect deviation from neutrality using GENEPOP v.4.227. Wilcoxon test P value for heterozygosity deficit compared to expectations at mutation-drift equilibrium (Pwil) was calculated using ARLEQUIN v.3.5 software28.Based on the microsatellite alleles, the average number of alleles per locus  recommended for microsatellite data20. The possibility of bottleneck events within each of the 42 populations was examined under three mutation models , respectively20. The TPM model was used with default settings of 30% and SMM model, 70%, respectively.Deviation of the mutation-drift equilibrium in each population was tested using the BOTTLENECK softwareFst29, was calculated using GENEPOP v.3.4 software27. The correlation between genetic differentiation and geographic distance was examined by Mantel test using IBDWS v.3.15 software28. The distribution of genetic variation was investigated by the analysis of molecular variance (AMOVA) using ARLEQUIN v.3.5 software28, and by calculating allelic diversity, heterozygosity, and pairwise values of Fst among the 42 populations. The genetic clustering of samples were examined using STRUCTURE v.2.3.2 software30, using the Bayesian clustering approach with a burn-in period of 50,000 iterations and one million Markov chain Monte Carlo (MCMC) repetitions under the admixture ancestry model. Twenty independent runs were performed for each testing K value, ranging from K = 1 to 42, and ΔK was used to calculate the optimal number of genetic clusters (K)31.The traditional population differentiation approach, Weir and Cockerham’s estimator of the fixation index Nem was calculated using microsatellited data respectively. Nem is M  calculated using Bayesian search strategies in MIGRATE v. 3.2.1632.To evaluate the dispersal of the WBPH between the populations in the GMS, the effective numbers of migrants per generation


Malaclemys terrapin) were a popular food item in early twentieth century America, and were consumed in soup with sherry. Intense market demand for terrapin meat resulted in population declines, notably along the Atlantic seaboard. Efforts to supply terrapins to markets resulted in translocation events, as individuals were moved about to stock terrapin farms. However, in 1920 the market for turtle soup buckled with the enactment of the eighteenth amendment to the United States’ Constitution—which initiated the prohibition of alcoholic drinks—and many terrapin fisheries dumped their stocks into local waters. We used microsatellite data to show that patterns of genetic diversity along the terrapin’s coastal range are consistent with historical accounts of translocation and cultivation activities. We identified possible instances of human-mediated dispersal by estimating gene flow over historical and contemporary timescales, Bayesian model testing, and bottleneck tests. We recovered six genotypic clusters along the Gulf and Atlantic coasts with varying degrees of admixture, including increased contemporary gene flow from Texas to South Carolina, from North Carolina to Maryland, and from North Carolina to New York. In addition, Bayesian models incorporating translocation events outperformed stepping-stone models. Finally, we were unable to detect population bottlenecks, possibly due to translocation reintroducing genetic diversity into bottlenecked populations. Our data suggest that current patterns of genetic diversity in the terrapin were altered by the demand for turtle soup followed by the enactment of alcohol prohibition. In addition, our study shows that population genetic tools can elucidate metapopulation dynamics in taxa with complex genetic histories impacted by anthropogenic activities.Diamondback terrapins ( Malaclemys terrapin) were considered a delicacy and were highly sought. The historical market price for terrapins demonstrates their popularity: a dozen larger terrapin sold for $70.00 USD during 1915–1920 [Turtle soup was a popular food item in the United States during late nineteenth and early twentieth centuries. Although many turtle species were consumed, diamondback terrapins  inferring population structure in a Bayesian framework, as well as with discriminate analysis of principal components (DAPC); ii) estimating both historical and contemporary levels of gene flow and comparing them to infer changes in gene flow over time; iii) testing alternative models of population structure, including stepping-stone models and models that include translocation events; and iv) surveying for population bottlenecks. Based on previous studies and historical documentation, we hypothesized: i) admixture between Atlantic and Gulf populations, but not with Florida populations; ii) some non-adjacent populations (e.g. Texas and New Jersey) would show increases in contemporary gene flow, consistent with translocation; iii) population genetic models incorporating translocation would outperform other models; and iv) genetic tests for bottlenecks would fail to detect population contractions in populations known to have experienced serious decline, due to human-mediated influxes of genetic diversity.We analyzed six polymorphic microsatellite loci   from 12 We demarcated coastal population structure with two methods. The first was a Bayesian analysis in the program STRUCTURE v. 2.3 . The secFor DAPC, we first optimized the number of PC axes to avoid under- or over-fitting our population genetic models. We accomplished this with cross-validation, which uses stratified random sampling and divides the dataset into a training set and a validation set. We partitioned the training set to be 50% of the data and the validation set to 50%, and employed 100 replicates. The cross-validation method estimated 60 axes should be retained. The Bayesian information criterion (BIC) was used to choose the optimum number of clusters for DAPC analysis. Four discriminate functions (DF) were retained for each analysis.h/μ: proportion of migrants per generation, scaled by mutation rate). For these analyses we treated sampling localities as populations with the exception of South Carolina. Because South Carolina lacked structure among its sampling localities  were modeled under a uniform distribution bounded between 0.0001 and 100, and historical gene flow estimates were bounded between 0 and 2000.We used MIGRATE v. 3.6.5  to estimcalities , we treaFor estimates of contemporary gene flow (m: proportion of migrants per generation), we used BAYESASS v. 3.0 . We ran e generations  in the past [Because MIGRATE uses the coalescent, it estimates gene flow over long periods of time, approximately 4Nthe past . Thus, ithe past , where “the past , 30 Withh/μ) by a mutation rate (μ) of 2.72 x 10−3 mutations site-1 generation-1. This mutation rate was estimated explicitly for the microsatellites used in previous studies [h. Positive values of Δm indicate increased levels of contemporary gene flow, negative values indicate reduced contemporary gene flow, and values near zero indicate no temporal change in gene flow.To estimate temporal changes in gene flow, we compared historical and contemporary estimates. First, we multiplied the historical gene flow estimates from MIGRATE  and the lowest were from NY to FL (mh = 0.0128). Contemporary gene flow estimates show SC to NC exhibited the highest levels of gene flow  exhibits a paucity of genetic variation across its range [Although we documented population genetic evidence of translocation between some non-adjacent populations, our study failed to find genetic evidence for some known instances of translocation. In particular, we did not detect increases in contemporary gene flow or admixture between TX and NC ; Table 3ts range , suggestIt is well documented that terrapin populations historically underwent severe contractions , but we Thus, our study suggests that population genetic structure in the diamondback terrapin possesses the signature of historical translocation events. Translocation among natural populations is known to increase levels of population admixture and genetic diversity , 47. At Historically, terrapins have been divided into seven subspecies , but recOur study shows that convoluted genetic histories can be disentangled with modern population genetic tools and that translocation can leave an indelible fingerprint in populations. Anthropogenic influences increasingly disrupt population dynamics , 62, 66;S1 FigOverlapping likelihood scores for the number of population in the north Atlantic .(TIFF)Click here for additional data file.S2 FigPCA analysis of sampling localities. Location number corresponds with Figs (EPS)Click here for additional data file.S1 TextDataset with all terrapin genotypes.(XLSX)Click here for additional data file.S2 TextSTRUCTURE/adegent input files.(STRU)Click here for additional data file.S3 TextBAYESASS input file.(TXT)Click here for additional data file.S4 TextMIGRATE input file.(TXT)Click here for additional data file.S5 TextBOTTLENECK input file, sampling localities.(TXT)Click here for additional data file.


Microtus arvalis) has been a model species of small mammal for studying end-glacial colonization history. In the present study we expanded the sampling from central and eastern Europe, analyzing contemporary genetic structure to identify the role of a potential ‘northern glacial refugium’, i.e. a refugium at a higher latitude than the traditional Mediterranean refugia. Altogether we analyzed 786 cytochrome b (cytb) sequences  from the whole of Europe, adding 177 new sequences from central and eastern Europe, and we conducted analyses on eight microsatellite loci for 499 individuals (representing nuclear DNA) from central and eastern Europe, adding data on 311 new specimens. Our new data fill gaps in the vicinity of the Carpathian Mountains, the potential northern refugium, such that there is now dense sampling from the Balkans to the Baltic Sea. Here we present evidence that the Eastern mtDNA lineage of the common vole was present in the vicinity of this Carpathian refugium during the Last Glacial Maximum and the Younger Dryas. The Eastern lineage expanded from this refugium to the Baltic and shows low cytb nucleotide diversity in those most northerly parts of the distribution. Analyses of microsatellites revealed a similar pattern but also showed little differentiation between all of the populations sampled in central and eastern Europe.The common vole ( Phylogeography is a discipline which uses molecular markers to infer population movements at the end of the Pleistocene and during the Holocene, to identify where glacial refugia were located and to establish genetic characteristics of present-day populations, including geographic barriers obstructing gene flow . TherefoDuring the Pleistocene in Europe there were three substantial glacial periods, separated by warmer interglacials: the Elster glaciation , the Saale glaciation (300–130 kya) and the Weichselian (or Vistulian) glaciation 115–11.5 kya) . Conside–11.5 kyaMicrotus arvalis  is one of the best studied small mammal species in Europe, in terms of phylogeography and population genetics. The common vole comprises two parapatric chromosomal races which are often considered subspecies, or even species, with the names M. arvalis and M. obscurus  (b (cytb) variation [b  . The twoariation –25. In tation [b . Previouagrestis , 27. Thragrestis , 28, 29)agrestis , 31).Previous studies of the Eastern lineage have been geographically limited, confined mainly to Poland , 30. BasSpecifically, this broad sampling allows us to consider the following questions relating to occupation of northern glacial refugia by the common vole: (i) Is the pattern of mitochondrial and microsatellite variation consistent with the Eastern lineage deriving from the Carpathian Basin, as opposed to a refugium or refugia located elsewhere? (ii) How does the timing of expansion of the Eastern lineage relate to events during the last glaciation, particularly the LGM? (iii) Is the differentiation that is evident in Poland, based on microsatellite variation, replicated at a wider scale in the Eastern lineage and what is the implication for the refugial population and its subsequent expansion? Overall, the level and density of sampling in the area surrounding this northern refugium provides an exceptionally detailed perspective on the relationship between genetic variation in a contemporary population and the refugium, or refugia, from which it originated.All capture and handling procedures of voles in Poland were approved by the Local Ethics Committee for Animal Experiments in Białystok (Decision no: 5/2013). Samples of voles from Croatia, Czech Republic, Hungary, Romania, Serbia and Slovenia were collected according to the Legislation of Nature Protection and Legislation of Animal Welfare valid in these countries and permission to the Slovenian Museum of Natural History given by the Veterinary Administration of the Republic of Slovenia. No additional permits from Ethics Committee were needed. All capture and handling procedures of the common voles from Russia and Ukraine were approved by the Animal Care and Use Committee of the A.N. Severtsov Institute of Ecology and Evolution of the Russian Academy of Sciences . No additional permits were required. Permission from the landowners was obtained where necessary. Samples were not collected from protected locations and field studies did not involve endangered, threatened or protected species.Microtus rossiaemeridionalis), a sibling species almost identical in morphology to the common vole [b sequences from those samples and they were identified using BLAST (https://blast.ncbi.nlm.nih.gov/Blast.cgi). They were not included further in the analyses performed in this study. The sequences obtained were deposited in GenBank (accession numbers: KX380179-KX380191).We obtained new mtDNA data from 177 samples of the common vole from Poland, Belarus, Russia, Moldova, Ukraine, Czech Republic, Hungary, Slovenia, Croatia, Romania, and Serbia . Samplesmon vole . We obtab sequence (1143 bp) were conducted according to methods described by Wójcik et al. [b sequences from 786 individuals . In allividuals  Tables.b sequences obtained from newly-collected individuals were determined in DnaSP 5.1 [The nucleotide sequences were aligned and manually checked in BioEdit 7.2.5 . As in onaSP 5.1  using thnaSP 5.1 .A median-joining network was constructed for all 786 sequences in Network 4.6 , to esta−7 substitutions/site/year-1 was used to calibrate the genealogy and date tMRCAs of each lineage [http://tree-bio.ed.ac.uk/). The analyses were repeated without sequence data to test the effect of the joint prior distributions on the posterior distributions for each parameter of interest.We used Bayesian genealogy sampling in BEAST 1.8 , with al lineage , 30. Pos lineage . PosteriD and Fu’s [FS statistics and the mismatch distribution using sum of squared deviations SSD [D and Fu’s FS significant, SSD not significant; see [-7substitutions/site/year-1 was applied and the generation time was assumed to be one year [Nucleotide and haplotype diversity were calculated in DnaSP. To test for recent population expansion in mitochondrial lineages, we applied three tests in Arlequin 3.5.1.2 : Tajima’and Fu’s  FS statiions SSD , with siant; see , 30, 50)ant; see , 52) usiant; see   for the Eastern lineage was mapped with interpolation using ArcGIS 10.3.1 Geostatistical Analyst . Populations with only one individual were excluded to avoid cases where π is equal to 0. Altogether we used 293 sequences from 74 populations. Interpolation was carried out using an Inverse Distance Weight model  which uses a linear-weighted combination set of sample points, assigned as a function of the distance of an input point from the output cell location. This means that the greater the distance is, the less influence the input cell obtained has on the results.We used 311 new specimens for microsatellite analysis, obtained from the Carpathian Basin, Russia and the Balkans, together with 188 specimens which were already analyzed in the previous study of Stojak et al. . We initO) and expected heterozygosity (HE) were calculated in Arlequin. FSTAT v. 2.9.3 [ST values [ST) and geographic distances was tested using a Mantel test [Only populations with five or more individuals were included in all population-level analyses. Observed  under the admixture model and with the assumption that allele frequencies among populations are correlated. The optimal number of clusters were identified using the Evanno method ; log probability). Calculations were conducted in STRUCTURE HARVESTER [q ≥ 0.8. Populations with assignment probability of 0.2 < q < 0.8 were classified as ‘intermediate’ [K and to generate graphical representations.To establish the number of genetic clusters occurring across central Europe we initially used Bayesian analysis in STRUCTURE 2.3.4 . Ten indhod  and meaARVESTER . We assimediate’ , 63. We mediate’  and Distmediate’  to assemAdditionally, we performed Spatial Principal Components Analysis  in R stE) were conducted for 42 populations to identify potential hotspots of genetic diversity to complement the nucleotide diversity analysis with cytb. Only populations with 5 or more individuals were included. Two Russian populations were excluded from this analysis because they were geographically distant from all the other populations. Analyses were carried out using ArcGIS 10.3.1, adopting the same model as for cytb.Interpolation of allelic richness (AR) and expected heterozygosity (Hb sequence (1143 bp) was successful for all 177 new samples of the common vole  , 71 wereThe network analysis allowed us to assign the new sequences to the six previously described mtDNA lineages –30, 72. b genealogy, illustrated by the MCC tree and obtained from MCMC simulations with a coalescent model, all of the sequences were again included in the six previously identified lineages  and the Eastern lineage 8.3 kya (95% CI: 4.8–13.9 kya). The Bayesian skyline plot obtained for the Eastern lineage suggested that population expansion started approximately 10 kya  and 0.581–0.925 (HE). Null alleles were identified only for Moe6 in a few populations. As this locus had little influence on the overall results, it was not excluded from further analyses (see below).We analyzed eight microsatellite loci in 499 individuals of the common vole . There wO) and expected heterozygosity (HE) varied from 4.49–7.47, 0.667–0.925 and 0.768–0.916, respectively , observed heterozygosity  and this value is nearly identical after removing the Moe6 locus . There was significant differentiation between some pairs of populations . This overall pattern of genetic differentiation is consistent with that from earlier studies of the common vole [Overall population differentiation was rather low (Fulations . A Mantemon vole .K) and ΔK, obtained with STRUCTURE were not entirely consistent (K) there was support for K = 9, while from ΔK three values were supported . With K of two or three, there was a clear pattern of group membership within populations and this was reflected in the geographical distribution of the populations  to confirm the six mtDNA lineages previously described in the species , a sibling species almost identical in morphology to the common vole [Here, we substantially enhanced the geographic coverage of cytmon vole , suggestWhile European temperate species were traditionally thought to have occupied Mediterranean glacial refugia, the possibility of more northerly refugia has been promoted since the 1980s –13, 16, b sequences from the Eastern lineage, with excellent coverage of its distribution between the Balkans and Baltic Sea. This area which would have been affected by severe glacial conditions during the LGM [Carpinus betulus; [Triturus cristatus; [Ursus arctos; [We analyzed 318 cyt the LGM , 5, but betulus; ), cresteistatus; ) and bro arctos; ). The Ca arctos; , 33.To address the first question of our study, we tested several properties of the Eastern lineage, to establish if the pattern of its mitochondrial variation is consistent with its derivation from a refugium located in the vicinity of the Carpathian Mountains. The distribution of the lineage clearly supports this hypothesis, as it is present in a wide area of central Europe, with the Carpathians in the centre of its range. Moreover, we observed a continuous spread of the lineage north of the Carpathians. Three diversity indices also provide evidence in support of the hypothesis Figs  and 5. Robscurus chromosome race occurs. Therefore, this hypothesis does not seem to be supported.It may be also hypothesized that the Eastern lineage of the common vole derived from refugia located somewhere close to the Ural Mountains or the Russian Plains and spread from such distant areas to central Europe after the LGM. For instance, Deffontaine et al.  suggesteThe second purpose of our study was to establish the timing of expansion of the Eastern lineage and to determine how it relates to events which occurred during the last glaciation. Coalescent genealogy sampling in BEAST, using the molecular clock rate that was established from common vole ancient DNA , inferreM. arvalis and M. agrestis. In this study, STRUCTURE analysis with samples of M. arvalis suggested that this pattern is also evident on a wider scale in central Europe. The eastern group occurs across eastern Poland, eastern Hungary, Russia and Serbia and the western group is present in western Poland, western Hungary and the Czech Republic  were inferred. The choice of K = 2 is based on the a priori data from [ST = 0.04) and significant differentiation between only some pairs of populations. There was a similar lack of confirmation of the STRUCTURE results in the previous study within Poland [The final purpose of our study was to determine if the microsatellite differentiation that we found in our previous study of genetic variation in common voles from Poland  would beRepublic . Again, Republic . Howeverata from , and cann Poland , where SThis study is the first to examine genetic variation, using microsatellite data, in common vole populations from a wide area of central Europe. Previous studies were confined to western Europe , 31. TheK = 2 pattern on the map  and the weasel [Extensive sampling allowed us to perform an in-depth analysis of genetic diversity throughout the Eastern lineage of the common vole. Results of our study suggest that this lineage expanded from the Carpathian refugium and support an assumption that the Carpathians play an important role as a biodiversity hotspot . The horizontal axis is in thousands of years ago (kya). Posterior probabilities of basal nodes indicate support (≥ 0.95) for each of the six mtDNA lineages  and for higher level lineages. Grey bars show 95% HPD intervals for time to most recent common ancestor of each lineage.Maximum clade credibility tree for 786 cytochrome (TIF)Click here for additional data file.S2 FigBayesian skyline plot presenting demographic change in the Eastern mtDNA lineage of the common vole with the effective female population size on a log scale against time from the present to 17.5 kya.(TIF)Click here for additional data file.S3 FigK  and the mean log probability Ln(K)  results from STRUCTURE for Microtus arvalis from central Europe based on the microsatellite data.The Evanno et al.  ΔK (cont(TIF)Click here for additional data file.S4 FigMicrotus arvalis populations in central Europe, based on a Bayesian analysis of microsatellite data with K = 2. The pattern is consistent with the presence of western and eastern groups . Locations on the map match localities given in Genetic structure of erved in ). Dots s(TIF)Click here for additional data file.S5 FigSpatial Principal Component Analysis (sPCA) based on microsatellites of the common vole from central Europe. (A) Positive and negative eigenvalues which reflect potential global and local structure respectively. Only the first principal component is of sufficient magnitude to be retained. (B) Distribution of each eigenvalue according to its spatial autocorrelation and variance. ʎ1 represents the first, highest positive eigenvalue, marked in red in part A. (C) Results of a G test which tests the whole dataset in searching for global structure and (D) an L test for specifying possible local structure. The grey bars indicate the simulated values and the black diamond indicate the actual observed values. In neither case are the observed values outside the distribution of the simulated values and therefore there is no significant global or local structure.(TIF)Click here for additional data file.S6 FigTwo representations of scores obtained for each population using Spatial Principal Components Analysis (sPCA), with a grid indicating the geographical relationship of the populations. The black and white squares (or grey level variant) represent positive and negative values respectively. Only populations with ≥ 5 individuals sampled were included. (A) Size of the squares reflects their differentiation: small squares are less differentiated than large ones. (B) Different absolute values are presented in different shades of grey. Neither plot shows a distinct pattern of genetic structure among the populations.(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Tableb sequences that were used in this study are available in The full list of previously published cyt(DOCX)Click here for additional data file.S3 TableIS are given after Bonferroni correction and marked by ‘*’. Only samples with ≥ 5 individuals were used for calculations.Samples used in the previous study of Stojak et al.  are mark(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 TableThe missing data are marked by ‘-9’.(XLSX)Click here for additional data file.S6 Table(DOCX)Click here for additional data file.S7 TablePopulation labels are given according to (DOCX)Click here for additional data file.


Phoxinus are promising candidates to investigate adaptive divergence, as they inhabit both still and running waters of a variety of altitudes and climatic zones in Europe. We used landmark‐based geometric morphometric methods to quantify the level of morphological variability in Phoxinus populations from streams and lakes of Northern Italy and the Danube basin. We analyzed body shape differences of populations in the dorsal, lateral, and ventral planes, using a large array of landmarks and semilandmarks. As the species identification of Phoxinus on morphological characters is ambiguous, we used two mitochondrial genes to determine the genetic background of the samples and to ensure we are comparing homogenous groups. We have found significant body shape differences between habitats: Minnow populations inhabiting streams had a deeper body and caudal peduncle and more laterally inserted pectoral fins than minnows inhabiting lakes. We have also found significant body shape differences between genetic groups: Italian minnows had deeper bodies, deeper and shorter caudal peduncles, and a shorter and wider gape than both groups from the Danube. Our results show that the morphology of Phoxinus is highly influenced by habitat and that body shape variation between habitats was within the same range as between genetic groups. These morphological differences are possibly linked to different modes of swimming and foraging in the respective habitats and are likely results of phenotypic plasticity. However, differences in shape and interlandmark distances between the groups suggest that some (though few) morphometric characters might be useful for separating Phoxinus species.Minnows of the genus  Even though species delimitation is not an aim of the current study , geometric morphometric methods have been shown to be powerful tools for detecting speciation processes  assess morphological differentiation between genetically homogeneous minnow populations inhabiting lakes and streams; (2) assess morphological divergence between genetically different populations inhabiting similar habitats; and (3) compare the extent of morphological differences between habitats and genetic groups.22.1Fish samples were caught under the permission of the concerned state, federal, or private agencies and institutions and were in accordance with the Austrian and Italian state laws on fisheries . For Austria: River Wien—Regional Government of Vienna MA 22 (Amt der Wiener Landesregierung für Umweltschutz), Lake Grundlsee—Austrian Federal Forest Agency (Österreichische Bundesforste AG), Lake Lunz—Forestry Administration Kupelwieser . For Italy: City of Turin, Det. no. 372‐48543/2014 (Servizio Caccia e Pesca della Città Metropolitana di Torino). As our study did not include experiments on living organisms, no further permissions from federal animal welfare agencies or ethics commissions were required.2.2Phoxinus and were divided into groups according to habitat and genetic background (see below). Characteristics of all localities and groupings are summarized in Table We analyzed minnows from 10 European populations, from streams (S) and lakes (L) of Northern Italy (ITA) and the Danube basin , to minimize suffering. Subsequently, the specimens went through an ascending alcohol series and were ultimately preserved in 75% alcohol like all museum specimens. Because preservation leads to shrinkage and weight loss of the specimens, which could affect morphometry  and include already existing material complemented by recently caught fish Table . From th2.3P. lumaireul and all other examined populations to P. phoxinus. However, because of the taxonomic ambiguity within the genus Phoxinus, and uncertainty regarding morphological characteristics for species determination (see Introduction), we used mitochondrial DNA markers to ensure that we were comparing homogenous groups. Thus, three to five specimens from each population were genetically characterized for two genes, cytochrome b (cyt b) and COI. DNA was extracted from fin tissue using DNeasy Blood & Tissue Kit (Qiagen) following the manufacturer's protocol. Polymerase chain reaction (PCR) was performed with primers GluF (5′‐AACCACCGTTGTATTCAACTACAA‐3′) and ThrR (5′‐ACCTCCGATCTTCGGATTACAAGACCG‐3′) for cyt b  of PCR products was performed by LGC Genomics , with primers used for PCR. The sequences were edited by eye and aligned with MEGA 5.0 . More details on DNA extraction, PCR conditions, and sequencing are available on request from the authors.According to Kottelat and Freyhof , the Ita2.4For the genetic and morphological analysis, we compared intergroup and intragroup variations in order to justify the formation of four groups, which were then used for the geometric morphometric and statistical analyses.2.5p‐values by the number of tests performed. Allometric effects were estimated using a multivariate, pooled, within‐group regression of shape on centroid size  lateral, and ventral sides, following Herler, Lipej, and Makovec . The samSD, and also ±0.5 SD, as an estimate of the usefulness or reliability of a trait for group delimitation. We refrained from producing p‐values, as a statistically detectable significant difference of a trait among groups does not imply that the concerned trait is indeed useful as a distinguishing feature.In addition, we calculated interlandmark distances  to look for traits which may be used as distinguishing features between habitats and genetic groups. All traits were standardized for standard length. Traits on the head or caudal peduncle were also standardized for head length or caudal peduncle length, respectively. We checked whether the respective groups show overlaps of the mean value of each trait ±1 33.1p < .001) effect on shape, but explained only 1.52% of the total variation in the data . Apart from slightly larger eyes of smaller individuals, no major differences were apparent. Due to the very small fraction of explained variance, allometric effects were not further considered in the study.Body size of individual fish varied among the populations, with an average length of 53.0 ± 7.8 mm (mean ± standard deviation). According to different studies Frost, , the sizAll body shape differences between habitats and genetic groups were equally expressed in both males and females. The exception is a slightly larger ventral region of females compared with males, which in turn leads to a deeper body. However, body shape changes between habitats or genetic groups that concern the ventral region or body depth (BD) were also expressed when only males were examined. All other traits  were unaffected by sexual dimorphism. As a consequence, males and females were pooled for all analyses.The PCA revealed that some of the PCs reflected preservation artefacts (bendings) without any actual variation in body shape. As a consequence, PCs 1 and 5 of the lateral data set, PCs 2 and 6 of the dorsal data, as well as PC 2 of the ventral data were removed, as they all depicted lunate‐like or S‐shaped bendings, but no shape changes that could be attributed to effects of habitat or genetic group .3.2Genetic analysis revealed three genetic groups, consisting of (1) the Danube lake populations , 2) the Danube stream populations , and (3) all Italian populations. The genetic distances between the groups are given in Table  the DanuFor the geometric morphometric analyses, we assigned the populations to four groups  to compare genetically identical groups from different environments and genetically different groups from the same environment. As DAN L and DAN S were genetically distant, we only used ITA L and ITA S for the habitat comparisons, to ensure that differences were not attributable to genetic differences.To justify the groupings from a morphological point of view, we looked at each population individually  and generally found that intragroup variation was smaller than intergroup variation and that populations from the same habitat and genetic group share similar body shapes.3.3p < .001), but not for the dorsal side , which had no overlap between DAN L versus ITA L. On the basis of means ±0.5 SD, there were still overlaps in all traits between the habitat groups (ITA S vs. ITA L). However, the number of traits without overlap increased for DAN L versus ITA L, including predorsal length, prepelvic length, CPD, and BD. Caudal peduncle depth also showed no overlap between DAN S versus ITA S .On the basis of means ±1 4Phoxinus in the dorsal, lateral, and ventral planes, using a large array of landmarks and semilandmarks. Previous studies mostly focussed on only one side  and used a small standard set of landmarks  body in lake minnows. Even though it is seemingly paradoxical that stream minnows exhibit a less streamlined body, our findings are in accordance with their habitat preferences. In streams, minnows prefer habitats characterized by slow flowing water, for example, close to the shore Frost, . Thus, iLake minnows in our study had larger heads Figure , which m4.2P. lumaireul in the Po tributary by Kottelat (Phoxinus species.By comparing genetically divergent groups from the same habitat, we aimed to identify morphological changes in body shape which are unaffected by the environment. We found differences in overall body shape between Italian and Danube populations, with Italian minnows having deeper bodies and deeper and shorter caudal peduncles in both habitat types. Additionally, all Italian populations had longer jaws, distinctly narrower gapes and snouts, pectoral fin bases originating in a steep angle, and a shorter distance between the anus and origin of the anal fin Figures  and 5. IKottelat . Because4.3b and 5% based on COI (Table The results of the DA and the detected shape differences suggest that the extent of morphological differences between genetic groups is within the same range as between different environments Figures ; Table 4OI Table , the morOI Table . This shPhoxinus species. The few traits we have found, which may be used as distinguishing features, concern either the depth of the body or caudal peduncle, or the insertion of fins. In particular, caudal peduncle depth appears to be a good trait for separating Italian populations from the Danube populations. Nevertheless, all traits generally showed some extent of overlap and may thus only be useful in combination.However, some morphometric characters might be useful for separating None declared.KX673409–KX673485.Raw landmark coordinates, used in the geometric morphometric analysis, are provided in the Supporting Information. All genetic sequences are deposited in GenBank under accession numbers  Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.