The combination of niche modelling and landscape genetics (genomics) helps to disentangle processes that have shaped population structure in the evolutionary past and presence of species. Herein, we integrate a comprehensive genomic dataset with ecological parameters and niche modelling for the threatened Kaiser’s newt, a newt species adapted to mountain spring-ponds in Iran. Genomic analysis suggests the existence of two highly differentiated clades North and South of the Dez River. Genetic variation between the two clades (76.62%) was much greater than within clades (16.25%), suggesting that the Dez River prevented gene flow. River disconnectivity, followed by geographic distance, contributed mostly to genetic differentiation between populations. Environmental niche and landscape resistance had no significant influence. Though a significant difference between climatic niches occupied by each clade at the landscape-scale, habitat niches at the local-scale were equivalent. ‘Niche similarity analysis’ supported niche conservatism between the two clades despite the southward shift in the climatic niche of the Southern clade. Accordingly, populations of different clades may occupy different climatic niches within their ancestral niche. Our results indicate that the change of climatic conditions of geographically and genetically separated populations does not necessarily result in the shift of an ecological niche. These characteristics can be biotic or abiotic, natural or anthropogenic, making several combinations possible, such as abiotic-anthropogenic (roads and modified topography), biotic-anthropogenic (agriculture), natural-abiotic (water resources distribution) and finally natural-biotic (community composition)2. Landscape factors affecting the level of genetic differentiation among populations can be summarised as ‘geographic distance’, ‘landscape resistance’ and ‘environmental resistance3.Landscape characteristics influence functional connectivity of habitats and therefore affect migration and gene flow of individuals among populations4. As in a heterogeneous environment, gene flow may be limited such that straight-line geographic distances may actually not represent the real geographic distances underlying observed genetic distance5. Accordingly, species that require specific habitat conditions may not disperse or migrate directly to a new suitable habitat patch; instead, landscape characteristics may promote or resist individual migration. Amphibians are typically associated with wet or humid habitat patches that are interrupted by non-suitable habitat patches. For instance, dry lands can act as movement barriers for salamanders6, though gene flow sometimes occurs through matrix habitats temporarily turned into suitable habitat7. Therefore, functional connectivity describes the amount of genetic variation explained by landscape resistance, the pattern underlain by isolation by resistance (IBR)8. In addition, the balance between gene flow and selection in populations that occupy different environments determines the population genetic differentiation10. In such circumstances, adaptation to local environmental conditions will diminish the establishment success of migrants and effective gene flow will decrease. Such local adaptations lead to a pattern of isolation by environment (IBE). Isolation by environment examines the effect of environmental niche dissimilarity causing genetic differentiation11.Isolation by distance (IBD) is the correlation between the genetic distance of individuals or populations compared to their geographic distance12. In contrast, closely related lineages may tend to retain their ancestral niche-related traits over time . An intermediate pattern between these two extremes would be ‘niche constraint’  in which two lineages segregate in environmental analogues of their ancestral niche14. Taking either of these evolutionary paths depends on many factors, including the degree of geographic and environmental heterogeneity, the lineage’s genetic predisposition, and timescale14. PNC assists in forecasting species geographic responses to changes in large scale environmental conditions that might be relevant to climate change (e.g. temperature and precipitation). Under global climate change conditions, species with conserved climatic niches might be driven to extinction if they are not able to adapt to changing conditions, e.g. by shifting their range15. To retain the ancestral climatic niche in a changing environment, populations may need to shift their geographical range; a task that may be difficult or impossible in heterogeneous landscapes. Especially for amphibians, which are in general characterised for limited dispersal propensity (but see16), lineages with strongly conserved niche may remain isolated in suitable habitat patches or are at risk of extirpation if they cannot migrate.Genetic divergence at the intraspecific level is mainly the result of limited gene flow among allopatric populations or lineages. If these lineages also use different components of the environmental space, this differentiation will result in a ‘niche divergence’ patternNeurergus are found in the Near East and form a monophyletic clade of newts within the family of Salamandridae that have adapted to a mountainous habitat reproducing primarily in streams19. Up to five species are  currently recognized22, among those the distribution of Neurergus kaiseri (Kaiser’s newt) extends to Iran, where which is the most southern distribution range of the genus and all Salamandridae in Eurasia. According to the IUCN red list assessment, N. kaiseri is classified as vulnerable23; it is restricted to springs in the southern Zagros Mountains of Iran. Across its geographical range, populations of N. kaiseri are facing a heterogeneous mountainous landscape with diverse climatic conditions ranging from wet to dry that is disconnected by two main rivers, Dez and Karoon. This is in contrast to the remaining more northerly distributed species , which occupy more homogenous mountainous habitats and reproduce in streams. As a result of its southern distribution and the lack of consistent water supply of available streams, Kaiser’s newt is the only spring-pond-breeding species of the genus. In general, N. kaiseri can be characterised as a spring-pond-breeding lineage of newts that occupies suitable habitat patches in a rather heterogeneous environmental setting with limited migration between suitable patches. A first insight on the structure of N. kaiseri populations based on the mitochondrial D-loop indicated the existence of two clades, with their divergence best explained by geographic distance24. However, the structure inferred from a single locus such as the mtDNA can substantially differ from a multi-locus approach of genomic DNA, which is reflecting more accurately the true history of populations and at higher resolution. Thus, in order to obtain a more complete understanding of both genetic structure and the underlying processes shaping it, the analysis of an extensive multi-locus dataset for N. kaiseri is crucial to inform future conservation measures.Members of the genus Restriction Associated DNA sequencing (RADseq). This dataset was then used to perform a comprehensive population structure analysis, which is the basis to address the question in how far landscape characteristics have shaped and impacted the observed population structure. We hypothesised that geographic distance (IBD) and environmental niche dissimilarity (IBE) acting as an adaptation barrier, and that landscape resistance (IBR) and barriers such as rivers  would limit gene flow among populations of N. kaiseri. Specifically we explored (1) to what extent N. kaiseri clades kept the same climatic tolerance after separation, (2) whether niche divergence/conservatism accelerates adaptation and diversification within this species, and (3) which ecological factors cause the species niche to be conserved at coarse and fine scales14.We sampled thousands of loci across the nuclear genome by applying de novo assembly on reads obtained from a ddRAD protocol (modified from25), we recovered a total of 26,746 loci of an average length of 115 bp , each of them being present in at least 28 individuals of N. kaiseri from 16 localities  to perform phylogenetic analyses, 23,518 loci were recovered for a total of 2,709,284 bp.Using N. kaiseri that is consistent with the previous study on a segment of the mitochondrial DNA24, populations are split into two monophyletic groups, which are geographically separated by the Dez River  from the dataset with outgroups, we recovered a tree that is resolved for the majority of nodes Fig. . This trver Fig. . While tIn line with the phylogenetic tree, a fineStructure analysis recovered two groups corresponding to the populations North and South of the Dez River Fig. . Higher The Northern and Southern clades were also very distinct on the first axis of the PCA . The variation between clades accounted for 76.62%, while the variation between populations within the clades accounted for 16.25%. When performing the AMOVA only on individuals of the Southern clade, geographic location North or South of the Karoon River was significantly correlated with genetic differentiation (p = 0.01) explaining 45.24% of the total variance.An AMOVA analysis of the complete dataset revealed that factors such as the sampling location and the clade were explaining significant amount of genetic variation among populations  Table . ‘IsolatTo test correlations between site-by-site genetic distance matrix and its predictive factors, we used Generalised Dissimilarity Modelling (GDM). The fitted GDM explained 74% of genetic differentiation between populations. Visual examination of the genetic distances predicted from the model versus the observed values indicated that the model had reasonable predictive power Fig. . The GDMp = 0.79) and similarity of them was significantly more than expected by chance (p = 0.02). Accordingly, niche conservatism hypothesis could not be rejected at the local scale , equivalency test illustrated that the two clades occupied statistically non-equivalent climatic spaces   and receive more precipitation. The random translocation and rotation (RTR) test showed no significant signal of niche conservatism nor divergence at climatic space since the observed Multidimensional niche overlap (MO) was in the 95% of the null distribution  . The Northern clade is rather restricted at both dimensions of the climatic space, while the Southern clade covers a wide climatic niche along both PC1 and PC2 Fig. , 1–3. In02) Fig. , 4. The 02) Fig. , 5,6. PCNeurergus kaiseri) takes an outstanding position. Populations of N. kaiseri cover roughly an area of only 10000 km2 and are potentially threatened by local extinction23. Therefore, the detailed analysis of population structure is a crucial basis for the effective conservation of this species in the future. Our detailed ecological niche modelling and landscape genetics approach allows for the identification of migration paths and parameterisation of the landscape factors affecting functional connectivity between sites inhabited by Kaiser’s newts. The results from our study are essential for landscape planning in order to avoid loss of genetic diversity due to inbreeding and genetic drift27 caused by habitat fragmentation.By reaching the Southern extent of the geographic range of salamandrids in Eurasia, Kaiser’s newt . We interpret these results as a sign for a reduction, or even absence, of gene flow between the clades. Most likley, the Dez River has been acting as a barrier to gene flow. However, the co-ancestry between individuals from the Northern and Southern clades gradually increases when getting closer to the Dez River, as expected under a scenario of isolation by distance. The individuals from Tova (Northern clade), for example, show an intermediate state of co-ancestry, being more close to the Southern clade than to the Northern-most populations. Thus, it seems that the presence of a barrier to migration alone can’t explain the observed pattern of genetic variation.With our extensive dataset we could corroborate the presence of two major clades as indicated by a previous study based on mitochondrial markers28. In N. kaiseri, a southward colonization/expansion from a northern refugium, followed by the spilt of the populations in two groups due to the opening of the Dez River would be a reasonable scenario in this context. However, studies on the effect of past climatic oscillation on population structure and patterns of genetic diversity of biota in the Zagros Mountains are missing and therefore it is highly speculative to link patterns of observed genetic diversity with specific geological as well as climatic events.The present analyses also revealed some interesting patterns of genetic diversity within the two clades. Even though populations of the Southern clade are separated by relatively large geographic distances, up to 145 km, they differ at ‘only’ 20% of the SNPs, while in the Northern clade the maximal observed genetic divergence is of 34% for a maximum geographic distance of 53.5 km. Within the Northern clade, we can further delimit four groups: (i) a core group of populations that are rather homogeneous and formed of most of the northernmost localities; (ii) the population of Shahbazan, which is still closely related to the core group although geographically distant; (iii) the populations of Bozorg Ab and Vojenab, and iv) finally the population of Tova. One possible explanation for these different patterns of genetic diversity within clades might be that during Quaternary climatic oscillations, the Northern part of the Zagros mountains acted as a refugium for Kaiser’s newt, while the Southern part was colonised more recently as climatic conditions became more suitable. Similar climatic processes have been assumed for shaping diversity of brown frogs in the Near East. Here, climatic oscillations triggered post-Messinian speciation events and populations could only survived in humid refugial areas during the glacial periods in the Northern Hemisphere that resulted in cold and dry weather conditions in that area, while an expansion was only possible during the warmer and more humid interglacial periodsSalamandra salamandra) in Europe – where phylogenetic species divergence and local adaptation are realised by different sets of genes . Unravelling the general processes as well as genetic mechanisms associated with population structure of N. kaiseri at different levels will be therefore rather interesting from a general evolutionary perspective.Interestingly, the divergence within and between clades on the PCA are not correlated to the same axes see Fig. , suggestN. kaiseri, we were able to quantify the role of ecological and geographical forces, such as IBD, IBR, IBRiv, and IBE in shaping genome-wide variation of Kaiser’s newt. As a result, we found that all four factors in isolation had an impact on genetic differentiation among N. kaiseri’s populations. In line with recent findings, we infer that the spatial arrangement of populations across landscape is determined by IBD, IBR, IBRiv, and IBE and can contribute to spatial genetic divergence31. In our study, IBRiv and IBD explained 74% of the genetic variation between populations. Some variation in genetic distances of the populations could be attributed to genetic drift as a consequence of intensive harvesting that occurred at distinct times at several places.  Although mtDNA-based analysis showed that IBD is the main driver of genetic differentiation of N. kaiseri populations1, genome-wide sampled single nucleotide polymorphisms (SNP data), which are expected to be more informative and sensitive, indicated that rivers can be the main factor for disconnectivity of populations causing genetic divergence. Geographic distances between N. kaiseri populations ranged from only 0.669 km up to 201 km. We showed that up to a scale of 50 km, geographic distance showed a measurable effect on genetic variation (differentiation at 20% of the SNPs). Beyond this distance, migration of newts seems to be not possible with gene flow being completely disrupted. Such a high distance is completely unexpected for a newt species at the southern edge of the Salamandridae’s distribution and fits nicely to the changing view that salamanders and newts do have a high dispersal propensity (see33).By analysing various habitat and ecological parameters of populations of N. kaiseri follow a parapatric distribution pattern with displaying strong genetic differentiation between clades, suggesting that a physical barrier exists to prevent gene flow between populations. The apparent disjunction of the two clades is probably due to the high physical landscape heterogeneity, resulting in a hard allopatry14. Landscape barriers can influence genetic structure of populations and can lead to inbreeding or loss of genetic diversity34. The cumulative current map illustrates two key water resources, Karoon and Dez Rivers, which may act as physical barriers to migration and gene flow of newts. Since the Dez River separates populations of the Northern and Southern clades, ‘isolation by river’ hypothesis is strengthened under  this scenario. As confirmed by AMOVA analysis, there is a significant genetic differentiation between the two clades located on opposite sides of the Dez River. The physicochemical characteristics of a river can impact migration of amphibians. With an estimated discharge of 245 m3 s−1 an annual suspended sediment load of 7.5 million tonnes  for the successful establishment of dispersers between sites. Therefore, our data suggest that local adaptation probably plays a less important role in N. kaiseri and that genetic differentiation among populations is mainly the result of other underlying evolutionary processes.We showed that the niches of the two clades tend to be conserved in geographically separate ranges. GDM result supportively rejected the N. kaiseri from N. crocatus approximately 5 million years ago (mya) in the late Miocene20, Kaiser’s newt dispersed across the Zagros Mountains’ front detrital apron. The origin of stream networks in this area, including the Dez River, is suggested to have occurred ~3–3.5 mya in the late Pliocene39. N. kaiseri then extended its distribution range southwards and migrants could occupy suitable terrestrial and aquatic habitats for their reproduction. Consequently, it can be assumed that the two major clades of N. kaiseri diverged about 1–1.2 mya in the middle Pleistocene24. Overall, high physical and ecological variation may have promoted divergence of the two clades in presence of PNC. Since there were no transition zones between the ranges of the two clades, the evolution of reproductive barriers and gradual speciation seems to be likely.After the divergence of Consistent with PCA-env, results of the RTR analysis did not support niche conservatism or divergence in climatic space, strengthening the niche constraint pattern. At a local habitat scale, the two clades occupied the closest analogue of the ancestral niche, but in different climatic conditions, while expanding their ranges on opposite sides of Dez River. Niche similarity and equivalency tests suggested ‘niche constraint’ pattern of PNC by showing the differences in climatic niches between the two clades and a southward shift in niche centroid over time. Ecological specialisation in Kaiser’s newt, as in other amphibians, depends on different processes that occur at multiple spatial scales. As the species occupy similar habitats at the local-scale in alternate climatic conditions, adaptive  divergence of populations is more probable when niche shift occurs at the local habitat space.N. kaiseri raises the question of whether these two lineages should be considered as distinct species. In a recent study analysing phylogenetic relations and investigating species boundaries of species of Neurergus, Multi-Species Coalescent (MSC) models consistently split the Southern and Northern clades of N. kaiseri in two species with high support22. However, MSC models tend to ‘over-split’ lineages40, and it is then important to test species hypotheses with other approaches. At a first glance, both clades appear to be really separated based on genome-wide differentiation of SNPs, no signs of recent hybridisation or ongoing gene flow  preparing the library as follows25: 1 μg of DNA from each individual was double-digested using the PstI-HF and AclI restriction enzymes (NewEngland Biolabs) and modified Illumina adaptors with unique barcodes for each individual were ligated to obtained DNA fragments. Samples were multiplexed (pooled) and a Pippin Prep was used to select for fragments with a size around a tight range of 383 bp, based on the fragment length distribution identified using a 2200 TapeStation instrument (Agilent Technologies). Finally, enrichment PCR was performed to amplify the library using forward and reverse RAD primers. Sequencing was conducted on an Illumina Next-Seq machine at Glasgow Polyomics to generate paired-end reads 75 bp in length.For the generation and assembly of the RADseq dataset we took 1 or 2 individuals per population, resulting in a total number of 28 individuals representing 16 populations/locations of de novo using ipyrad44 and clustered using a 95% similarity threshold; base positions with a coverage >8 were called. Finally, since uneven missing data among populations can have deleterious impact on downstream analyses, loci with less than 28 individuals covered were discarded from further analysis. The assembly was performed with two different subsets: one containing all the 30 samples, and one with only the 28 samples of N. kaiseri. Indeed, as the number of RAD loci recovered is expected to decrease when the evolutionary distance between samples increases, the approach allows to maximise the amount of loci used in analyses that do not necessitate the outgroup taxa.De-multiplexed reads were assembled 45, with a GTR + GAMMA substation model, and performed 100 bootstrap replicates.We used the concatenation of the loci from the dataset with outgroups to infer a phylogenetic tree with a maximum likelihood approach. Accordingly, we used the hill-climbing algorithm implemented in RAxML46, we also investigated the genetic structure of N. kaiseri using various population genetics approaches. First, we used SNPs extracted exclusively from the kaiseri populations dataset to estimate the co-ancestry between each pair of individuals using fineRADStructure47. Then, in order to understand the relationships between the genetic groups and detect potential hybrids, we used the SNPs as variables to perform Principal Component Analyses using the ‘adegent’ R package48. More precisely, we represented the individuals in a multivariate space depending on their centred-scaled allele frequency at each SNP. We then defined Principal Components (i.e. axes maximizing the variation of the variables in the multivariate space) in order to reduce the number of dimensions, and studied the repartition of the individuals in the space defined by the PCs.As phylogenetic models can give an incomplete or even misleading representation of the populations history49) on the 18,546 SNPs, using the ‘poppr’ package50 in R. The statistical significance of the results was assessed based on 99 permutations. A similar analysis was performed on a subset including only the individuals from the Southern clade, to test for the effect of the Karoon River on genetic differentiation. The individuals were separated in two groups depending whether they were located between the Dez and Karoon Rivers  or South of the Karoon River .In order to analyse whether observed genetic variation of individuals is distributed among or within clades, we performed an Analysis of Molecular Variance , and then averaged them to get the pairwise distance between populations. We recorded geographic position of presence sites over the sampling period. Pairwise Euclidean distances corresponding to straight-line geographic distances between presence sites were estimated using the ‘vegan’ R package52. We used log-transformed geographic distance to rescale predictor variables in the same range.We estimated the pairwise genetic differentiation between localities using the SNPs from the RADseq loci. However, since the sampling size for each site is very low , widely used estimators such as 53. We created an average solar radiation map for the 1st and 15th of each month, hourly, from March to October (active season of the target species) using the Solar Radiation tool. TPI represents topographic roughness by comparing the elevation of each cell in a digital elevation model (DEM) to the mean elevation of neighbourhood cells. We prepared TPI layer using Land Facet Corridor Tool54. TWI quantifies effects of topography on hydrological processes and refers to the soil moisture content of each cell in the landscape. To consider geological effects on the possible migration of newts we calculated the Euclidian distance to conglomerate formations in the study area (i.e. Kashakan and Bakhtiari formations). Due to their high porosity these formations store water underground and might act as temporal habitat for transient newt individuals. As Kaiser’s newt is highly dependent on the forest which can provides heat shelter for migrants, we also calculated Euclidian distance to forest land cover. We included both distance layers in the modelling process , solar radiation, Topographic Position Index (TPI), Topographic Wetness Index (TWI), distance to the conglomerate formation and distance to the forest were mapped at 30 m spatial resolution in ArcGIS 10.4. NDVI quantifies vegetation density by measuring the difference between near-infrared, which is strongly reflected by the vegetation, and red light, which is absorbed by the vegetation. We used non-cloudy images of Landsat-7 ETM to measure NDVI values. Solar radiation is the power per unit area received from the sun and effects on species habitat suitability by controlling biological process55). First, for each clade we predicted the suitability value of each pixel of the study area through Maxent modelling. We then used the ‘maximum’ overlay method by overlaying the two suitability maps and giving the output cells the maximum value of the two overlapping cells. This approach permits one-way dispersal of a clade. We then quantified the resistance layer (R) as opposite of the suitability (R = 1 − S). Finally, we calculated connectivity between populations in Circuitscape 4.0.55. By assuming that individuals’ movement is limited across an area with high resistance (i.e. unsuitable area), Circuitscape estimates the density of potential dispersers through a landscape. This program revealed potential paths with the expected high density of dispersers. We used circuit distances matrix, calculated by Circuitscape, as resistance-based geographic distance. On the river raster, following Oliveira, et al.56, we assigned a value of 1 to main rivers in the study area as potential barrier of newt migration, and used Circuitscape to calculate the pairwise connectivity of populations that may be disconnected by the course of rivers.We presumed that the low mobile species passes from pixels at the landscape that meets multidimensional requirements of its Grinnelian niche , mean temperature diurnal range (Bio2), temperature seasonality (Bio4), annual precipitation (Bio12), and precipitation seasonality (Bio15) based on physiological requirements of the species. The pairwise correlation between these five climatic variables was ≤0.72. Values of bioclim data were then extracted at each presence point to create an environmental dissimilarity matrix using ‘ecodist’ R package58.We created and mapped 19 bioclim layers using ‘dismo’ R package60.We considered geographic distance, landscape resistance, river disconnectivity, and environmental dissimilarity at presence sites as the affecting variables on genetic variation. The hypothesis of isolation of populations by each distance matrix was separately assessed using Mantel tests in R. Significant variables were then accounted for Generalised Dissimilarity Modelling (GDM) as a matrix regression to estimate the non-linear relationship between the genomic distance of populations and its driversN. kaiseri that belonged to identified clades in the previous step to examine PNC in Kaiser’s newt at landscape and local scales following Willis and Whittaker61. The local habitat variables were NDVI, solar radiation, TPI, TWI, distance to the conglomerate formation and distance to forest, as briefly described above. Species occurrences were then projected onto the gridded environmental space of the first two PCs calculated with the local habitat variables62. In addition, the five bioclim variables  were used to calculate the climatic niche similarity of the two clades at the landscape-scale. For this purpose, we applied PCA-env approach62 which characterised the climatic space at the two first principal components of the bioclimatic values for the entire study area per pixel. Thereafter, the probability of ecological niche evolution between these two clades was assessed based on the random translocation and rotation (RTR) approach following Nunes and Pearson63. RTR is a recently developed approach based on the Multidimensional Overlap (MO) metric to test the significance of niche differentiation. The MO metric is similar to BIOCLIM, a presence-only approach that takes into account species’ occurrences to delimit a climate envelope. It ranges between 0 (no niche overlap) and 1 (complete niche overlap). By maintaining the spatial configuration of occurrences, the RTR Null model calculates MO, niche overlap metric for thousands of replicates while randomly translocates and rotates the position of occurrences across the study region. The observed MO is finally compared to the distribution of MO values generated by the Null model. The RTR test also showed a great performance when dealing with rare, range-restricted species. Since RTR is suited for macro spatial scales and is highly dependent on relative occurrence area (ROA), we extended the study region to an extent in which 10,000 RTR replicates were possible without replacement.We used 28 trimmed records of Dataset 1


Physospermum cornubiense in view of translocation measures across its Italian range.Due to habitat loss and fragmentation, numerous forest species are subject to severe population decline. Investigating variation in genetic diversity, phenotypic plasticity and local adaptation should be a prerequisite for implementing conservation actions. This study aimed to explore these aspects in ten fragmented populations of Metcalfa pruinosa and soil parameters). We measured vegetative and reproductive traits in the field and analysed the genetic population structure using ISSR markers (STRUCTURE and AMOVA). We then estimated the neutral (FST) and quantitative (PST) genetic differentiation of populations.For each population we collected environmental data on landscape  and local conditions , number of flowering adults  and inflorescence size (range: 5.0–8.4 cm) were positively related to Mg soil content. Populations’ gene diversity was moderate (Nei-H = 0.071–0.1316); STRUCTURE analysis identified five different clusters and three main geographic groups: upper, lower, and Apennine/Western Po plain. Fragmentation did not have an influence on the local adaptation of populations, which for all measured traits showed PThe variation of phenotypic traits across sites was attributed to plastic response rather than local adaptation. Plant translocation from suitable source populations to endangered ones should particularly take into account provenance according to identified genetic clusters and specific soil factors. In recent years, human-induced habitat loss and fragmentation have caused severe reductions in biodiversity so that many formerly widespread plant species have become rare and are now persisting in isolated populations . PreviouThe reduced link between populations following habitat fragmentation is frequently associated with isolation by distance, isolation by genetic drift, and adaptation to different environments  and reproductive success . It is oThe restoration of local populations of wide-ranging species and the subsequent selection of potential sources for population reintroduction or reinforcement may be problematic due to the genetic structure and the reduced intra-population genetic variation of such populations  that areST) is widely used to estimate genetic differentiation with neutral loci  by analysing variance in allele frequency (ST) is an estimate of quantitative genetic differentiation  using quantitative trait measurements within populations , obtained in common garden experiments, but influenced by environment (ST and FST can be used to estimate the relative importance of genetic processes and selection: (a) PST = FST indicates that divergence is compatible with a scenario of genetic drift; (b) PST > FST indicates directional selection  among populations; (c) PST < FST indicates that the same phenotypes are favoured in different populations due to stabilising selection.The quantification of population differentiation based on neutral genetic markers and quantitative traits can highlight the relative role of evolutionary processes such as natural selection, genetic drift and gene flow for patterns of local adaptation . Fixatiorequency . In contironment . The relPhysospermum cornubiense (L.) DC. a herb, which is rare due to habitat loss and deterioration in the fragmented woodlands of the Po plain . Possible restoration actions (reintroduction or translocation) for P. cornubiense will need to consider a number of viable populations as propagule donors within the species’ historical range to (re)create new or reinforced populations to increase the range and reduce the risk of extinction.In this study, we explored phenotypic plasticity, the divergence in quantitative traits  and the patterns of genetic variation at the population level of the species P. cornubiense, we quantified the genetic and phenotypic variation of populations in the Italian portion of the species’ range. We hypothesised that historical habitat loss and fragmentation have influenced genetic structure and local adaptation. Additionally, the long-term survival of some populations may be threatened by the loss of genetic diversity and declines in reproductive fitness. To address these questions, we used complementary approaches: (a) we measured a set of morphological traits to assess phenotypic population differentiation in the field, correlating local and landscape conditions with the population characteristics; (b) we investigated genetic diversity and genetic differentiation among populations by examining FST values; (c) we assessed the patterns of local adaptation, in terms of level of divergence of quantitative traits, by applying a PST approach.In order to inform restoration efforts for Physospermum cornubiense (L.) DC. is a rhizomatous perennial (hemicryptophyte) herb, belonging to the Apiaceae, in which it represents a relatively isolated taxon compared with other genera of the family (http://www.brc.ac.uk/plantatlas/). Its chromosome number (2n) ranges from 2n = 14 to 2n = 22 , which are well known to disperse pollen over medium to long distances . Here, P. cornubinese populations were found to grow in shaded or semi-shaded conditions and are mainly found in oaks (Quercus petraea (Matt.) Liebl. and Q. robur L.) or chestnut woods (Castanea sativa Miller) mixed forest, preferring moderately moist soils with low pH , August and September (beginning) 2013. The data collection included: (a)abundance: counting of individuals, total for the population (Pop_sz) and per age class including seedling, juvenile, non-flowering adult and flowering adult. Because of the difficulty of distinguishing seedling and juvenile stages, these two classes were grouped in the analyses. (b)vegetative traits: plant height , measured from the ground to the highest growing point of the main branch; lateral spread , measured as the maximum diameter of the plant; number of leaves (N_leav). (c)reproductive traits: maximum size of a composite umbel ; total number of composite umbels (Comp_umb); total number of simple umbels (Simp_umb); seed mass , measured with a precision balance (0.0001 g), based on ten randomly collected seeds per individual.P. cornubiense populations, we collected data on landscape variables (LAND) and local variables (LOC)  habitat fragmentation index –this index is based on the distance between populations, perforation (formation of holes in habitat patches), dissection (presence of narrow linear corridors) and shrinkage (information on habitat shape); see y = 1, n = 0); (d) presence of the herbivorous Metcalfa pruinosa Say, 1830, an invasive polyphagous insect (Homoptera) native to North America that colonised Europe from 1979 onwards ; (e) soil characteristics .To investigate the contribution of environmental factors to the differentiation of es (LOC) . The LAN2 and the solution was placed on a shaker for 2 h, before measuring pH with a standard glass electrode. The total contents of carbon (C) and nitrogen (N) were determined in % using an elemental analyser . The cations calcium (Ca), potassium (K) and magnesium (Mg) as well as plant available phosphorus (P) were extracted with ammonium lactate. The concentrations of the three cations were measured with Atomic Absorption Spectroscopy , whereas P was determined by flow injection analysis . The laboratory measurements followed the methods described by Regarding soil characteristics, soil samples were collected and analysed applying standard techniques , each selected with a random starting point and a randomly selected direction, covering the whole population range. All sampled individuals were established adults; plant material (leaves) was collected at a reciprocal distance of at least 10 m. Genomic DNA was extracted from the dried leaves using the EuroGold Plant DNA Mini Kit  following the manufacturer’s instructions. The quantity and quality of the extracted DNA were determined by absorbance measurements .We used ten inter-simple sequence repeat (ISSR) molecular markers based on a technique involving the use of microsatellite sequences as primers in a PCR analysis to generate dominant multilocus markers. ISSR markers combine the advantages of AFLP and microsatellites (SSRs): they are highly polymorphic as they use universal primers and are useful for organisms for which genetic information is scarce . During ®, LIZ1200, Applied Biosystems, Foster City, CA, USA) for capillary electrophoresis using an ABI PRISM 3100 Genetic Analyzer . Analysis of the results was performed using the software Gene Mapper 4.0 and Raw Geno 2.0 . Then, aliquots of 2 µL of ISSR PCR products were suspended in 9.75 µL of deionised formamide and with 0.25 µL of size standard , Nei’s genetic diversity H_Nei; ; H, and P. cornubiense at the landscape level was inferred and individuals assigned to geographical ancestry populations by using the software STRUCTURE v. 2.3.4., which provides the use of dominant markers such as ISSRs  were performed with an admixture model at 100,000 runs of burnin period and 500,000 Markov chain Monte Carlo iterations. Before the end of the burnin period, we checked for FST and alpha plots to be sure that the summary statistics had a stable trend. To determine the number of clusters we used ΔK, the second-order rate of change in lnP(X—K), for successive values of K  was carried out using the Genalex v. 6.5  in orderant data .P. cornubiense populations, comparisons of quantitative traits and genetic differentiation among populations were performed. According to ST estimates are not available, PST can be justified as a substitute. According to divergence across populations of species that are less amenable for proper QSTestimation may still be of considerable evolutionary or conservation interest” and it can be assessed by using PST. In our study, we chose PST index since the seeds of P. cornubiense were difficult to germinate and some populations had a very small number of flowering individuals and consequently did not produce an adequate number of seeds that could be used for common garden experiments.To estimate the role of local adaptation through natural selection in the ST values were calculated for each trait (and for an average PST), using the following formula: PST = cσ2B∕(cσ2B + 2h2σ2W). In this formula, σ2B and h2 expresses the heritability (the proportion of phenotypic variance that is due to additive genetic effects); the scalar c expresses the proportion of the total variance that is presumed to be due to additive genetic variance across populations  and h2 (heritability) in the wild, for a set of traits . Therefore, a sensitivity analysis of the PST–FST comparisons, starting from the null assumption of c = h2, was carried out, accounting for the lower limit of the 95% CI of FST.For each population pair, pairwise Pulations . The prof traits . Consequχ2 statistics (contingency table). To analyse the correlation between the environmental factors  with vegetative and reproductive traits of P. cornubiense populations, a generalised linear mixed model (glmm) with a normal or Poisson or binomial distribution (depending on the variable) was carried out. To analyse the correlation between LAND and LOC and demographic and genetic variables of populations (constant variables), a generalised linear model (glm) with Gaussian distribution was carried out. We performed corrections for multiple tests by using the Holm’s method  and Nei’s genetic distance (H_Nei) with demographic parameters  were also investigated by performing Pearson’s correlation analysis, correcting for multiple testing.ST), genetic differentiation (FST), geographic distances (GEO) and environmental  variability were related, we calculated pairwise correlations between the correspondent distance matrices, applying Mantel tests (ST) were also carried out. We then performed corrections for multiple tests by using the Holm’s method ; all three matrices were retained to perform successive separate tests. To assess whether levels of quantitative genetic differentiation in wild populations . Mg and Ca contents were also positively correlated with pH . Total N was very low in the GRAF population but relatively high in FAGB, with proportions of 0.09% and 0.50%, respectively . In particular, the percentage of seedlings/juvenile plants was lowest in TO (6.9%) and highest in MCA (43.3%); the proportion of flowering adults was lowest in CUS (4.3%) and highest in TO (64.1%).As regards to demographic data, the number of individuals in the populations ranged from 16 in SC to 655 in TO. The proportions of individuals of different age classes of The differences between populations, with respect to their vegetative vigour and reproductive fitness components, are shown in G = 18.204; p < 0.001) and population size .The glmm and glm, after corrections for multiple tests by using the Holm’s method, revealed that soil factors and habitat characteristics were correlated with population abundance and traits . In partNo significant relationships were detected by glmm analyses.P. cornubiense populations produced a total of 171 scorable peaks from about 50 bp to 1,000 bp. The percentage of polymorphic loci ranged from 22.81% in MCB to 61.99% in GRAF while Nei’s genetic diversity varied from 0.071 in MCB to 0.1316 in CUS; the mean H Nei at the species level was 0.109  and performed at the individual level  showed both low genetic diversity and/or reproductive fitness. The relationship among the al level .K = 5 [lnP(D)], indicating that populations of P. cornubiense are subdivided into four different genetic geographic groups  upper Po plain ; (b) lower Po plain ; and (c) Apennine/Western Po plain .STRUCTURE analysis estimated the highest mean log likelihood at c groups ; File S1F-statistics was FST = 0.365. Pairwise FST ranged from 0.101 (FAGA vs. FAGB) to 0.628 (MCB vs. SC). AMOVA analysis showed that 66.1%  of the total genetic variation is attributed to individuals within populations, while 31.2%  and 2.7%  are due to differences among populations and between regions, respectively. The ΦST value estimated with AMOVA was 0.339.The overall genetic differentiation among populations according to Wright’s ST) and geographic distance did not give a significant result following corrections for multiple tests by using the Holm’s method  was 0.171 (95% CI [0.137–0.205]). This value was significantly lower than FST  as also shown in the PST–FST comparison function of c∕h2  of P. cornubiense. No patterns were found.Applying a Mantel test to Fmatrices  we invesP. cornubiense in the Po plain region influenced the genetic structure of the populations but not their local adaptation. Therefore, differences in the phenotypic traits across sites could be due to a plastic response of populations to local environmental conditions. Despite no overall correlation was found between genetic diversity and population size and between genetic diversity and reproductive fitness, two among the smallest populations (SC and MB) showed low genetic diversity and low reproductive fitness; therefore, their long-term survival is compromised and may require restoration measures.Our results showed that historical habitat loss and deterioration across the range of P. cornubiense exhibited morphological variation in response to Mg content in the soil. Increasing Mg content was positively correlated with the number of flowering adults and with population size. Soil characteristics had an influence in shaping the demographic patterns and the traits of the studied populations. Populations of Petagnaea gussonei (Spreng.) Rauschert , and Apennine/Western Po plain and may best be explained by historical genetic drift. The very small and endangered SC population likely originated from the same cluster of CUS and GRAF but it is probably a sister population to GRAF . The SC population has probably been exposed to reduction and deterioration of habitat  causing separation between adjacent forest patches. Subsequently, the population has been subject to isolation within a smaller patch and with a reduction in population size and genetic divergence without clear evidence of an inbreeding depression. However, we found some low values of H Nei in the smallest population (SC), which also did not produce any inflorescences and consequently, seeds. The origin of such genetic clusters is probably a consequence of isolation due to habitat loss and fragmentation combined with population differentiation, indicating scarce gene flow. Processes of isolation by distance occur when gene flow and gene drift are in equilibrium and when gene flow decreases with distance among locations  may have reduced the effects of genetic erosion. Indeed, under unstable population sizes, perennial species may exhibit low levels of biparental inbreeding and reduced drift due to their longevity and overlapping generations  with high inbreeding and genetic drift is recognised that it depresses population fitness and viability in recently diverged populations  supporting genetic divergence by isolation  solation  and receST, total or for single traits) with the environmental components  of populations, confirming a scarcity of evidence for local adaptation. In any case, though PST is can be used as an analogue of QST, results derived from such an index must be considered as a first line of investigation and interpreted with caution since it can be influenced by environmental variability (abiotic conditions) that occurs across sites of sampled populations , urgent measures should be applied, carrying out plant translocation from locally adapted seed source populations in order to increase their population size as well as their genetic diversity. The candidate populations to be used in the rescuing of SC are CUS and GRAF populations that belong to a very close cluster of SC. However, the use of GRAF as source population should be limited due to its modest population size. On the other hand, the small population MCB could be restored with individuals coming from the close large population of MCA.The adaptation of populations to local environmental factors can provide key information to conservation practitioners in restoration projects , such asin situ) populations may allow outcrossing, preserving genetic diversity and favouring population size (Translocation of propagules (both via seed or from vegetative reproduction) from existing (ion size . In the in situ trials aiming at investigating the influence of Mg content on the species’ fitness are suggested.In our study, the analysis of soil factors highlighted a positive relationship between population fitness and levels of Mg. Therefore, specific ex situ and P. cornubiense, causing a genetic drift in some populations. No phenotypic differentiation due to local adaptation was ascertained, so the variation of phenotypic traits across sites was attributed to plastic response of local populations. Although there are at present no signs of imminent extinction of this plant species across the Po plain, there is evidence that habitat loss and fragmentation have induced a drop in fitness and probably in the migration ability of individuals between forest patches. These factors may lead to future extinction events at local or regional scales if restoration action does not occur. Future restoration action must offset the continuous genetic erosion that this interesting forest herb species suffers from, by translocating suitable plant material into the at-risk populations.In this work we try to link genetic differentiation, local adaptation and phenotypic plasticity in populations of a herb forest species needing conservation action. Particularly, the extensive forest fragmentation due to habitat loss that occurred in historical times across the biogeographic province of the Po plain that had an effect on the genetic and demographic structure of the forest herb species 10.7717/peerj.4929/supp-1Table S1Click here for additional data file.10.7717/peerj.4929/supp-2Table S2Click here for additional data file.10.7717/peerj.4929/supp-3Table S3Click here for additional data file.10.7717/peerj.4929/supp-4Table S4Click here for additional data file.10.7717/peerj.4929/supp-5Data S1Click here for additional data file.10.7717/peerj.4929/supp-6Data S2Click here for additional data file.10.7717/peerj.4929/supp-7File S1Click here for additional data file.


Anoplophora glabripennis, the Asian long-horned beetle (ALB), is highly polyphagous and can colonize a wide range of broadleaved host trees causing significant economic damage. For this reason, it is considered a quarantine pest in Europe and North America. Although the global spread of ALB has been depicted recently, no comprehensive studies exist on the genetic pattern of populations’ establishment and dynamics at fine-scale (i.e. within invasive outbreaks), before eradication measures are applied. This information may, however, be particularly important for an efficient management and control of invasive pests. Here, we characterized population genetic diversity and patterns of spread of ALB within and among the four outbreaks detected in Switzerland between 2011 and 2015. For this, we genotyped 223 specimens at 15 nuclear microsatellite loci and conducted specific population-based analyses. Our study shows: (1) At least three independent introductions and a, human-mediated, secondary dispersal event leading to the four outbreaks in the country; (2) An overall low intra-population genetic diversity in the viable and several years active invasive populations; (3) A colonization of single trees by homogeneous ALB genotypes; And (4) an establishment of populations several generations prior to its official discovery.The xylophagous cerambycid  Insights into the species biology and genetic structure of newly established populations, as well as reconstruction of introduction events and invasion routes have the potential to define the factors underlying the invasion success and to outline the pattern of local pests’ outbreaks . This information can be particularly helpful for developing successful management strategies to prevent new invasions and control new outbreaks.The intensification of global trade and worldwide mobility has humanitarian and economic benefits, but it also involves potential challenges for native ecosystems due to the introduction of alien species. In recent years, an increasing number of invasive pests and pathogens have been reported in ecosystems worldwideColeoptera, Cerambycidae) Anoplophora glabripennis (Motschulsky) is a well-known invasive insect in Europe, in North America, and in artificial plantations in East Asia5. ALB can attack a wide range of deciduous trees and survive in cut wood. Trace-back investigations have shown that introductions into Europe and North America occurred via infested wooden packing material from East Asia6. In China, the beetle presumably co-evolved in its native range with relict plants like Eucommia ulmoides7 and, due to reforestation programs in the 1980s, spread as a pest through artificial forests  that were frequently established with tree species introduced from Europe . In invaded areas, the favourite host trees are species in the genera Aesculus, Acer, Betula, Fraxinus, Platanus, Salix, and Ulmus5. Female beetles can produce 30–60 (up to 200) eggs annually, which they oviposit in the cambial region of the host trees12. Although ALB adults, according to laboratory experiments14, have the potential to fly 14 km, in open environments they fly only 1–3 km during their life span, and when suitable host trees are available most ALB remain in proximity (hundreds of meters) to the tree from which they emerged15. Larvae feeding on the phloem and xylem tissues, before emerging as young adults from the trees (after 1–2 years), cause the most damage by disrupting the vascular system of the tree16.The xylophagous Asian long-horned beetle  in a private garden in the remote village of Brünisried, Canton Fribourg17. The source of the infestation could not be determined. During a second survey and sampling in 2013, the presence of exit holes suggested that at least one generation of ALB developed and emerged in Brünisried17. In 2012, a new ALB outbreak was found in the industrial area of the city of Winterthur, Canton Zurich9. The pest was detected on sycamore maples with new and old exit holes within three infestation spots situated about 250 m apart9. In 2014, a large outbreak was detected in Marly, an industrial city situated about 10 km away from the first detected population in Brünisried18. In Marly, exit holes were observed on several dozens of trees of Acer spp. and Aesculus hippocastanum, and ALB was found in all development stages . The infestation area in Marly included two spots (North West and South East), at about 1.5 km distance17. The fourth and last Swiss population was detected in Berikon (Canton Aargau) in 201519. A female beetle with fertilized eggs was initially found on a construction site. Later on, a sycamore maple with beetles, egg depositions and exit holes was detected 240 m away from the first finding. Because ALB is an A1 quarantine organism (EPPO 2017), all trees after sampling within outbreaks were eliminated by chipping and/or burning9. ALB was also found several times in wooden packaging material at the border of the country and in industrial sites within the country. The relatedness of these beetles to the four outbreaks remained unclear9 until the present study.Here, we aimed to investigate the invasion genetics of ALB in the four outbreaks detected in Switzerland between 2011 and 2015 , markers to explore the invasion genetics in the four ALB populations described above and in single ALB findings. The SSR markers previously developed specifically for ALB enabled to assess genetic diversity within and among invasive populations and offered a great potential to reconstruct history and the pathways of beetles’ spread using Approximate Bayesian computation analysisTherefore, with an emphasis on genetic population structure and history of local spread, we addressed the following questions: (1) How many introduction events in Switzerland led to the four outbreaks? (2) What is the genetic relatedness of the beetles in the outbreaks and single findings? (3) How genetically diverse and structured are the invasive populations?A. glabripennis. However, three different COXI haplotypes were observed: specimens from the geographically close outbreaks of Marly and Brünisried showed the COXI haplotype C, whereas specimens from Winterthur and Berikon the haplotype A .Locus-specific deviation from HWE and significant correlation between allele frequencies were not consistent among populations  was observed between all populations pairs, apart from Brünisried and Marly  was 1.5-fold higher than between the geographically more distant (~ 10 km apart) Marly #1 and Brünisried (FST_Ma1Br = 0.08).The population structure analyses described above suggests that populations in Marly and Brünisried were clearly interconnected and substantially differ from the other two Swiss populations  and the Structure results, six different scenarios of the demographic history were tested for the ABC analysis , failed to establish new populations.15. Results of our genetic population structure analysis confirm the field observations. In all populations, only one or maximum two genetic clusters were found on a single tree. Remarkably, riparian broadleaf stands that are potentially attractive for the polyphagous ALB exist in a proximity of 140 m to the first infested area (Marly #1). However, the second population (Marly #2) was established at a distance of about 1.3 km from the first, along a main road, which could be explained by local human-mediated transportation (e.g. hitch-hiking).The strong population differentiation coupled with deficit of heterozygotes suggests no gene flow between the geographically distant populations, which is expected considering the limited natural dispersal of ALB. As already observed in open environment, when suitable host trees are available most ALBs remain in proximity to the tree from which they emerged17, that would support the oldest origin of the population in Marly. The genotypes with admixed assignments indicate that beetles had probably several generations for breeding prior to sampling. The multiple genetic clusters in the oldest population may be also the result of introductions from a diverse population, presumably in South Korea as suggested in the study of Javal, et al.22. The presence in the stepwise population of Brünisried of a cluster that was not detected in the initial population of Marly, might be explained either by genetic drift that had occurred, or by the introduction of specimens from another, unidentified population. However, considering that i) Brünisried is a relatively small and remote village and ii) there is no evidence of such an unknown population in the surrounding region, we think that the last explanation is unlikely. As expected, the founder population (Marly #1) was most likely of limited effective size, owing to a transitory bottleneck. According to the supported ABC scenario and the estimated parameters, this first population experienced a lag invasion phase, i.e. a period of low growth and reduced effective size24. Intriguingly, this period was probably twice as long in the initial population as in the step-wise populations. It could be that during this period natural selection acted in favour of the phenotypes which performed best in the new environment. Thus, the beetles that established subsequent populations were already better adapted than those that initially arrived. Despite a possible uncertainty in the specific quantitative results of our ABC analysis, it shows that all three populations with common origin increased their effective sizes in about the same time period and, given also to the high fecundity of female beetle , had the potential to restore populations of up to a few thousands specimens. Although, field observations during sampling suggest that the populations in Marly and Bruenisried were less abundant in reality.Reconstruction of the invasion history of the interconnected populations of Marly and Brünisried with Approximate Bayesian Computation (ABC) suggests that initially up to two hundred ALB individuals arrived in the industrial area of Marly . ALB genotypes originating from a single tree were mostly genetically homogeneous and belonged to the same genetic cluster. However, our analyses also revealed an efficient secondary dispersal of ALB within Switzerland, most likely by human activity. Consequently, when a new outbreak of an invasive pest is detected, intensive monitoring should also target trees along the main transportation and communication routes  near the outbreak. Remarkably, the largest Swiss population (Winterthur) was genetically homogeneous but have been successfully active by several years before eradication. It seems that low genetic diversity does not compromise the ability of ALB to become established outside its native range.9.A total of 223 ALB specimens were sampled at different development stages and analysed in this study Table . Most of25. PCR products were purified with Illustra™ ExoProStar™ mix , following the manufacturer’s instructions. Sequencing reactions were performed at both strands separately, using the Big Dye Terminator sequencing kit , on an ABI 3130 Genetic Analyzer at Swiss Federal Research Institute WSL . The obtained sequences were edited manually using GeneStudio (TM) Professional Edition 2.1.2.3 and analysed with CLC Main Workbench 7. The sequences were then BLAST searched against the non-redundant nucleotide collections of the NCBI database (https://www.ncbi.nlm.nih.gov/). A COXI haplotype was assigned when match similarity of the BLAST search was greater than 98%.Until DNA extraction, the ALB specimens were preserved in absolute ethanol at −20 °C. DNA extraction was performed using the DNeasy Blood & Tissue Kit , following the manufacturer’s protocol. DNA was extracted from one leg (adults), the head  or entire eggs. The barcoding region of the mitochondrial gene cytochrome oxidase I (COXI) was amplified using the standard primer pair HCO2198 and LCO1490et al.26. Amplifications were multiplexed in six reactions as follows: (1) ALB38/ALB77, (2) ALB10/ALB53/ALB59, (3) ALB9/ALB14, (4) ALB15/ALB35/ALB44, (5) ALB40/ALB24, and (6) ALB43/ALB19/ALB30). Multiplexed PCR reactions were performed using the Multiplex PCR Kit (Qiagen), as described by Javal, et al.22. All PCR amplifications were performed on a Veriti 96-Well Fast Thermal Cycler (Applied Biosystems), and PCR products were subsequently denatured by formamide before fragment sizing on ABI PRISM 3500 . Allele sizes were scored with the GeneMapper v5 software (Applied Biosystems). Ambiguous loci and genotypes that could not be reliably scored were re-amplified and re-analysed.Samples were genotyped at 15 microsatellite loci developed by Carter, 27, the number of private alleles, the evenness of multilocus genotypes28, fixation indices, and the deviation from Hardy-Weinberg equilibrium29 were estimated using Arlequin 3.5.2.130 and the R-package poppr v 2.3.031. Pair-wise linkage disequilibrium (LD) between loci was tested with the log-likelihood ratio using a Markov chain algorithm (default parameters), as implemented in the web version of Genepop 4.232. The statistical significance of LD was inferred using 1000 permutations and a sequential Bonferroni correction with α = 0.05. Genetic differentiation among populations was assessed by calculating pairwise FST-values29 and corresponding P values (α = 0.05) with Arlequin 3.5.2.1.For population genetics analyses in the four outbreaks in Switzerland , each outbreak was considered as a population. In each ALB population, the number of alleles per SSR locus, the observed and expected heterozygosityadegenet33. First, multilocus genetic data were transformed into principal components (PCs) and the optimal number of PCs was determined with cross-validation33. Thereafter, ALB groups were predefined according to the origin of the specimens . Samples were then plotted along the first two discriminant functions of the analysed PCs.Genetic relatedness of the ALB specimens among populations as well as single findings was studied with a multivariate clustering method, i.e. discriminant analysis of principle components (DAPC), implemented in the R-package et al.34, by (1) considering the maximal mean and small standard deviation of the posterior probability of K among runs35, (2) applying ΔK methods36, using Structure Harvester37, and (3) analysing the alterations of individual assignment probabilities with increasing K . Average assignment probabilities of specimens to the genetic clusters were computed with Clumpp 1.1.238 using the greedy algorithm for K ≥ 10 and visualized using Distruct 1.139 and R graphic functions. Spatial distribution of the defined genetic clusters and their probabilistical assignments in populations were mapped with ArcGis 10.4.1.The population genetic structure of the four outbreaks was analysed with the Bayesian model-based cluster analysis, as implemented in STRUCTURE v 2.3.4. ALB specimens were probabilistically assigned to genetic clusters using allele frequencies at each locus. No prior geographic information was used (LOCPRIOR = 0 option), and the admixture ancestral model with correlated allele frequencies was applied. Analyses were run with 200,000 burn-in iterations, followed by the same number of iterations for Markov chain Monte Carlo (MCMC) in ten independent runs for each number of clusters (K) from 1 to 20. The most likely K was determined, as suggested in Janes, 40. For this analysis, the two infestation areas (North West and South East spots) in Marly were considered as different populations, that is Marly #1  and Marly #2 , geographic coordinates for the rest of 14 individuals in Marly were not recorded, thus they were excluded from the analysis. The demographic scenario that best explained the observed genetic diversity in outbreaks was inferred from two analysis steps (for details see Supplementary). First, the most likely sequences of demographic events and defined topology of ALB populations’ spread were tested. In this step, we used a broad frame of prior population parameters to compute simulated data-sets. Then, considering information from the field observations we restricted the first event of the ALB arriving to 10 generations ago and defined the time of each demographic event in a likelihood scenario. In both steps, the ABC analysis was conducted following Cornuet, et al.41 and included the following steps: (1) assume realistic competing scenarios considering structure, FST ratio between sampled populations, and field observations; (2) simulate 1 × 106 pseudo-observed datasets (PODs) for each scenario and compute correspondent summary statistics; (3) evaluate posterior probabilities of each scenario on 1% PODs with the closest summary statistic to the observed dataset and identify the best scenario in 95% confidence interval; (4) assess the confidence level of the chosen scenario as the proportion of times that this scenario was falsely rejected (type-I error) or accepted (type-II error); (5) evaluate the goodness-of-fit of the selected scenario to the data.The demographic history of the ALB spread in the two related outbreaks of Marly and Brünisried (see Results) was investigated using a coalescent approximate Bayesian computation approach implemented in DIYABC v.2.1.0The article does not contain any studies with human participants or vertebrate animals.Supplementary information


Pterois volitans, into waters off the US East Coast, Gulf of Mexico, and Caribbean Sea provides a natural system to study rapid range expansion in an invasive marine fish with high dispersal capabilities. We report results from 12,759 single nucleotide polymorphism loci sequenced by restriction enzyme‐associated DNA sequencing for nine P. volitans sampling areas in the invaded range, including Florida and other sites throughout the Caribbean, as well as mitochondrial control region D‐loop data. Analyses revealed low to no spatially explicit metapopulation genetic structure, which is partly consistent with previous finding of little structure within ocean basins, but partly divergent from initial reports of between‐basin structure. Genetic diversity, however, was not homogeneous across all sampled sites. Patterns of genetic diversity correlate with invasion pathway. Observed heterozygosity, averaged across all loci within a population, decreases with distance from Florida while expected heterozygosity is mostly constant in sampled populations, indicating population genetic disequilibrium correlated with distance from the point of invasion. Using an FST outlier analysis and a Bayesian environmental correlation analysis, we identified 256 and 616 loci, respectively, that could be experiencing selection or genetic drift. Of these, 24 loci were shared between the two methods.Range expansions driven by global change and species invasions may have significant genomic, evolutionary, and ecological implications. During range expansions, strong genetic drift characterized by repeated founder events can result in decreased genetic diversity with increased distance from the center of the historic range, or the point of invasion. The invasion of the Indo‐Pacific lionfish,  Recent FST analyses that may be under drift or under selection, potentially playing adaptive roles in certain lionfish populations.This study presents genome‐wide SNP data for the invasive lionfish collected throughout the Caribbean, using 12,759 loci across nine populations. Data are analyzed from a range expansion perspective, not just a population structure perspective, identifying changes in genetic diversity with distance from the point of invasion. We test the hypothesis that lionfish range expansion is characterized by repeated founder effects through space and time at the moving range edge, leading to decreased genetic diversity  with increased distance from the point of introduction in southeastern Florida. We predicted that signals of allele surfing would be detectable in the SNP data, in line with the theoretical predictions outlined above. Counter to these predictions, patterns of decreased diversity in the form of decreased major allele frequency or allelic richness were not observed in the data. However, decreases in average observed heterozygosity were observed, indicating higher levels of nonequilibrium population genetic dynamics near the range edge, with more central populations tending toward an equilibrium state. This may occur as populations become more established and the invasion front propagates forward. We also identify outlier loci in both Bayesian and 22.1Pterois volitans individuals were collected from nine Caribbean sites for genomic analysis , Belize, Honduras, and Trinidad were collected by divers throughout 2013, and tissue subsamples were archived in the US National Oceanic and Atmospheric Administration (NOAA) Beaufort Laboratory, Beaufort, North Carolina. Samples from Trinidad were only used in mitochondrial analyses due to DNA quality requirements for genomic analyses. All other sites were used for both mitochondrial and RAD‐sequencing analysis. Sections of muscle tissue from archived filets were subsampled at NOAA. Fish were identified to species when possible through meristics  at the collection site and later confirmed through molecular barcoding. If provided by collectors, latitude and longitude, depth, date of collection, sex, and standard or total length for each sample are given in Supporting Information Appendix s Figure . AdditioTo estimate the age of each sampled individual, and therefore the likely time of recruitment of the individuals used in this study, we calculated age from total length using a von Bertalanffy growth curve . Genome‐wide SNP data were generated for a subset of 120 samples (Table Polymerase chain reactions (PCRs) were performed targeting the mitochondrial control region D‐loop with primers LionfishA‐H (5′‐CCATCTTAACATCTTCAG TG‐3′) and LionfishB‐L (5′‐CATATCAATATGATCTCAGTAC‐3′)  was carried out on concentration‐normalized gDNA by Floragenex Inc.  in identical fashion to several other recent RAD‐seq studies  10 base pairs (bp) in length and an Illumina adaptor were ligated onto the sticky end of the cut site. Samples were then pooled, sheared, and size selected for optimal Illumina sequencing . A subset of samples were prepared for paired‐end Illumina sequencing  following the library prep protocol described in Baird et al.  and sorted by individual‐specific barcode. Reads were truncated to 90 bp, including the 6‐bp restriction site. For the data generated with paired‐end sequencing, only the first read was used. Putative loci were generated using the denovo_map.pl pipeline in Stacks v1.35  of 3, such that three reads were required to generate a stack ; a within‐individual distance parameter (‐M) of 3, allowing for three SNP differences in a read; and a between‐individual distance parameter (‐n) of 3, allowing for three fixed differences between individuals to build a locus in the catalog. In initial exploratory analyses, altering the values of the within‐individual and between‐individual parameters did not significantly impact the number or identity of downstream loci called by Stacks (not reported).Using the FIS) were calculated by the populations program in Stacks, using loci found in eight of the nine populations and in at least 80% of individuals per population . Information on the effect of changing the ‐p and ‐r flags is available in Supporting Information Appendix –write_random_snp . Heterozygosity (observed and expected) values were also calculated in the R Package PopGenKit  to provide secondary validations of reported values. Allelic richness was calculated using PopGenKit.Population summary statistics . Smartpca was run with four iterations of outlier removal (“numoutlieriter” = 4) with otherwise default parameters. In addition to the PCA, fastSTRUCTURE  set to values between one and 10 to assess genetic structure through a hierarchical analysis, and the program chooseK.py was run to select the value of k most consistent with the program's spatial structure model. FST values were calculated by the populations program in Stacks using a p‐value cutoff of 0.05 and a Bonferroni correction (using the “bonferroni_gen” flag in the populations program). In addition to these analyses, frequency spectra of the major alleles and of FIS reported by Stacks were plotted in iPython. FIS is calculated as FIS=HS-HIHS where HS is the heterozygosity in the subpopulation and HI is the heterozygosity of the individual. The output from Stacks reports FIS values of zero when the HS is equal to zero (p = 1), but in these cases, the numerical value of FIS is actually undefined. In order to remove these values, only FIS values that were calculated when HEXP > 0 were used.Three methods were used to describe the genetic structure of lionfish populations in the study area: principal component analysis (PCA), a stats package from Scipy, a collection of open source software for scientific computing (https://scipy.org). The least‐cost distance dispersal trajectories used in these regressions were calculated using the “gdistance” package in R with a bathymetric constraint from ETOPO1 .In addition to the described approaches of regressing genetic diversity measurements with distance from Florida, we also implemented range expansion specific analyses  and annotate RAD loci.To annotate the RAD loci and infer possible links to gene function, we aligned the sequences to the nonredundant sequence database (restricted to teleost bony fishes) of National Center for Biotechnology Information (NCBI) using the BLASTx  program as implemented in 2.6P. volitans genome based on the observed number of restriction sites , we used the linear model and parameter estimates for the SbfI enzyme described by Herrera, Reyes‐Herrera, and Shank . Loci were identified for which (a) the major allele switched to the minor allele in at least one of the nine populations ; or (b) the difference between the maximum and minimum value of the overall major allele among the populations exceeded a defined value . Loci identified by these filtering techniques were used in analyses of site frequency spectra (SFS) and FIS to determine whether specific loci were driving and/or breaking patterns in the dataset, meaning that the forces driving those loci might be dominating the overall population data.Custom scripts were developed to identify groups of loci in the data with unique diversity patterns , we used two analysis programs.  BayEnv 2.0 . Within each bin, each locus was ranked by Bayes Factor and that rank was divided by the number of loci in the bin. This created the empirical distribution from which loci in the top 5% and 1% of Bayes factor values were identified, as described in Coop et al. . The number of reads removed varied slightly by sequencing type (single end vs. paired end) and by population . In most cases, two RAD‐tag sequences matched to a BLAST result, which is consistent with having two “loci” sequenced in each direction away from the restriction site. These results could be used in concert with future draft and scaffold assemblies of the lionfish genome to confirm identity and location or RAD loci.3.4denovomap.pl, reviewed in Supporting Information Appendix The number of RAD loci identified in multiple populations ranged from 9,502 to 48,079 with the majority of values between 30,000 and 50,000  remained steady throughout the sampled range , or subpopulations, the chooseK.py program from fastSTRUCTURE was run for values of k between 1 and 10. The value of k that maximized marginal likelihood and that best explained the structure in the data  was 1, indicating that the fastSTRUCTURE analysis fit the data best with just one genetic lineage. After a Bonferroni correction, many pairwise FST values calculated by Stacks were not statistically different from zero. For those that were, FST values showed very slight genetic differentiation among populations with significant values only for five pairings: Bahamas—Belize = 6.91 × 10−5; Caymans—Mexico = 1.1 × 10−4; Jamaica—Dominican Republic = 6.10 × 10−5; Jamaica—Honduras = 1.2 × 10−4; Dominican Republic—Honduras = 1.1 × 10−4. FST values, therefore, do not reveal genetic differentiation of populations closer to the edge from those at the center of the range.In order to determine the most likely number of genetic lineages  and those closer to the moving edge of the invaded range (“edge populations”) were used to detect specific loci for which frequencies were greater in the core of the invaded range than closer to the edge. From the list of loci that had a difference of 0.5 or more between maximum and minimum allele frequency, 115 had greater allele frequencies in Florida than in the USVI, 127 had greater allele frequencies in Florida than in Honduras, 106 had greater allele frequencies in the Bahamas than in the USV, and 122 had a greater allele frequency in the Bahamas than in Honduras. Additional pairwise comparison results showing counts of loci that overlap with different filtering requirements, including the outlier analyses described below are presented in Table 3.8LOSITAN analyses identified 256 loci as possible targets of directional selection . BayEnv 2.0 generated Bayes factors for the 12,759 analyzed loci. Taking the top 1% of loci from each bin captured 120 loci considered to have high enough Bayes Factors to be considered correlated to the linear regression model generated by the program BayEnv, taking the top 5% captured 616 loci. The top 5% of loci identified by BayEnv were then compared to the list of FST outliers generated by LOSITAN and were also compared to lists generated by the locus‐specific diversity analyses described above, including the loci with a change from major to minor allele, and those with large differences between their maximum and minimum frequencies  in certain populations , so it is likely to detect alleles with certain clines in the parameter space  locus 48803, which is likely located in a glutamate receptor; (b) locus 11751, which is potentially part of a membrane progestin receptor sequence; and (c) locus 15012, which was identified as being located in a proto‐oncogene tyrosine kinase. These three loci could potentially be involved, respectively, in (a) learning and memory (Riedel, Platt, & Micheau, Of the loci that were identified as outliers by both 4.2The year of recruitment of individual fish may affect genetic outcomes. For example, the fish sampled from the Cayman Islands—while collected in 2013—putatively recruited to the reef as early as 2005/2006, which would make them the oldest fish in the study (Supporting Information Appendix This study is the first to employ RAD‐seq to explicitly describe range expansion genetics in lionfish across Caribbean sampling sites. While the development of NGS has accelerated the generation and analysis of large amounts of reduced representation genomic data, and the subsequent resolution of questions in the field of nonmodel species genomics (Merz et al., 5Range expansions, while an undeniably important force in shaping genetic diversity across the planet, have limited signatures in some species due to the specific context of the expansion. Here, we have demonstrated that while not all the predicted patterns of expansion manifest themselves in the lionfish populations sampled, the range expansion process has led to disequilibrium closer to the range front. Populations of lionfish sampled in this study are well mixed and dispersal among sites is high, potentially precluding the detection of predicted decreases in allele frequency along the expansion axis. Genome‐level analyses revealed low to no spatially explicit metapopulation genetic structure, yet genetic diversity throughout the invaded range was not homogeneous. While patterns of genomic diversity correlated with invasion pathway, observed heterozygosity decreased with distance from Florida while expected heterozygosity remained mostly constant, indicating population genetic disequilibrium correlated with distance from the point of invasion.Ultimately, the lack of decreases in major allele frequency or allelic richness across the invaded range suggests that the process of expansion is unlikely to cause long‐lasting limits to the adaptive potential of lionfish in their invaded range. It could also be inferred that signals of disequilibrium dissipate over time and space for the lionfish. Temporal comparisons of genetic diversity in a spatial context will be necessary to fully understand how a rapid invasion like that of the lionfish affects adaptive potential and the evolution of the species.None declared.EKB designed the research with assistance from TMS, JAM, and SH. EKB performed the research. EKB and SH completed the analyses. EKB wrote the manuscript with assistance from TMS, SH, and JAM. Click here for additional data file.


Mythimna separata, is a serious agricultural pest in China. Seasonal and roundtrip migration has recently led to sudden, localized outbreaks and crop losses. To evaluate genetic differentiation between populations in eastern and western China and elucidate gene flow, the genetic structure of 20 natural populations from nine provinces was examined using seven microsatellite markers. The results indicated high genetic diversity. However, little to moderate (0 < FST < 0.15) genetic differentiation was detected, and there was no correlation between genetic distance and geographical distance. Bayesian clustering analysis identified three groups whereas discriminant analysis of principal components identified ten clusters that were considered as two clear‐cut clusters and one admixed group. Gene flow occurred frequently in most population pairs, and an asymmetrical migration rate was detected in several pairwise population comparisons. The bottleneck test showed that few populations had experienced recent bottlenecks. Correspondingly, large‐scale and long‐distance migration of M. separata has caused low genetic differentiation and frequent gene exchange. Our findings are important for studying genetic evolution and help to improve predictions of M. separata outbreaks in China.The oriental armyworm,  Mythimna separata is a serious agricultural pest, and our results will help to improve predictions of its outbreaks in China.Our study evaluated the population structure, genetic differentiation, and gene flow between geographically distant oriental armyworm populations in eastern and western China using seven microsatellite markers. The results showed that there was little genetic differentiation but high genetic variability and extensive gene flow among populations. We believe that our study makes a significant contribution to the literature because  The gluttonous behavior of larvae, their short life cycle  fields from nine provinces at 20 geographical sites in China  was calculated using PowerMarker 3.25 , effective alleles number (Ne), Shannon's index (I), observed heterozygosity (Ho), and expected heterozygosity (He) were estimated using GenAlEx 6.5 , allelic richness (Ar), and inbreeding coefficient (Fis) within populations were evaluated using Fstat 2.9.3 , and its significance levels  were estimated with 1,000 permutations ) against the natural logarithm of geographical distance (km) across populations for microsatellite loci using the Mantel test  values which ranged from 1 to 20 were performed with a burn‐in period of 50,000 iterations and 1,000,000 Markov Chain Monte Carlo (MCMC) replicates. The most likely number of clusters (K) was determined by considering log‐likelihood values of each K and the Delta K method described by Evanno, Regnaut, and Goudet , as suggested by Jombart et al. , retaining 200 PCs in the analysis. The dapc function performed a discriminant analysis using 50 PCs (>80% of variance explained), and nine eigenvalues were retained and examined. The assign.per.pop function was used to evaluate the proportions of successful reassignment of individuals to their original clusters. Specifically, we applied the a.score and a.optim.score functions were used to identify the optimal number of principal components to be retained. Twenty independent runs were executed and the average results were plotted.The population genetic variance was further analyzed by a global analysis of molecular variance (AMOVA) performed using Arlequin 3.5, and average  Mantel,  with 1,0 Mantel, . Populat Mantel, . Twenty d Goudet , implemed Goudet . CLUMPP d Goudet . Then cld Goudet . Furtherd Goudet . The numt et al. . The fun2.3.3Nem) from genetic data based on the relationship FST = 1/(4Nem + 1) , the strict stepwise mutation model (SMM) and two‐phase model (TPM) were applied with 10,000 simulation iterations to identify whether populations have experienced bottleneck effects in history under the assumption of mutation–drift equilibrium using BOTTLENECK 1.2.02  ranged from 0.628 to 0.935 (Table Na) and effective number of alleles (Ne) were 9.5 and 5.23, respectively. The estimation for the average of Shannon's index (I) was 1.808. The allelic richness (Ar) ranged from 6.499 to 11.449 per population, and gene diversity ranged from 0.712 to 0.828. Observed heterozygosity (Ho) ranged from 0.580 to 0.702, while expected heterozygosity (He) ranged from 0.694 to 0.810. The inbreeding coefficient (Fis) within individuals, relative to the rest of their subpopulation, was between 0.097 and 0.297 (Table p < .05). Linkage disequilibrium presented in 63 of the 147 pairs of microsatellite loci, and no complete linkage of a certain locus was detected.A total of 193 alleles were detected over seven microsatellite loci, with a low null allele frequency ranging from 0.029 to 0.185. Therefore, no loci were removed from further genetic analyses. Global 3.2K was difficult to determine as no single unifying characteristic was apparent for any of the inferred groups at K = 3. Generally, among them, cluster 1 dominated in the LNF and SXB populations, cluster 2 dominated in the JLC and YNZ populations, and cluster 3 dominated in the HBB and SYC populations (cluster with an estimated membership >0.800). However, the other 14 populations showed some level of admixture, and half of them did not completely form their own cluster  curve in the DAPC analysis supported 10 clusters Figure . ClusterCombining results from Bayesian analysis in STRUCTURE and DAPC, individuals from NME and SXB to be genetically differentiated from LNF, as well as HBC Figures  and 3. A3.3FST value, calculated across all populations and loci, was 0.045 (p < .001). It is generally assumed that FST < 0.05, 0.05 < FST <0.15, 0.15 < FST <0.25, and FST > 0.25 exhibit little, moderate, significant, and high levels of genetic differentiation, respectively . With the exception of SDJ population, moderate differentiation presented between the HBB population and 18 the other populations (FST > 0.05). The findings illustrated that genetic divergences in the armyworm were mainly between individuals and that gene flow among populations in China was not limited.The global analysis of molecular variance (AMOVA) test results attributed 4.54%, 19.72%, and 75.74% of the variation to differences among populations, among individuals within populations, and within individuals, respectively, based on the pairwise differences distance method  between the FST/(1 − FST) ratio for pairs of populations against the natural logarithm‐transformed geographical distance  of several population pairs were greater than 4  during a period of large‐scale migration from June to August 2017. Theoretically, Nem also assumes that populations are in migration‐drift equilibrium, which occurs when the increase in genetic differentiation caused by drift is equal to the decrease in genetic differentiation caused by gene flow  in any populations under the SMM model. Conversely, heterozygote excess of most populations was apparent (p < .05) under the IAM model, except HBC and JLS populations, elucidating that those populations experienced a reduction in effective size. The discrepancy between IAM and SMM might result from either a small sample size or an influence of compound and complex loci. Under TPM model, significant heterozygote excess (p < .05) was detected in three of the populations , indicating that these populations deviated from mutation–drift equilibrium and might have recently undergone a genetic bottleneck; allele frequency presented a normal L‐shaped distribution  based on FST among populations. Our results indicated that migratory dispersal led to differences in population structure but they still belonged to a panmictic population owing to their high capacity for long‐distance migration.Bayesian clustering and DAPC analyses Figures  and 3 su3 Figure , individ3 Figure . Further4.3Nem > 1.0), between pairwise populations, even between most adjacent populations of M. separata. This might be owing to its migratory behavior and nongeographical isolation. Therefore, a high gene flow of armyworms  could immigrate into east–central China (SD) and subsequently to southern China (i.e., FJ, GD, and GX; Table Generally, there are two large‐scale and long‐distance migrations, that is, seasonal and roundtrip flight between southern and northern China (Li et al., 5M. separata. Our analysis showed that little population structure, the lack of genetic differentiation and its extensive gene flow among populations in China, which in consistent with the fact that populations of this species undertakes a long‐distance and large‐scale migration. In addition, bottleneck effects and genetic drift have not yet affected the genetic differentiation of M. separata. Finally, sampling including all generations occurring in a year across its entire distribution in China is required to further confirm genetic structure of populations, which reflects the interaction of genetic drift, mutation, and migration, with influences from life history. Greater knowledge on the genetic variation in natural populations of M. separata will influence regional outbreak patterns in China by ensuring proper pest prediction and control in advance.Microsatellite markers elucidated higher genetic diversity of the second and the third generations of None declared.X.L.X. and J.X.W. conceived the study; M.M.L., S.X.J. and Y.W.Z. participated in collecting the biological samples; and M.M.L. and B.L.L. analyzed the data and wrote the manuscript. All authors contributed to editing the manuscript. Click here for additional data file. Click here for additional data file. Click here for additional data file.