Mimulus guttatus in the United Kingdom, where the species is considered invasive, and compare this diversity to that in native populations on the west coast of North America. Additionally, we looked at diversity in non‐native populations that have not yet become invasive  in eastern North America. We investigated population structure among populations in these three regions and attempted to uncover the sources for populations that have established in the naturalized and invasive regions. We found that genetic diversity was, on average, relatively high in populations from the invasive UK region and comparable to native populations. Contrastingly, two naturalized M. guttatus populations were low in both genetic and genotypic diversity, indicating a history of asexual reproduction and self‐fertilization. A third naturalized population was found to be a polyploid Mimulus hybrid of unknown origin. Our results demonstrate that M. guttatus has likely achieved colonization success outside of its native western North America distribution by a variety of establishment pathways, including those with genetic and demographic benefits resulting from multiple introductions in the UK, reproductive assurance through selfing, and asexual reproduction in eastern North America, and possible polyploidization in one Canadian population.An ongoing controversy in invasion biology is the prevalence of colonizing plant populations that are able to establish and spread, while maintaining limited amounts of genetic variation. Invasive populations can be established through several routes including from a single source or from multiple introductions. The aim of this study was to examine genetic diversity in populations of  Mimulus guttatus native, naturalized, and invasive populations in the Western US, Northeastern America, and the United Kingdom, respectively. Naturalized populations had low genetic variation relative to native and invasive ones.We investigated the genetic footprint of  Factors that can restrict the establishment and spread of introduced plant populations include low genetic diversity and Allee effects associated with founder events, insufficient propagule pressure in the form of a single or few introductions, maladaptation to novel environmental pressures, or some combination of these Lee, . HoweverAccording to Richardson et al. , naturalThe important transition from naturalization to invasion is often dictated by the genetic constitution of the plant population, which is in turn governed by the mode of reproduction and mating system of the plant species in question  in the introduced range Barrett, . The stuTragopogon mirus , a nearby naturalized population comprised of a heretofore‐undescribed hybrid Mimulus taxon, three non‐native M. guttatus populations in the United Kingdom, where the species is considered invasive, and native populations that occur across a large span of the species' home range in western North America. Our goal was to address the following questions: (1) How does genetic and genotypic diversity in non‐native populations  compare with diversity in native populations? We predicted that populations in the invasive region will have similar levels of genetic diversity as native populations due to the species' history of multiple introductions as an ornamental plant , or common monkeyflower, is a herbaceous species native to the west coast of North America, found from Mexico to Alaska , it was apparent that the NBBR population was comprised of polyploid hybrid Mimulus individuals. These individuals likely represent a polyploid  with M. guttatus constituting at least one of the parental taxa. It has been shown that M. guttatus readily hybridizes with closely related Mimulus species to form allopolyploids  formed by M. guttatus and a South American species, M. luteus, which is also found throughout the UK  greenhouse, and when seedlings were ~6 cm tall, leaf tissue was collected from 20 individuals per population and stored in silica gel. Following DNA extraction and genotyping (see below), the sample size was reduced to 14 individuals for each of the UK populations due to poor‐quality DNA in some samples.For each of the 14 native and naturalized populations, we randomly sampled fruits and leaf tissue from 30 to 50 individual plants that were >1 m apart to increase the chances of sampling multiple genotypes. Leaf tissue was immediately stored in silica gel until DNA extraction. For the three 2.3Mimulus populations  are suitable for genotyping based on a selection strategy of Vallejo‐Marín et al. ; the average number of alleles per locus in each population (A'); the average number of alleles per locus in an individual (H′); the proportion of observed heterozygotes, averaged over all loci (HO); and the number of private alleles (P). Welch's two‐sample t‐tests were used to test for significant differences between regions for these statistics . For the diploid M. guttatus populations, we used GenAlEx 6.5 to calculate expected heterozygosity and deviations from Hardy–Weinberg equilibrium (HWE). To determine pairwise genetic differences between individuals within each population, we used the method developed for microsatellite data by Bruvo et al. , which allows calling of multiple peaks per locus. A random sample of 10% of individuals was reassayed and rescored to check consistency. For the polyploid individuals at the NBBR site, determining conventional genetic diversity parameters based on allele frequency  is problematic because of the difficulty in identifying alleles in partial heterozygotes. Therefore, to assess allelic diversity in each population and between regions, we calculated the following statistics  assignment, to determine expected proportion of MLGs from the total number of individuals sampled (R) using a rarefaction method to account for sample size  a hierarchical analysis of molecular variance  was left out of the analyses of population structure because it was the only polyploid population found. This omission allowed us to focus on the structure among the remaining diploid M. guttatus populations.We used four complementary analyses to investigate population structure among the 16 nce Nei,  visualizpoppr to estimate variance and distribution of diversity within and among regions, populations and individuals within populations. The significance of variance components calculated for all levels was tested with 1000 permutations.First, we conducted a hierarchical AMOVA in k‐means clustering algorithm to analyze any number of potential clusters (k's) in a sequential manner. The optimal k should correspond with the lowest Bayesian Information Criterion (BIC) score. DAPC has been suggested as an alternative to other Bayesian clustering methods such as STRUCTURE , three separate Mantel tests were performed with the ns Jost, . Jost's 33.1M. guttatus populations and ranged from one to three peaks in the putative polyploid hybrid population NBBR. Markers deviating from Hardy–Weinberg equilibrium (HWE) were found in each of the 11 native and three invasive M. guttatus populations. The two naturalized M. guttatus populations, NBS  and FC (New York), were monomorphic for 11 and seven loci, respectively . All loci that were not monomorphic in these populations deviated from HWE. The total number of alleles amplified per locus (A') ranged from 6 at locus AAT267 to 23 at locus AAT230, when both the M. guttatus and the putative polyploid taxa were considered (Table A) were amplified in the 16 M. guttatus populations and 32 alleles in the putative polyploid (NBBR) population for the 12 microsatellite and intron‐length polymorphic markers. Of the 32 alleles from the polyploid hybrid population, six (19%) were found exclusively in that population.Individual genotypes consisted of either one or two peaks per locus in the 16 A, A', H′, HO, P; Table t‐tests; p > .05). The total number of alleles . The largest number of alleles was found in the putative polyploid NBBR population in the naturalized region (32), while the fewest was found in the naturalized M. guttatus population NBS . The putative polyploid NBBR population had the greatest number of alleles per locus (2.7). Average observed heterozygosity in the native and invasive region was similar , while heterozygosity in the NBBR population was relatively high (0.49), as expected for a population consisting of polyploid individuals .The mean pairwise genetic difference between individuals .An AMOVA Table  with a tM. guttatus individuals from 16 populations) into 16 clusters  showed that the k‐means clustering separated the data set . The three native populations from Alaska, along with the population from Washington state, formed a clade within the larger grouping of native populations (72% support). This AK/WA clade was also shown as being the most closely related native group to the invasive UK/NBS clade; however, support for this relationship was low (28.5%).A dendrogram based on Nei's genetic distance Nei,  provideds Figure . Each ofs Figure . Also, trm; Table M. guttatus populations and showed a positive correlation between genetic and geographic distance , which indicates a classic pattern of isolation by distance. The second test included only the 11 native populations and also showed a positive correlation with geographic distance . The third test included the five non‐native populations (excluding the putative polyploid NBBR population) and, contrary to the previous tests, showed little correlation between genetic and geographic distance .To examine the relationship between genetic and geographic distance, we performed three Mantel tests  The naturalized M. guttatus populations in eastern North America had low genetic diversity compared with populations in the native and invasive regions, so the occurrence of only a few multilocus genotypes in naturalized populations suggests a population bottleneck and persistence due to a selfing/asexual reproduction; (2) we found some evidence for the northern edge of the native distribution representing the source location for populations in the invasive region, as well as data suggesting a close relationship between the invasive UK populations and one of the naturalized populations on the east coast of North America; (3) one naturalized population in New Brunswick, Canada, was identified as a polyploid species of Mimulus. Overall, we have provided evidence for multiple pathways of establishment for the non‐native populations of M. guttatus. Later, we discuss our results in more detail and consider their relevance to broader questions in invasion genetics.Understanding the role of genetic variation in plant invasions is a primary focus in modern ecology, and reconciling the paradox that exists when plant populations with low genetic diversity are able to establish in non‐native locations is a goal for researchers interested in managing these populations , we found that the average total number of alleles, number of alleles per locus, and observed heterozygosity in native populations were nearly twice that found in the two naturalized populations , was also relatively deficient in some measures of genetic diversity relative to native populations but overall its observed heterozygosity was similar to the average heterozygosity found in the native populations. The FC population may have a similar introduction history as the NBS population, but it is unlikely they originated from the same source population (see discussion of source populations below). Methods designed to detect a recent reduction in population size based on the principle of excess heterozygosity using microsatellites or other molecular markers . While few morphological, environmental, or demographic variables can be considered as universal facilitators across all plant invasions, propagule pressure has been found to be a common denominator explaining nearly all successful invasions for which there are historical records of introduction  are derived from a region in the North Pacific, specifically in the Queen Charlotte Islands in British Columbia, Canada. Future “Next‐Gen” sequencing may provide greater resolution of the geographic source region compared with traditional SSR marker techniques regarding introduction histories and establishment pathways, and recent methods for analysis such as approximate Bayesian computation can allow the evaluation of different invasion scenarios  population located in New York demonstrated high differentiation from the other populations, completely isolated from other groups by the first two principal components Figure  and rece4.3Mimulus hybrid species in eastern North America. Chromosome counts conducted revealed between 44 and 46 chromosomes , greater than the 28 chromosomes typically found in the diploid M. guttatus  and M. cupreus (2n = 4x = 62) , which makes it a candidate as the second parental taxon with M. guttatus that could produce the putative triploid population NBBR. However, the results from chromosome counts revealed higher counts than would be expected from an M. guttatus × M. moschatus hybrid, and they have also been reported as being incompatible  Stace, . PerhapsPennell, . MimulusMimulus hybrids in the UK have been found to be largely sterile ; data curation (lead); formal analysis ; investigation (lead); methodology ; resources ; validation ; writing – original draft (lead); writing – review and editing . Michele R. Dudash: Conceptualization ; data curation (supporting); formal analysis ; funding acquisition (supporting); investigation (lead); methodology (supporting); project administration (supporting); resources ; supervision (supporting); validation ; visualization (supporting); writing – review and editing . Elizabeth A. Zimmer: Conceptualization ; data curation ; funding acquisition (lead); investigation (supporting); methodology ; project administration ; resources (supporting); software (supporting); supervision ; validation (supporting); visualization (supporting); writing – review and editing .


Isoodon auratus), a threatened marsupial endemic to Australia. The currently recognised taxon consists of three subspecies distributed among multiple natural and translocated populations. After confirming the genetic distinctiveness of I. auratus from two closely related taxa, I. fusciventer and I. macrourus, we identified four genetic clusters within I. auratus. These clusters exhibited substantial genetic differentiation , reflecting long-term isolation of some populations on offshore islands and the influence of genetic drift. Mainland natural populations in the Kimberley region had the highest genetic diversity and the largest contribution to overall allelic and gene diversity compared to both natural and translocated island populations. A population translocated to Guluwuru Island in the Northern Territory had the lowest genetic diversity. Our data suggest that island populations can appear genetically unique due to genetic drift and this needs to be taken into account when considering genetic diversity in conservation efforts to maintain overall genetic diversity of the species. We effectively demonstrate how genomic information can guide practical conservation planning, especially when declining species are represented by multiple isolated populations.Using genetic information to develop and implement conservation programs is vital for maintaining biodiversity and ecosystem resilience. Evaluation of the genetic variability within and among remnant populations can inform management of both natural and translocated populations to maximise species’ adaptive potential, mitigate negative impacts of inbreeding, and subsequently minimise risk of extinction. Here we use reduced representation sequencing to undertake a genetic assessment of the golden bandicoot ( Genetic diversity is a fundamental element of biodiversity and helps drive ecosystem resilience, stability, and services  and red foxes (Vulpes vulpes)  plan for threatened species conservation and recovery, the “Threatened Species Action Plan: Towards Zero Extinctions”. The plan indicates that evidence-based conservation actions will be needed to achieve recovery targets. Genetic management will be integral to strengthening species’ resilience and adaptive capacity, as well as to ensure genetic diversity is maintained in insurance populations, particularly those in havens. In light of this ambition, here we conducted a genetic assessment of the threatened golden bandicoot s Ramsay , a smalls Ramsay , 2015. TI. a. auratus from the Kimberley region, I. a. arnhemensis from the Northern Territory and I. a. barrowensis from Barrow Island, Pilbara region  listed independently as Vulnerable under the Environment Protection and Biodiversity Conservation (EPBC) Act 1999. Furthermore, recent molecular analysis suggests a pattern of intermediate polyphyly of I. auratus and I. fusciventer  estimate the degree of genetic differentiation between each I. auratus sampling locality (hereafter referred to as population) and interpret it in an evolutionary context by comparing to other Isoodon taxa; (2) quantify the existing genetic variation within each population; (3) determine whether genetic diversity has been conserved in translocated populations, and (4) prioritise populations for conservation based on genetic contributions to within-species diversity. We expected to find strong structure between subspecies- and species-level taxa. Within species, we expected island populations to show low genetic diversity, particularly when established via translocations, and to be strongly differentiated from higher diversity mainland populations. Given the close relationship of I. fusciventer and I. auratus, we include samples from this species as well as I. macrourus  in Melbourne, Victoria. Illumina libraries were built on 280–375-bp DNA fragments and sequenced on the Illumina NextSeq 600 system (Supplementary Text).n = 28) were discarded. Parameters for the Stacks de novo pipeline were chosen on a subset of 100 random samples following the r80 optimisation approach of Paris et al.  and the second including all natural and translocated populations of I. auratus . Each dataset was run through the Populations module in Stacks with the following parameters: loci needed to be present in a single population, 50% of samples were required to process a locus, a maximum observed heterozygosity of 70%, and pruning to only a single SNP per locus to account for short distance linkage disequilibrium. The resulting VCF was filtered in R v4.0.2 using a modified script from Wright et al. . Additional details on read assembly and data filtering methods are described in the Supplementary Text. Note that datasets were filtered in different ways to meet assumptions of analysis methods, as detailed in Fig. Sequenced reads were cleaned, demultiplexed and trimmed to 125-bp with a phred quality score ≥30 using process_radtags module in Stacks v2.59  and Discriminant Analysis of Principle Components (DAPC). We used the gl.pcoa function in the dartR package  and then optimised using cross validation to choose the optimal number of PCs to retain (10 PCs and 30 PCs for the ‘Isoodon’ and ‘auratus’ datasets respectively). Successive DAPC analyses were run from K values 2–10 and the K value selected based on the lowest Bayesian information criterion (BIC) and after the largest decrease in BIC .Due to the apparent complex evolutionary histories of  Jombart . For DAPWe estimated the proportion of an individual’s genome belonging to ancestral K gene pools using the sNMF function in the R package LEA  and genetic divergence (Dxy) between populations using the software pixy  to produce a VCF consisting of both variant and invariant sites  which was further filtered in VCFtools version 0.1.16  were excluded.We quantified the degree of genetic differentiation  (Rousset gl.ibd in the dartR package.Using the ‘ Rousset  and perfauratus’ dataset. Allelic richness (AR) was estimated using the allelic.richness functions in the hierfstat R package and the number of alleles which only occur in a single population (PA) using the private_alleles function in the poppr R package , expected heterozygosity (HE) and nucleotide diversity (π) values were then extracted from Populations in Stacks summary statistics output. These independent datasets were also used to identify temporal changes in our translocated populations by calculating diversity metrics as described above across time periods. Due to only a single sample available in 2016 from Raragala Island, this population was excluded from this analysis. Autosomal heterozygosity estimates were calculated for the Guluwuru Island population as this method is more robust to small sample size , the diversity among subspecies (δ), the within-subspecies diversity (σ), the among-population diversity within each subspecies (β), and the within-population diversity within each subspecies (α). As this function does not allow for missing data, a dataset with a final call rate of 100% in SNPs was generated using the custom R script described above.Using the ‘S, HS), among-population diversity  and total allelic (AT) and gene (HT) diversity  and repeated the analysis 50 times, taking the average result across all runs.Secondly, we used the program Metapop2 , our ‘Isoodon’ dataset retained 124,079 SNPs, with a mean read depth of 32.491 and 17.444 and a median read depth of 14.182 and 8.091 for the reference and alternative allele, respectively. After filtering using the custom R script, 117 unique individuals were retained with 8552 SNPs. When all missing data were removed for the TreeMix analysis, 117 individuals and 3043 SNPs were retained. Running 203 I. auratus samples that passed quality control (19 samples failed) through the de novo pipeline, 121,863 SNPs were retained, with a mean read depth of 26.088 and 11.436 and a median read depth of 11.282 and 5.222 for the reference and alternate allele, respectively. After filtering using the custom R script, 176 unique individuals and 8244 SNPs were retained, with an overall level of missing data for the filtered SNP by sample matrix of 1.3%. When all missing data were removed for the QDiver analysis, 172 unique individuals and 2495 SNPs were retained.Running the 134 Isoodon’ and ‘auratus’ dataset in ‘sNMF’ analysis  from the ‘auratus’ dataset were consistently separated in all analyses, with the first two PC axes explaining 49% for the PCoA  and nucleotide divergence (Dxy) were variable between different named taxa as well as allopatric populations within taxa, as expected , consistent with their clustering in the ‘sNMF’ analysis . These islands also had the longest branch lengths in the TreeMix tree . Isoodon a. arnhemensis had higher pairwise FST values (FST = 0.39–0.65) than I. fusciventer (FST = 0.2–0.54) and I. macrourus (FST = 0.33–0.57). Pairwise FST values of Augustus Island were higher than the other Kimberley mainland populations, consistent with clustering analyses  as well as the highest number of private alleles, whilst the lowest diversity was observed in I. a. arnhemensis populations, which also had the lowest number of private alleles . Isoodon a. auratus had statistically higher within-region diversity (σ = 0.123) and among-population diversity (β = 0.023) than the other subspecies restricted to offshore islands . Within populations, Artesian Range (α = 0.128) had slightly more diversity than Mitchell Plateau (α = 0.124), which was not detected in diversity metrics .Partitioning genetic diversity into hierarchical strata via a standardised ‘Q’ diversity metric using the QDiver analysis revealed the unequal distribution of genetic diversity across the three recognised subspecies of T) diversity but a positive contribution to gene (HT) diversity  and gene (HS) diversity  which coincided with these populations having the greatest number of private alleles , consistent with low estimates of genetic diversity metrics (Table G) diversity, which reflected their higher pairwise FST values   to total diversity of the species was similar for gene and allelic diversity, except for Augustus Island which had a negative contribution to allelic  Fig. .Fig. 4ThI. a. auratus and I. a. barrowensis always being selected  , which displayed extremely low levels of genetic diversity compared to the mainland  is currently represented.To preserve the long-term viability, resilience, and adaptive potential of n > 100; Ottewell et al. Given the success of reintroductions of this species to date, translocations will continue to be an important conservation tool to reduce the risk of extinction for threatened species and can ensure persistence of important genetic variation  observed between I. auratus populations and long branch lengths in the TreeMix analysis indicated a strong influence of population-specific genetic drift. Other Kimberley Islands in closer proximity to the mainland , although excluded from most analyses due to small sample size, were not distinguished in the clustering analyses. Therefore, divergence time of islands from the mainland and ecologically relevant phenotypic variation should also be considered. The identified hierarchical structure generally coincides with the three subspecies of I. auratus, but this structure primarily reflects geographic isolation and thus should not constrain management options by defining discrete units. In the case of reintroduction programs, prioritizing the conservation of populations for their genetic diversity (with the aim of maintaining >90% of remaining diversity), and thus their adaptive potential, should take precedence over preserving the perceived genetic uniqueness of island populations. This approach ensures the conservation of the species’ overall genetic variability, resilience, and adaptive capacity.Australia’s heavy reliance on offshore islands for threatened species management, whilst crucial for the persistence of multiple mammal species  at the species level, with insurance populations containing representatives of each lineage to spatially spread the risk of cumulative threats and catastrophes. Overall, our study highlights the importance of understanding population genetic structure when considering the loss of genetic diversity across genetically diverged and fragmented populations, particularly islands, and how such information is crucial to incorporate into conservation strategies and management of threatened species.While remnant island populations harbour a proportion of the genetic diversity present within Supplementary material


Esox lucius) to characterize landscape genetic variation, determine the most likely origins of introduced populations, and investigate a presumably postglacial population from Southeast Alaska of unclear provenance. Using a set of 4329 SNPs from 351 individual Alaskan northern pike representing the most widespread geographic sampling to date, our results confirm low levels of genetic diversity in native populations (average 𝝅 of 3.18 × 10−4) and even less in invasive populations (average 𝝅 of 2.68 × 10−4) consistent with bottleneck effects. Our analyses indicate that invasive northern pike likely came from multiple introductions from different native Alaskan populations and subsequently dispersed from original introduction sites. At the broadest scale, invasive populations appear to have been founded from two distinct regions of Alaska, indicative of two independent introduction events. Genetic admixture resulting from introductions from multiple source populations may have mitigated the negative effects associated with genetic bottlenecks in this species with naturally low levels of genetic diversity. Genomic signatures strongly suggest an excess of rare, population‐specific alleles, pointing to a small number of founding individuals in both native and introduced populations consistent with a species' life history of limited dispersal and gene flow. Lastly, the results strongly suggest that a small isolated population of pike, located in Southeast Alaska, is native in origin rather than stemming from a contemporary introduction event. Although theory predicts that lack of genetic variation may limit colonization success of novel environments, we detected no evidence that a lack of standing variation limited the success of this genetically depauperate apex predator.Invasive species are a major threat to global biodiversity, yet also represent large‐scale unplanned ecological and evolutionary experiments to address fundamental questions in nature. Here we analyzed both native and invasive populations of predatory northern pike ( Restriction digest products were used to build individually tagged libraries, which were then pooled, and size selected to a range of 200–500 base pairs  and sequenced on an Illumina HiSeq platform using 2 × 125 bp PE V4 chemistry. Library construction, sequencing, and demultiplexing were performed by GENEWIZ LLC  with a targeted 5 million paired reads per individual.Total genomic DNA was isolated from preserved tissue samples using the reagents and protocols of the Qiagen Gentra Puregene Tissue kit  with a modification to the final elution buffer. Specifically, isolated genomic DNA was dissolved in 50 μL of low‐EDTA TE buffer (pH 8.0) to minimize potential inhibition of downstream reactions. Quantity and purity of DNA preparations were assessed through fluorometry, spectrophotometry, and electrophoresis. We used a double‐digest restriction‐site‐associated sequencing (ddRAD‐seq) approach . The site frequency spectrum was also used to generate Tajima's D and nucleotide diversity (𝝅) statistics for each population. Both Tajima's D and 𝝅 were estimated on a chromosome level and boxplots (using ggplot2) were created to show the variance between populations.Genotypes were called from sorted BAM files using ANGSD  and (2) introduced samples from Southcentral Alaska . Analyses were repeated with K set to varying numbers . Ancestry plots were then created in R , we generated a called set of genotypes following the same parameters as the admixture analysis but also enforcing a posterior cutoff option (−postCuoff 0.95) with ANGSD and outputting the genotypes as a PLINK‐formatted file. Then we used PLINK . Subsequently, an undivided geographic grouping of introduced pike was investigated by a separate genotype calling and DAPC analysis using the same parameters and methods.To examine population structure evidenced by an alternative method to NGSAdmix, we applied Discriminant Analysis of Principal Components (DAPC) as implemented in the R package adegenet Jombart, . Discrim2.5p – val , as well as a minimum MAF of 0.05 (−minMaf 0.05). The PLINK file was converted to a VCF formatted file with PLINK v1.9 . We then generated a consensus tree based on 1000 rapid bootstraps (−bb 1000) in IQ‐TREE v2.0‐rc1  collected and sequenced in this study Table . These 22.6n = 9) and obtained additional geographic coverage with three additional sites by downloading whole‐genome resequencing data from the NCBI Sequence Read Archive. Whole‐genome‐resequencing data from Palmer Lake in Northern British Columbia , the Yukon River ~90 km NE of Whitehorse, Yukon Territory , and Minto Flats, Alaska . The whole‐genome resequencing data included a resampling of Minto Flats to verify intercompatibility of the data types (RADseq and WGS) and two locations from western North America that are geographically close to Antlen River and could be near relatives. Whole‐genome resequencing data were aligned to a reference following the methods applied to ddRADseq data.We examined the relationships of Antlen River pike to native pike collected from natural occurrences in northern North America to determine which lineage (Beringian or Eastern North American) Antlen River pike are most closely related to and to further investigate if these fish are an introduced population from elsewhere in Alaska. We filtered our ddRADseq dataset to sites presumed to be native  and invariant sites removed with ascbias.py (https://github.com/btmartin721/raxml_ascbias). An input file for SVDQuartets was made by grouping samples by location and data type. A set of 1,000,000 random quartets was evaluated and 100 bootstrap replicates were undertaken to assess confidence in inferred relationships.Phylogenetic analysis was conducted by first converting the pruned VCF file to PHYLIP format with vcf2phylip.py (33.1n = 83) and introduced ranges . In addition, we sequenced seven individuals from a single site in Western Canada yielding a total of 358 pike. The sample distribution is shown in Figure We generated ddRAD‐seq data from 351 individuals from 19 sites across Alaska that included sites within the species native , we found a total of 4329 SNPs that had a minor allele frequency greater than 0.05 and were genotyped in at least 281 samples. Levels of nucleotide diversity were low in all populations and varied from 2.22 × 10−4  to 3.63 × 10−4   compared to introduced populations  although several introduced populations . Measurements of Tajima's D also showed a substantial difference between native and introduced populations, with introduced populations showing a more negative value indicative of population expansion following a major bottleneck , Southcentral II , and Kenai Peninsula (Stormy Lake and Tiny Lake) Figure . These gST varied widely between comparisons that ranged from 0.419 (between Antlen River and Otter lake) to 0  . Lastly, comparisons between the Southcentral I and Southcentral II genetic groups of pike also produced moderately high FST values (0.148), suggesting separate origins for the three introduced groups.Pairwise estimates of Fe) Table . FST valST between native populations were also high. For example, genome‐wide FST values between Fairbanks and Minto Flats were 0.201 and between Lake Clark and Lake Nerka 0.143. Lastly, genome‐wide FST results between the Antlen River were high in all comparisons regardless of the population's history (average FST for introduced populations = 0.356 and between Antlen and native populations = 0.280). Average FST showed a significant pattern of isolation by distance with a positive relationship between FST and the distance between populations  and comparisons within both Southcentral groups .Comparisons of FST results. For the complete dataset, K = 5 was the most supported. However, we varied K from 2 to 10 and reported on the major differences between groupings produced by those K values. When K = 2, the samples split into native and introduced groups with limited allele sharing between them  and Southcentral II . There was some allele sharing with the Southcentral II group with two native populations (Yukon Flats and Minto Flats), which is suggestive of native origins for the Southcentral II group. Similarly, the Southcentral I introduced group has some allele sharing with Fairbanks and Lakes Nerka and Clark. When K = 5, the Antlen River samples split from the other native populations with some allele sharing with Yukon Flats and fish from the North Slope. Increasing the K value to 6 caused the two Kenai Peninsula populations to split from native pike from lakes in Western Alaska.Our structure analyses suggested similar patterns of relatedness between populations as our Fm Figure . The twoK value was 3 and could be broadly grouped into a Southcentral I genetic cluster, a Southcentral II genetic cluster, and the two lakes on the Kenai Peninsula. Increasing the K values suggested some lakes contained a high level of admixture and might be indicative of stocking from multiple populations and/or gene flow through dispersal. For example, when K = 4 the Southcentral I group began to divide, with Otter Lake and Shell Lake differentiated from Alexander Lake, whereas Deshka River and Alexander Creek appeared to contain alleles from both non‐native Southcentral groups suggesting admixture. Lastly, restricting our admixture analysis to just the Southcentral I populations suggested admixture in both Alexander Creek and Deshka River from fish from Otter Lake and Alexander Lake.A major aim of this research was to address the origin and relationships of introduced populations of pike in Alaska. Therefore, we also focused our admixture analyses on the introduced populations. Here, the optimal 3.4K = 2 genetic clusters is specified, the two observed clusters are composed of (1) native populations and Kenai Peninsula introduced pike and (2) all other introduced pike , and Southcentral I sampling locations are divided into two groups: one of Alexander Creek, Alexander Lake, and the Deshka River and a second of Otter Lake and Shell Lake. The genetic cluster present at K = 8 of Southcentral II  sampling locations was further examined by additional genotype calling for these fish . This genetic cluster was subdivided by an optimal K of 2 splitting Anderson Lake from Bulchitna Lake, Tukallah Lake, and Yentna River sampling locations. The average membership in each genetic cluster for introduced pike sampling sites at K = 8 is plotted geographically in Figure A total of 345 individuals and 4860 loci were passed to DAPC after calling genotypes and removing sampling locations with few individuals . When 3.5An initial 3614 SNPs were reduced to 907 with the consensus tree shown in Figure 3.6Initially, from 139 samples from 12 presumably native pike populations, 837 SNPs met minimum MAF and other thresholds. These populations include eight sites in Alaska with RADseq data covering the broad natural range of pike in Alaska, a geographically distant site of native pike in Canada (Eagle Lake) and three locations from western North America from WGS data. Pruning reduced this number to 425 SNPs across native pike populations and the Antlen River pike. Plotting of PC 1 (30.58% of variance) and PC 2 (13.75% of variance) indicates Antlen River pike is a discrete group, separate from all other sampling locations examined Figure . PrincipFor the construction of a species tree, 306 SNPs are available for use with SVDQuartets. Bootstrapping found maximal support for all inferred nodes. Antlen River and Eagle Lake were identified as most‐closely related Figure . Minto F4The introduction of non‐native northern pike in Alaska has had significant ecological impacts including the widespread reduction in the abundance of culturally, ecologically, and economically valuable Pacific salmon , and Anderson Lake, Bulchitna Lake, Tukallah Lake, and Yentna River . While some of these groupings conform with expectations of geographic and hydrologic connectivity , others do not  than either Fairbanks and the rest of the introduced populations (0.335–0.339) or the Southcentral I group compared to Yukon Flats and Minto Flats (0.321–0.335). By contrast, the Anderson Lake, Bulchitna Lake, Tukallah Lake, and Yentna River populations  shared alleles with Yukon Flats and Minto Flats as well as a reduced FST (0.193–0.204) compared to other native populations. One possibility is that the Southcentral I group was indeed founded by multiple source introductions from both Interior and Western Alaska .Despite lingering uncertainty regarding the origins of non‐native populations, admixture plots in Figure ST estimates were high between the Kenai Peninsula samples and the other populations (both introduced and native) but lower between Stormy Lake and the two sampled Western Alaska populations . A Western Alaska origin for the Kenai Peninsula samples was supported by both population genetic and phylogenetic analyses, indicating that either these lakes or other lakes in the vicinity of Lakes Clark and Nerka were the origins of pike in the Kenai Peninsula. The first documented recovery of pike in Stormy Lake was in 1970, providing several decades for pike to disperse, but movement between Stormy Lake and Tiny Lake would involve dispersal through drainage basins and crossing of a saltwater barrier, which as discussed previously is unlikely for this scenario. The low likelihood of dispersal by pike without assistance between Stormy Lake and Tiny Lake paired with evidence of admixture within Stormy Lake , nor are they closely related to other native Alaska populations. Population genetic and phylogenetic analyses of existing samples indicate the closest relationship of the Yakutat pike is to samples from Eagle Lake in Ontario, Canada, but again the effect of “ghost populations” is likely. Based on geography and the high FST values between the Yakutat pike and native Alaska populations, we believe it is likely that Yakutat was colonized by pike with a similar genetic background to pike that colonized east of the North American Continental Divide. Due to low sample size for the Eagle Lake pike from Ontario (n = 5), we did not perform FST or admixture analyses on these samples. Clearly, more sampling east of the North American Continental Divide and in other drainages geographically intermediate to Yakutat and those examined in this study is needed to further illuminate the relationship of Yakutat area pike in the Antlen River.The origin of pike in the Antlen River in the Yakutat region of Southeast Alaska has long been suspected to be a postglacial artifact but has remained unclear. Our genetic data from the Antlen River strongly suggest a native origin based on high genome‐wide pairwise Fs Figure  and TajiOur results contribute to a broader emerging story of pike as an increasingly successful global invader (Dunker et al., The authors have no competing interests to declare.Figure S1.Click here for additional data file.Table S1.Click here for additional data file.


Cephalotaxus oliveri throughout the species' distribution. Twenty‐eight EST‐SSR markers were applied to analyze population genetics, for the investigation of the driving factors that shaped spatial structure. In addition, we identified the outlier loci under positive selection and tested their association with environmental factors. The results showed a moderate genetic diversity in C. oliveri and high genetic differentiation among populations. Population structure analyses indicated that 18 populations were clustered into two major groups. We observed that the genetic diversity of central populations decreased and the genetic differentiation increased towards the marginal populations. Additionally, the signatures of IBD and IBE were detected in C. oliveri, and IBE provided a better contribution to genetic differentiation. Six outlier loci under positive selection were demonstrated to be closely correlated with environmental variables, among which bio8 was associated with the greatest number of loci. Genetic evidence suggests the consistency of the central‐marginal hypothesis (CMH) for C. oliveri. Furthermore, our results suggest that temperature‐related variables played an important role in shaping genetic differentiation.Evaluating the contributions of geographic distance and environmental heterogeneity to the genetic divergence can inform the demographic history and responses to environmental change of natural populations. The isolation‐by‐distance (IBD) reveals that genetic differentiation among populations increases with geographic distance, while the isolation‐by‐environment (IBE) assumes a linear relationship between genetic variation and environmental differences among populations. Here, we sampled and genotyped 330 individuals from 18 natural populations of  Cephalotaxus oliveri populations in southern China. (a) Estimation of population structure using delta K (∆K) with the number of clusters (K) ranging from 1 to 18. (b) Estimation of population structure of C. oliveri using the STRUCTURE analysis.The genetic structure of the 18  Ecologically marginal populations may be separated not only by distance from the core but also experience different biotic and abiotic environments  is a dioecious woody shrub or small tree, with the distinctive feature of white stomatal bands on abaxial surface of leaves. As an endemic conifer to southern China, the species has a limited distribution, only appearing in montane regions of Chongqing, southern and western Sichuan, Guizhou, Hunan, north‐western Hubei, eastern Jiangxi, northern Guangdong, and south‐eastern and north‐eastern Yunnan, China. This plant primarily grows along the sides of streams or valleys at altitudes from 300 to 1800 m and prefers warm and humid habitats  assess the genetic variation and population structure of this species, and compare the genetic variation between 12 central and 6 marginal populations; (b) investigate the effects of geographic and environmental factors contributing to genetic variation; (c) identify candidate outlier loci and test for correlation between environmental variables and allelic distribution of outlier loci.To explore the role of geographic isolation and environmental heterogeneity in shaping genetic variation and whether the pattern of genetic variation conforms the prediction of CMH, we used 28 EST‐SSR makers to investigate the genetic variation of 330 individuals from 18 natural populations of 22.1C. oliveri populations, 18 populations were collected from the whole distribution region in southern China, including 6 marginal and 12 central populations . While marginal populations were distributed in Yunnan and Jiangxi Provinces, and isolated from central populations, with small coverage high fragmentation and low densities. Fresh needles were collected from 330 individuals and desiccated with silica gel for subsequent use. Geographic and altitude information were obtained via GPS. Cetyltrimethylammonium bromide (CTAB) approach modified by Su et al.  and effective alleles (Ne), Shannon's information index (I), expected (He), and observed (Ho) heterozygosity. The number of private alleles (Np) was examined using the private_alleles function of R package “poppr”  and allelic richness (Ar) were calculated using the R package “hierfstat”  / 4FST.Analysis of molecular variance (AMOVA) was carried out in Arlequin v.3.5.1.2 to detect genetic variation  ranged from 1 to 18, ten runs were performed for each K, with Markov chain Monte Carlo (MCMC) steps of 100,000 iterations followed by a burn‐in period of 100,000 iterations. STRUCTURE HARVESTER was implemented to obtain the optimum K value according to the delta K (∆K) values . Eight ecological variables included slope, aspect, altitude, normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), percent of tree cover (PTC), leaf area Index (LAI), and fraction of absorbed photosynthetically active radiation (FAPAR). Slope and aspect were extracted from SRTM elevation data (2.5 arc‐mins resolution) and computed in ArcGIS v.10.4.1. Based on the moderate resolution imaging spectroradiometer (MODIS) dataset, the other five ecological factors were derived from the Land Process Distributed Active Archive Center .A total of 47 environmental variables were obtained, including 19 bioclimatic, eight ecological, and 20 soil variables. Nineteen bioclimatic variables for the current period  were extracted from WorldClim database  solution, inductively coupled plasma optical emission spectrometer was used to measure the total P, K, Na, Ca, Mg, Si, Al, S, Cu, Zn, Pb, Fe, and Mn. Three soil samples were collected for each population, and each sample was analyzed in triplicate. Finally, 20 soil variables of sampling sites were obtained.The soil samples were also collected from 18 populations. The electrical conductivity and pH values of the soil samples were determined as soon as possible after water extraction from fresh soil (soil/water = 1/5 weight/volume) using a potentiometer and a conductivity meter, respectively. The moisture content of soil (fresh or air‐dried) was measured by drying at 105°C oven. The air‐dried soil samples were then smashed, and sieved through 0.2‐mm mesh for subsequent analysis. The content of soil organic matter was determined through the potassium dichromate volumetry method, which is divided by 1.724 to obtain organic carbon content. The total nitrogen (N) was evaluated by the Kjeldahl method with a mixture of Kvif.cca function in R package “usdm” .The 22 environmental variables were transformed matrix using PCA. The Euclidean distance between population pairs was calculated using the first five principal components as the environmental distance matrix. The pairwise geographic distance matrix was transformed using the geographic coordinates of populations. The pairwise genetic distance among populations using MMRR function with 999 permutations.To explore the existence of IBD and IBE, we applied Mantel tests to assess the relationships between genetic distance and geographic or environmental distance. Then, we also used the partial Mantel test to assess the effect of one factor on genetic distance by using another factor as a covariable. The Mantel and partial Mantel tests were implemented using R package “vegan” Dixon,  based on2.7rda function of the R package “vegan.” To avoid spatial autocorrelation, distance‐based Moran's eigenvector maps (dbMEM1–dbMEM10) were applied to represent the geographic variables by transforming the coordinates of each individual using the pcnm function of the R package “vegan”. Hellinger transformation was used to transform EST‐SSR data into response variables using the decostand function in R. The 22 environmental variables and 10 geographic variables were performed forward selection separately to remove the variables that lacked explanatory power for partitioning using ordiR2step function of R package “vegan”. Then, RDA was performed between forward selection variables (explanatory variables) and the EST‐SSR matrix (response variables) using rda function. In addition, variation partitioning was also performed using the varpart function in RDA. The significance of all RDA models and constrained axes was detected using the anova.cca function with 999 permutations.Given that IBD and IBE were considered as useful models for describing the observed genetic differentiation  and environmental factors were analyzed using a linear mixed‐effects model (LMM). The lmer function of the R package “lme4”  to 3.714 (LP), with an average value of 2.679, and Ne varied from 1.260 (MG) to 1.922 (FJS), with an average value of 1.660. The ranges of Ho and He were 0.125 (HK)–0.361 (FJS) and 0.141 (MG)–0.382 (SX), respectively. SX exhibited the highest I (0.217), whereas the lowest was observed in MG (0.687). The Ar in each population ranged from 1.500 (HNG) to 2.909 (JFS), with a mean of 2.367. The average FIS was 0.135, and the minimum and maximum values were −0.086 (AF) and 0.323 (XF), respectively. Except for AF, FIS of the other populations was positive. The Np varied from 1  to 11 (LP and PB), and private alleles were observed in 17 populations. The genetic diversity of population MG, HK, and PB showed a lower level than that of other populations, according to the analysis of Ne, Ho, He, and I. No evidence was found for null alleles of all loci by Micro‐Checker. Generally, except for Co164, all other loci significantly deviated from HWE , and group 2 included 3 populations of Yunnan Province   Figure . The res) Figure . Moreove) Figure .p < .01). The FST was 0.260 , suggesting that there was significant genetic differentiation among populations , while differences among populations within two groups  and within populations  accounted for 13% and 57% of the variation, respectively, indicating low genetic differentiation among populations within these two groups.The AMOVA results for all populations showed that 26% and 74% of the total genetic variation was among and within populations, respectively , suggesting high genetic differentiation. The lowest values were observed between MG and FX, MG and XF, HK and FX, and HK and XF, while the greatest was observed between populations YM and HNG, YM and LP, and CX and SX. In addition, the mean value of pairwise FST among populations from group 1 was 0.197, and that of group 2 was 0.180, both were lower than the value (0.475) between group 1 and group 2 (Table Nm) within each group were higher than that across the groups  was higher than populations in the central group (2.305). The Ho and He in the marginal populations (0.198 and 0.239) were lower than the central populations (0.299 and 0.333). Overall, except for Np and Ar, other indices  for the central group were significantly greater than that for the marginal group  was significantly lower than those for populations of the marginal group  was higher than marginal populations (mean Nm = 0.555).We also evaluated the intrapopulation genetic diversity and differentiation between central and marginal groups. The average roup 2.49 was high3.4r = .670, p = .001) or environmental  distance, indicating significant patterns of IBD and IBE among populations of C. oliveri , whereas the association between genetic distance and environmental distance was nonsignificant , while the effect of environmental distance on genetic differentiation was nonsignificant .The Mantel test detected significant relationships between genetic distance and geographic  and 19 environmental variables, 27 of which were related to bioclimatic variables, 16 were related to ecological variables, and 35 to soil variables Table . The mai44.1He is a primary index to measure gene diversity and has been used to measure the level in several studies , which illustrated that a large proportion of the genetic variation occurred within populations. Our results were consistent with the finding that the genetic variation of perennial cross‐pollinated plants mainly existed within the population  and chloroplast sequences (0.639), mainly because of the limited sampling size of populations and differences in molecular markers. The Nm of C. oliveri populations was 1.018 , about 4200 meters high in elevation, have been illustrated to play a major role in the population divergence of the species , which were predicted as two potential refugia for C. oliveri . Zinc finger proteins are a large family of transcription factors in plants and play a key role in regulating growth, development, and response to abiotic stresses in plants ; methodology (lead); software (lead); validation (lead); visualization (lead); writing – original draft (lead). Zhen Wang: Data curation ; formal analysis ; software ; visualization . Yuli Zhang: Data curation ; formal analysis ; methodology ; validation . Minghui Li: Formal analysis ; software ; validation ; visualization . Ting Wang: Data curation ; funding acquisition ; methodology ; supervision ; writing – review and editing . Yingjuan Su: Data curation ; funding acquisition (lead); methodology ; project administration (lead); supervision (lead); writing – review and editing (lead).This work was supported by the National Natural Science Foundation of China (31872670 and 32071781), Guangdong Basic and Applied Basic Research Foundation (2021A1515010911), Science and Technology Projects in Guangzhou (202206010107), and Project of Department of Science and Technology of Shenzhen City, Guangdong, China (JCYJ20190813172001780 and JCYJ20210324141000001).The authors declare that there are no conflicts of interest.Appendix S1Click here for additional data file.


Paramacrobiotus fairbanksi was described from Alaska (USA) based on integrative taxonomy and later reported from various geographical localities making it a true cosmopolitan species. The ‘Everything is Everywhere’ (EiE) hypothesis assumes that the geographic distribution of microscopic organisms is not limited by dispersal but by local environmental conditions, making them potentially cosmopolitan. In the present work we report four new populations of P. fairbanksi from the Northern Hemisphere which suggests that the ‘EiE’ hypothesis is true, at least for some tardigrade species. We also compared all known populations of P. fairbanksi at the genetic and morphological levels. The p-distances between COI haplotypes of all sequenced P. fairbanksi populations from Albania, Antarctica, Canada, Italy, Madeira, Mongolia, Spain, USA and Poland ranged from 0.002 to 0.005%. In total, twelve haplotypes (H1-H12) of COI gene fragments were identified. We also report statistically significant morphometrical differences of species even though they were cultured and bred in the same laboratory conditions. Furthermore, we also discuss differences in the potential distribution of two Paramacrobiotus species. Currently there are 33 families, 159 genera, 1464 species and 21 additional subspecies within this phylum1. Paramacrobiotus fairbanksi Schill, Förster, Dandekar & Wolf, 20103 was described from Alaska (USA) and reported from the Antarctic, Italy, Poland and Spain4 9. It is a large-size (up to 800 μm) parthenogenetic Paramacrobiotus found mostly in mosses and can be shortly characterized by white or transparent cuticle without pores, three bands of teeth in the oral cavity, three macroplacoids and a microplacoid in pharynx (richtersi group), smooth lunules under all claws, granulation on all legs, and eggs with reticulated conical processes without caps or spines. Paramacrobiotus fairbanksi is a triploid species8 inhabiting various locations throughout the globe. The species is an omnivore, i.e., it feeds on algae, cyanobacteria, fungi, nematodes and rotifer10. However, dietary preferences have been observed to differ between juveniles and adults .The Phylum Tardigrada currently consists of 12 suggests that microorganisms and small invertebrate are not dispersal-limited on large geographical scales and have potentially cosmopolitan distribution. Microscopic organisms are often considered cosmopolitan species, as, the presence of specific adaptations allows them to being disperse easily. These adaptations include (a) the possibility of easy passive dispersion , (b) the presence of very resistant spore stages  that help to survive extreme conditions, and (c) the presence of asexual or parthenogenetic reproduction, allowing for rapid increase in the number of individuals16. Cosmopolitism was strongly suggested for many tardigrade species in the past, however, the suggestion was later undermined . At present, we have strong and compelling evidence of a wide distribution of some tardigrade taxa, which means that we return to the concept of cosmopolitism of at least some species of tardigrades  which can support the hypothesis ‘Everything is Everywhere’ (EiE) for tardigrades. According to Gąsiorek et al.21, “a species may be termed as cosmopolitan if it was recorded in more than one zoogeographic realm”. There are 19 tardigrade species known from more than one zoogeographic realm, i.e., Cornechiniscus madagascariensis23 Maucci, 1993, Echiniscus africanus24 Murray, 1907, E. baius25 Marcus, 192826, E. blumi27 Richters, 1903, E. cavagnaroi28 Schuster & Grigarick, 1966, E. lichenorum29 Maucci, 1983, E. lineatus30 Pilato, Fontoura, Lisi & Beasley, 200831, E. marginatus32 Binda & Pilato, 1994, E. merokensis Richters, 190426, E. perarmatus Murray, 190724, E. pusae25 Marcus, 1928, E. scabrospinosus33 Fontoura, 1982, E. testudo34 , Milnesium inceptum35 Morek, Suzuki, Schill, Georgiev, Yankova, Marley & Michalczyk, 2019, Nebularmis cirinoi36 28, P. gadabouti22 Kayastha, Stec, Mioduchowska and Kaczmarek. 2023 and P. fairbanksi, Pseudechiniscus (Meridioniscus) wallacei26 Vončina, Gąsiorek, Morek & Michalczyk, 2022, and Viridiscus viridissimus37 38 . Furthermore, two parthenogenetic species from the genus Paramacrobiotus, i.e., P. fairbanksi and P. gadabouti, are contenders as they show a wide distribution that supports the hypothesis EiE.The ‘Everything is Everywhere’ hypothesis, which was proposed at the beginning of the twentieth centuryP. fairbanksi from all known localities of this species in Albania, the Antarctica, Canada, Italy, Mongolia, Poland, Portugal (Madeira) and the USA. We also discuss genetic and morphological differences between them and consider the general distribution of P. fairbanksi.In the present paper we compare morphological and genetic variability of different populations of 39. The moss samples  were dried post extractions and were deposited at the Department of Animal Taxonomy and Ecology, Institute of Environmental Biology, Adam Mickiewicz University, Poznań, Uniwersytetu Poznańskiego 6, 61–614 Poznań, Poland. Additionally, we used morphometric and genetic data of P. fairbanksi populations from the Antarctic, Italy, Spain, the USA and Poland9.Four moss samples from trees and rocks were collected in 2018 (Mongolia) and 2019   with the rotifers and nematodes added as food ad libitum. All cultures were kept in the environmental chamber at a temperature of 18 °C and in darkness.Specimens of the populations from Albania, Canada, Madeira and Mongolia were cultured in the Department of Animal Taxonomy and Ecology  according to the protocol described by Roszkowska et al.43. Slides were then placed in an incubator and dried for two days at ca. 60 °C. Dried slides were sealed with transparent nail polish and examined under an Olympus BX41.Specimens were extracted from cultures and prepared for light microscopy analysis. They were mounted on microscope slides in a small drop of Hoyer’s medium and secured with a cover slip44. Macroplacoid length sequence is given according to Kaczmarek et al.45. The pt ratio is the ratio of the length of a given structure to the length of the buccal tube, expressed as a percentage46. The pt values always provided in italics. Morphometric data were handled using the “Parachela” ver. 1.8 template available from the Tardigrada Register47. Tardigrade taxonomy follows Bertolani et al.48.All measurements are given in micrometers [μm]. Structures were measured only if their orientation was suitable. Body length was measured from the anterior extremity to the end of the body, excluding the hind legs. Buccal tubes, claws and eggs were measured according to Kaczmarek and MichalczykP. fairbanksi was identified in vivo using light microscopy (LM). To obtain voucher specimens, DNA extractions were made from individuals using a Chelex® 100 resin (Bio-Rad) extraction method provided by Casquet et al.49 with modifications described in Stec et al.39. We sequenced three molecular markers, which differ in effective mutation rates: two nuclear fragments (18S rRNA and 28S rRNA) and one mitochondrial fragment (COI). All DNA fragments were amplified according to the protocols described in Kaczmarek et al.9, with primers listed in Table Before genomic DNA extraction, each specimen of 53. Comparison of obtained molecular markers with those deposited in GenBank and homology search were performed using Blast application . The COI haplotypes were generated using the DnaSP v5.10.01 program55 and were translated into amino acid sequences using the EMBOSS-TRANSEQ application56 to check for internal stop codons and indels. Then all sequences obtained in our study, and the sequences downloaded from the GenBank database as originating from P. fairbanksi, were aligned with ClustalW using default settings. Alignment sequences were trimmed to 689, 572 and 574 bp for 28S rRNA, 18S rRNA and COI barcodes, respectively. The calculation for the uncorrected pairwise distances (p-distances) was performed for COI sequences using the MEGA X57.The amplified nuclear and mitochondrial barcode sequences were edited using the BioEdit softwareP. fairbanksi were deposited at the Department of Animal Taxonomy and Ecology, Institute of Environmental Biology, Adam Mickiewicz University, Poznań, Uniwersytetu Poznańskiego 6, 61–614 Poznań, Poland.All obtained sequences have been deposited in GenBank (for the accession numbers please see Table www.fluxuxengineering.com). The median-joining algorithm (MJ)58 and substitution rates with the weight of 3 for transitions and 1 for transversions (transition: transversion ratio (ti:tv)) were applied. The star contraction pre-processing was generated to delete all superfluous median vectors and links. Additionally, the maximum parsimony post-processing was calculated. In turn, signatures of population expansion, equilibrium or decline in P. fairbanksi were inferred from the neutrality tests calculation  computed in the DnaSP v5.10.01 program and Arlequin v.3.5. software61. Analyses were performed with 1000 replicates.Reconstruction of genetic relationships among COI haplotypes and genealogical connections was carried out using the Network 4.6.1.3 software  were used as the dependent and the populations as grouping variables. Normal distribution in residuals was checked using the Shapiro test. Other morphometric traits, i.e., stylet support insertion points (SSIP), external width of buccal tube (BTEW) and placoids  were also analysed. All the analyses were performed in R 4.1.362. The level of statistical significance was considered at p < 0.05. Principal Component Analysis (PCA) was performed using the R script from Stec et al.63. The analysis was performed for data from eggs and animals. For animals, both absolute values (raw measurements in μm)  and relative pt values  were used. For eggs, absolute values (raw measurements in μm) were used. All analyses were carried out using the R software program48. The “imputePCA” function of the R package “missMDA ver. 1.17” was used to impute missing data in the animal data set using the PCA imputation technique64. Cross-validation (function “estim_ncpPCA”) was used to determine the number of components utilized to impute the missing data. The PCA function of the software “FactoMineR ver. 2.3”65 was used to perform PCAs on the scaled data. The software “ggplot2 ver. 3.3.2”, “plyr ver. 1.8.6”, and “gridExtra ver. 2.3” were used to depict PCAs67. The presence of a structure in the PCA data was tested using a randomization approach on the eigenvalues and statistics according to Björklund68 and an in-house R script developed by MV in Stec et al.63. PERMANOVA was done on the PCs with the R packages “vegan ver. 2.5.6” and “pairwiseAdonis ver. 0.3”69, with the species hypothesis generated by phylogenetic techniques as the independent variable. Using the Benjamini–Hochberg correction, the level for multiple post hoc comparisons was adjusted independently for adults and eggs70. In total, 106 tardigrade specimens  were measured and later used in the analyses for animals. Furthermore, differences in egg morphology between populations were studied and tested using ANOVA. Egg bare diameter (EBD), full diameter (EFD) and processes height (PH) were characters for the populations used as the dependent variable to determine compared groups and Benjamini-Hochberg corrections. In total, 100 tardigrade eggs  were measured and used in the analyses. All the analyses were performed in R 4.1.0. The level of statistical significance was considered at p < 0.05.We used the Analysis of Variance (ANOVA) test with post hoc comparison of pairs of measurements, applying Benjamini–Hochberg correction to statistically analyze the differences in morphometrics between different populations of P. fairbanksi populations was assembled in Corel Photo-Paint 2021.A map of the known distribution of P. fairbanksi and P. gadabouti. The ENM was performed with the use of the MaxEnt software, ver. 3.2.0. ( https://biodiversityinformatics.amnh.org/open_source/maxent/). MaxEnt performs the model with the fewest possible occurrence data and takes presence-only (PO) data. The model generates models of habitat appropriateness by handling continuous and categorical variables using regularization parameters72. The raster package in R was used to extract climatic raster values, and for ENM evaluation, version 0.3.1 of ENMevaluate in R was used. The bioclimatic variables available in MERRAclim Dataset 19 were used as environmental variables for MaxEnt modelling. We used MERRAclim Dataset because it provides a global set of satellite-based bioclimatic variables that includes Antarctica, which is one of the localities for P. fairbanksi. The 19 global bioclimatic datasets from the 2000s at 5 arcminutes resolution 73 consist of temperature layers (BIO1-BIO11) and humidity layers (BIO12-BIO19). Using ENMTools74 correlations among environmental layers were tested for all 19 variables and correlation coefficients >|0.7| were removed. Based on correlation results, six bioclimatic variables with correlation coefficients <|0.7| were selected. The temperature layers are in degrees Celsius multiplied by 10 and the humidity layers are in kg of water/kg of air multiplied by 100,00073. The receiver operating characteristic (ROC) plot’s area under curve (AUC) was used to assess the model’s accuracy71. AUC describes the relationship between the proportion of correctly anticipated presences and the proportion of absences of mistakenly-projected species in the model75. The AUC gauges the effectiveness of the model with a value between 0 and 1. Furthermore, AUC values > 0.9 indicate excellent accuracy, 0.7 to 0.9 indicate good accuracy, and values below 0.7 indicate low accuracy77. The jackknife test was used to estimate the model’s variable relevance. Later, the MaxEnt results were masked to the landmasses using shapefile from https://www.naturalearthdata.com/downloads/10m-physical-vectors/10m-land/. The localities for P. fairbanksi are from Table P. gadabouti from Kayastha et al.22. The coordinate list is provided in An ecological niche modelling (ENM) approach was used to predict the current potential distribution of All procedures were conducted in accordance with the guidelines. Also, none of the moss samples were collected from the region which requires permission.No significant differences were shown by the ANOVA test performed on BL between the studied populations , the Antarctic population (p = 0.035), the Canadian population (p = 0.004), the Mongolian population (p = 0.004) and the Polish population (p = 0.0005), while pt values of specimens from the Madeiran population were higher than the Albanian population (p = 0.014), the Canadian population (p = 0.009) and the Polish population (p = 0.0005), pt values of specimens from the Polish population were lower than the Antarctic population (p = 0.030) and pt values of specimens from the Alaskan population were higher than the Madeiran population (p = 0.002)  showed significant differences between all the populations Tables . Eggs inpt: ψ = 13.14 p < 0.001, ϕ = 0.43 p < 0.001; eggs: ψ = 17.62 p < 0.001, ϕ = 0.50 p < 0.001). The first two components of the PCA of animals’ absolute measured value  for both animal and egg datasets . As a reces Fig. , 13, 14.ces Fig. –SM.07. Rces Fig. . All theces Fig. . Resultsces Fig. .Figure 5P. fairbanksi from Albania, Canada, Madeira and Mongolia were 623–689 bp-long, and represented three haplotypes: haplotype H11 was observed in the population from Albania, haplotype H1 was identified in P. fairbanksi from Mongolia, and haplotype H4 was found in populations from Canada and Madeira   that differed from it by one mutational step. One haplotype (haplotype H2 from Spain) differed from central haplotype H4 by two mutational steps. In several geographical regions, i.e., the USA, Albania, Italy, Poland and Spain there were regional endemic haplotypes. Surprisingly, the second haplotype that occurred in different localities was haplotype H1 and this haplotype was common for three populations, from Mongolia, Poland and Antarctica.The COI sequences of P. fairbanksi from Albania, Canada, Madeira and Mongolia were 917–1547 bp-long , they showed only one nucleotide substitution. A comparison was performed with the sequences from the following geographical localities: Antarctica (GenBank: MN9603029), Poland (GenBank: MH664941-4278), USA (GenBank: EU03807879) and Italy (GenBank: MK041027-298). The 28S rRNA molecular marker (694–805 bp-long) was very conservative. No nucleotide substitution was found for all obtained sequences even after comparing (and trimmed to 689 bp) with GenBank sequences from Antarctica (GenBank: MN960306–MN9603079) and Poland (GenBank: MH66495078). Nevertheless, one unidentified base was found in the sequence originating from the Polish population.In turn, the 18S rRNA sequences of ng Table  and no nDemographic expansion was preliminarily tested based on the value of neutrality tests that confirmed a neutral model of observed polymorphism. Negative significant values for Tajima’s D were found, indicating a high number of low-frequency polymorphisms in the COI sequences dataset and potential population size expansion Fig. C. In turP. fairbanksi and P. gadabouti. The study is limited to bioclimatic variables. The stimulated model predicted good accuracy for the overall model with an AUC for P. fairbanksi of 0.778 and the overall model with an AUC for P. gadabouti of 0.843. The suitability for P. fairbanksi seems moderate   Fig. B.Figure P. fairbanksi from different regions of the world. However, the identification of this species is still possible based on morphological characters, in fact the morphometric data are shown to not affect the species identification because of the overlap in measurements of all measured structures. Therefore, it is valid to suggest the correct classification of all the specimens collected from different regions based on their morphology only. Even though the egg processes of Polish and Albanian populations are similar, the EBD of the Polish population are the smallest and those from the Albania are largest. The EFD as well as egg processes of the Madeiran population are largest while those of the Polish population are the smallest. Additionally, body length values of the Polish and USA populations of P. fairbanksi are smaller compared to the other populations studied.Based on morphometric analyses, there is clear variation in measurements of morphological features between populations of 9 suggested that the differences in measurements between different populations of this species are caused by conditions, i.e., specimens from cultures and specimens from wild populations. However, in the present study all measurements were based on specimens from cultured populations, i.e., Albanian, Canadian, Madeiran and Mongolian. Thus, we can suggest that the phenomenon described by Kaczmarek et al.9  is unlikely to be true. Similarly, the suggestions that harsh conditions in Antarctica may favour laying larger eggs while in cultures the eggs are smaller because of the lack of such selective pressure9 seems untrue as the egg size of specimens from Antarctica overlaps with egg sizes of specimens from Albania, Canada and Mongolia, which were sampled from cultured populations in the present study.Kaczmarek et al.80. Various studies combining COI variation and phenotypic plasticity were conducted throughout different invertebrates’ phyla, including tardigrades84, proving the marker’s accuracy in this group of organisms. The result showed high genetic homogeneity between organisms with wide geographical distribution together with clearly visible morphological differences known as phenotypic plasticity82. This phenomenon could be possible explanation for the subtle morphological variation observed in this study between P. fairbanksi populations, accompanied by very low mitochondrial barcode variation.Cytochrome oxidase subunit I gene (COI) sequences is one of the most reliable barcodes to investigate genetic variation with phenotypic plasticity since COI is a genetic marker with a high genetic variation compared to multiple other DNA barcodes85 or corals86, suggesting that occasionally COI may fail as a barcode marker due to hybridization events. Many studies have already shown that Wolbachia  can increase the speciation rate and can affect COI haplotypes88. However, the nuclear markers tested for P. fairbanksi have been consistent for the studied populations.Furthermore, several studies uncovered data incongruence between mitochondrial and nuclear markers, e.g., for earthwormsP. fairbanksi remains unknown, although, it has unsurprisingly been shown, that some physical traits differ in chosen cultured tardigrades depending on the temperature and food abundance7. If the morphological variation in P. fairbanksi is an effect of phenotypic plasticity, it is unclear which factors could cause various morphotype expressions. The specimens from Mongolia, Albania, Canada and Madeira that were measured in our study come from populations cultured in similar laboratory conditions but were started with different counts of founders of various ages, kept in variable densities and with different numbers of generations that had passed culture, so no answer can be proposed at this moment. No molecular markers that correspond with morphological features in tardigrades have been suggested so far. Future studies with higher-resolution markers designed for intrapopulation variation should be performed to determine if any pattern of genetic diversity concordant with morphological variation can be observed.The exact causes and mechanisms of the phenotypic plasticity in the morphology of adults and eggs of 89), which tardigrades’ habitats clearly are. Furthermore, phenotypic plasticity has been widely observed in other invertebrates like corals  Verrill 1864, scallops  Linnaeus, 1758, marine invertebrates, gastropods  Linnaeus, 1758, rotifers ) and many more. No concordant genetic variation was observed, but a large and discrete differentiation of morphotypes was present and was always associated with external environmental factors such as temperature, predation risk and food availability97.Phenotypic plasticity, in morphology and other aspects of phenotype, such as life history traits, is seen as an advantage for thriving in heterogeneous environments  and the scorpion species Liocheles australasiae101 (Fabricus 1775) are parthenogenetic for multiple generations in captivity103 and are widely distributed105. Similar cases are found in many animals and plants (ref109)). However, Baker et al.99 also suggested that parthenogenesis indicates morphological variation as a result of epigenetic mechanisms. Furthermore, Mioduchowska et al.87 provided molecular evidence of the presence of the bacterial endosymbiont Wolbachia based on next generation sequencing in tardigrades. Wolbachia have an effect on the evolution as well as the ecology of their hosts and have been found to cause effects including cytoplasmic incompatibility, feminization, male killing, and induced parthenogenesis110 It has been noted that at the intraspecific level, even individuals from the same population can undergo morphological changes in their characters to diversify within niches available to the species111. Similarly, Kihm et al.104 proposed epigenetic factors as a main cause for variability in tardigrade Dactylobiotus ovimutans112 Kihm, Kim, McInnes, Zawierucha, Rho, Kang & Park, 2020 egg morphology, although the population was cultured under controlled laboratory conditions. Despite being rare, it is known that intraspecific variation is caused by external environmental conditions, epigenetics and seasonality112.The phenomenon where parthenogenetic  lineages occupy a wider geographical range, but sexual populations are restricted to a limited area, is termed ‘geographical parthenogenesis’113. It effectively predicts habitat suitability for rare and poorly studied taxa115. P. fairbanksi presence is linked to the presence of suitable microhabitats, like moss patches, and their life strategy can make them less likely to be affected by general climatic conditions. However, bioclimatic variables used in the study may be a good predictor of the possibility of the occurrence of suitable microhabitats. We investigated the possible distribution of P. fairbanksi and compared it with other widely distributed species of the genus Paramacrobiotus, i.e., P. gadabouti. Paramacrobiotus fairbanksi already reported from various continents exhibit a cosmopolitan distribution covering different types of environments, whereas P. gadabouti, although also potentially cosmopolitan, has a clear affinity to areas with a Mediterranean climate. Its distribution is poorly known due to lack of sampling in many habitats. Such differences clearly show us that even when we consider some of the species to be cosmopolitan, specific patterns of distribution can be completely different. However, we must also stress that the number of known localities for both species is relatively low and, in the future, when the number of records of these species will be higher, a distribution pattern may look different.Ecological niche modelling is an important and useful tool that has been used to address issues in many fields of basic and applied ecologyParamacrobiotus fairbanksi described originally from Alaska, USA, is now known from almost all zoogeographic realms. The identification of this species is still possible based on morphometric characters alone because the morphometric data are shown to not affect the species identification because of the overlap in measurements of all measured structures. Moreover, the analysis shows low genetic variability among P. fairbanksi populations from various geographical locations, which may in general suggest that interspecies genetic variability in tardigrades is very low too or could be’ the effects of Wolbachia infection. The species fits the ‘Everything is Everywhere’ hypothesis and is an example of a parthenogenetic species with wide distribution. Despite very low genetic variation, some indiscrete morphological variations were observed. Since all the studied populations were cultured and bred in the same laboratory conditions, such variation may have been caused by epigenetic effects, and were not the result of different temperatures, food sources and seasonality.Supplementary Information 1.Supplementary Information 2.Supplementary Information 3.Supplementary Information 4.Supplementary Information 5.Supplementary Information 6.Supplementary Information 7.Supplementary Information 8.Supplementary Information 9.Supplementary Information 10.Supplementary Information 11.Supplementary Information 12.Supplementary Information 13.


The Hui people are the second-largest ethnic minority in China, and they are distributed throughout the country. A previous study explored the paternal genetic structure of the Hui population in nine different regions of China, but it overlooked the Liaoning province. In this study, we examined the paternal genetic makeup and forensic traits of the Hui population in Liaoning province by analyzing 157 Y-chromosome single nucleotide polymorphisms (Y-SNPs) and 26 short tandem repeats (Y-STRs). We successfully genotyped 282 unrelated male individuals from the Hui population of Liaoning province using the SNaPshot® single base extension assay and Goldeneye™ Y26 system kit . The results revealed high haplotypic diversity (0.9998) and identified 46 terminal haplogroups for the Hui population. Additional analyses, such as heat maps, principal component analysis (PCA), genetic distance (FST), Multidimensional scaling (MDS) analysis, and median-joining network (MJ) analysis, showed that the Hui population could be classified into three groups: Northwest Hui populations (NWH), including Liaoning, Xinjiang, Qinghai, Gansu, Ningxia, Shaanxi, and Henan; Hui populations from Sichuan and Shandong (SSH); and Yunnan Hui populations (YNH). Pairwise genetic distance (Rst) comparisons with other Chinese populations revealed that the Hui population displayed genetic affinity with the Han population. The comprehensive understanding of the Hui population in Liaoning province, explored by Y-SNPs and Y-STRs, can be utilized to interpret their genetic structure and enhance the accuracy of forensic databases.The online version contains supplementary material available at 10.1186/s12864-023-09774-8. The ancestors of the Hui came to China from Central Asia and Islamic Persia as handicraftsmen, merchants, scholars, and soldiers. This human movement started in the seventh century and continued until the thirteenth century. After settling in China, they intermingled with Han Chinese, Mongols, and Uyghurs, ultimately assimilating their phenotype, cultural characteristics, and language into Chinese culture. In Liaoning province, the Hui population represents only 0.632% of the population and is the fourth largest ethnic group after Han (83.94%), Manchu (12.88%), and Mongol (1.60%) [Short tandem repeats (Y-STRs) and single nucleotide polymorphisms (Y-SNPs) on the male-specific Y chromosome are valuable genetic markers used in population genetics and forensic investigations. These markers have distinctive inheritance patterns that enable the identification of paternal lineages and the reconstruction of male ancestry , 2. Y-ST (1.60%) . Previou (1.60%) . Another (1.60%) . Our pre (1.60%)  showed a (1.60%) , 18. How (1.60%) , 20. In This study was approved by the Ethical Review Board of China Medical University in Shenyang, Liaoning Province, People's Republic of China, in accordance with the standards of the Declaration of Helsinki. Blood samples on FTA cards were randomly collected from 282 unrelated healthy male individuals of the Hui population living in Liaoning province for at least three generations. The aims and procedures of the study were explained to all volunteers, and they signed informed consent forms before participating.DNA was extracted from bloodstains collected on FTA cards  using the Chelex-100 method . DNA quaA total of 157 Y-SNPs were selected from elsewhere , represeNext, the PCR products were purified by adding 1 μl of exonuclease I and 2 μl of shrimp alkaline phosphatase (SAP)  Co., Ltd) to a 9 μl multiplex PCR product. The mixture was then incubated at 37°C for 60 min, followed by enzyme denaturation at 80°C for 10 min . This reFollowing the SNaPshot reaction, the reaction products were purified by adding 1.25 μl of SAP and incubating at 37°C for 60 min, followed by enzyme denaturation at 80°C for 10 min. Further analysis was performed by mixing 1 μl of the purified SNaPshot reaction product with 9.5 μl of Hi-Di formamide and 0.50 μl of LIZ-120 internal sizing standard . The mixture was then subjected to denaturation at 95°C for 3 min, followed by cooling to 4°C. The samples were separated on an ABI Prism 3100 Genetic Analyzer  using a 36 cm capillary array and the default instrument settings recommended by the manufacturer. The Goldeneye™ 26Y system kit , which contains PowerPlex Y23 loci and three additional Y-STRs , were co-amplified in a GeneAmp® PCR 9700  thermal cycler according to the manufacturer's recommendations . The 280th haplogroup, and n is the sample size. Heat map matrices were performed based on haplogroup frequency in the R program, and the ggplot2 module was used. Arlequin 3.5.2 [Haplogroup frequencies were calculated by direct counting and presented in pie charts using Microsoft Excel. Haplotype diversity was calculated according to the formula:in 3.5.2  was usedAllelic frequencies and haplotypes were calculated by the direct counting method, while haplotype diversity (HD) was calculated using the formula:S385a/b) , 11 lociS385a/b) , PowerplS385a/b) , Yfiler™S385a/b) , PowerplS385a/b) , GoldeneS385a/b) . The disS385a/b) . ReducedThe median-joining networks was constructed using NETWORK 5.0.0.3 `. We setThe genetic diversity of the study population, consisting of 282 self-identified Hui individuals from Liaoning, China, and their genotypic profiles are summarized in Supplementary Table The Hui population from Liaoning showed high haplogroup diversity with 46 terminal groups. The predominant haplogroups were O (57%), J (8.86%), C 8.51%), Q (8.15%) and D (5.31%) in Hui population from Liaoning. When we have combined our data with previously published data of Hui population , 99 dist%, Q  using Y SNPs and Y STRs between Hui population from Liaoning PR China and nine other Hui populations across China.Additional file 6: Supplementary Table S6. Pairwise Rst values  and P values  for Hui population from Liaoning and other relevant population across China.Additional file 7: Supplementary Figure 1. Phylogenetic tree showing Y-haplogroups found in the ten Hui populations.Additional file 8: Supplementary Figure 2. Interactivity test between Hui population from Liaoning PR China and nine other Hui populations across China.Additional file 9: Supplementary Figure 3. Heatmap analysis between Hui population from Liaoning and other relevant population across China.Additional file 10: Supplementary Figure 4. Principal component analysis between Hui population from Liaoning and other relevant population across China.