Rhizophora apiculata, which is one of the most widespread and economically important species in tropical Asia. In Malaysia, there has been an alarming decline in R. apiculata populations driven primarily by anthropogenic activities. However, the lack of genetic and demographic information on this species has hampered local efforts to conserve it. To address these gaps, we generated novel genetic information for R. apiculata, based on 1,120 samples collected from 39 natural populations in Peninsular Malaysia. We investigated its genetic diversity and genetic structure with 19 transcriptome and three nuclear microsatellite markers. Our analyses revealed a low genetic diversity (mean He: 0.352) with significant genetic differentiation (FST: 0.315) among populations of R. apiculata. Approximately two-third of the populations showed significant excess of homozygotes, indicating persistent inbreeding which might be due to the decrease in population size or fragmentation. From the cluster analyses, the populations investigated were divided into two distinct clusters, comprising the west and east coasts of Peninsular Malaysia. The western cluster was further divided into two sub-clusters with one of the sub-clusters showing strong admixture pattern that harbours high levels of genetic diversity, thus deserving high priority for conservation.Worldwide, many mangrove species are experiencing significant population declines, including  The mangroves, which form the habitat for hundreds of species at all levels of near-shore food webs, provide numerous ecosystems functions such as storm surge protection and carbon sequestration for climate change mitigation3. However, in recent decades, mangrove populations have plummeted owing mainly to various anthropogenic activities, which contribute to widespread mangrove forest degradation through land clearing, illegal logging and the over-exploitation of their highly valuable wood5. These were evident with around 16% mangrove species are in danger of extinction6.Southeast Asia holds the greatest diversity of mangrove species in the world7. Given that populations with a lack of genetic diversity often exhibit a greater risk of extinction8, examining the genetic diversity patterns of the threatened mangrove populations will be the key to ensure their long-term survival. The patterns of genetic diversity in a population can be shaped by both natural (evolution) and environmental events such as human-induced climate change. Unveiling insights into the mechanisms underlying these patterns are crucial to ensure informed conservation and management of the threatened species.Habitat fragmentation can affect the genetic structure of a species, primarily by increasing levels of genetic drift and inbreeding within populations, which consequently reduces the genetic diversity within the gene poolRhizophora is the most widely distributed species among all the mangroves species9. Among them, Rhizophora apiculata is a dominant commercial mangrove species that plays important ecological and economic role in Malaysia10. Locally known as Bakau Minyak, this species is preferred for its hard, strong and heavy wood, harvested mostly for wood chips, furniture, and charcoal12. While the population size of R. apiculata has been reduced dramatically over the past few decades13, little is known about the population genetics of this species. Previous work on the genus Rhizophora revealed low genetic diversity and high genetic differentiation, which seemed to be common traits for mangroves18. However, as most studies aimed to cover a large geographical area, sampling was not thorough, e.g. for Malaysia, only a few populations were chosen to represent the country (see18). The genetic information generated from a few populations is not sufficient to develop sound conservation plans for the species in Malaysia.R. apiculata using next generation sequencing (NGS) approach, to assess its level of genetic diversity and population differentiation throughout Peninsular Malaysia. Microsatellite markers have been widely used for population analyses because of their co-dominant inheritance and high degree of polymorphism (for recent work see20). The markers developed in this study will provide a detailed genetic diversity database of R. apiculata which can facilitate the formulation of conservation guidelines in Peninsular Malaysia.Here, we developed a new set of genic microsatellite markers (EST-SSR) in R. apiculata via PCR amplification and fragment analysis. Nineteen out of 46 primer pairs which showed clear genetic polymorphisms along with three other primer pairs  previously developed for R. mucronata21 were selected , followed by trinucleotide  and tetranucleotide microsatellites . Three highest frequencies of dinucleotide motifs that were detected were CT (16.80%), AG (16.68%) and TC (13.45%). Out of the 60 primer pairs tested, 46 yielded successful amplification. These primers were then used to screen 24 individuals of R. apiculata based on the 22 polymorphic microsatellite markers are listed in Table Aa) ranging from 2.3 to 4.6 alleles for all samples, with an average of 3.2 alleles per locus. The mean values for observed heterozygosity (Ho) and expected heterozygosity (He) were 0.299 and 0.325, respectively. The expected heterozygosity (He) at the population level ranged from 0.247  to 0.503 (Muar). The allelic richness (Rs) ranged from 2.07 to 3.63, showing marginal differences among the populations investigated. All loci deviated from Hardy–Weinberg equilibrium (HWE), with heterozygote frequencies being either lower or higher than expected (Table FIS) ranging from 0.007 to 0.450. Of that, 66.7% (26 populations) were found to be statistically significant (p < 0.05), mainly of the populations with disturbed habitat, either due to logging for firewood, charcoal production and construction (Telok Gedong and Merchang) or development for human settlement, aquaculture, ecotourism, road construction and land use for plantation . There were only two populations with negative FIS values  or excess of heterozygotes but were not statistically significant (p < 0.05) (Table Descriptive statistics for the 39 populations of HT = 0.532) was partitioned within population (HS = 0.370) (Table FST) ranged from 0.079 to 0.638, while those for the Slatkin’s divergence parameter (RST), varied from 0.038 to 0.617. The proportion of genetic variation distributed among populations (GST) was estimated at 0.305, indicating that 30.5% of genetic variability was distributed among populations (Table FST (0.315) estimate was slightly higher than GST and was significantly greater than zero (p < 0.05), while the mean RST (0.242) was lower than FST   and South China Sea   and Sub-cluster 1b (populations 20–27)  corroborates with the STRUCTURE analysis, whereby the 39 populations were also divided into two distinct clusters Fig. d, i.e. CWhen the 39 populations were grouped based on the two main clusters, AMOVA revealed that 45% of the variation was apportioned between the western and eastern regions of Peninsular Malaysia, 13% among populations within regions, and 42% within populations (Table Avicennia marina)25, downy oak (Quercus pubescens)26 and crape myrtle (Lagerstroemia spp.)27. A total of 19 transcriptome-based microsatellite markers (EST-SSR) were developed in this study. To increase the number of markers for genotyping, three additional nuclear microsatellite markers (gSSR) which were previously developed for R. mucronata21 have been validated and utilised in our study. Increasing the number of polymorphic loci can greatly enhance the precision of estimates of genetic distance28. The high cross-species transferability of microsatellite markers between R. apiculata and R. mucronata has previously been demonstrated9.From our transcriptome data, we identified a total of 18,674 microsatellites, with dinucleotide repeat motifs (85.13%) being the most frequent type of microsatellite. Similar observations, whereby dinucleotides was the most abundant motif in the plants’ genomes, have been reported for other tree species such as grey mangrove 9, R. stylosa (He = 0.321)9, and Sonneratia alba (He = 0.280)29. The low level of genetic diversity occurring within R. apiculata populations suggests that this species may have experienced severe habitat fragmentation or population size reduction.Generally, low genetic diversity is common in mangrove plant species particularly the FIS) in most of the R. apiculata populations, consistent with the observed habitat destruction found in most of these populations , causing extensive over-exploitation of the species34. Owing to this, decline in effective population size and aggravate loss of genetic diversity ultimately reduced resilience of populations to anthropogenic climate change35. The genetic fragility in R. apiculata is of concern, considering that future impacts of environmental changes, whether natural or otherwise, will likely to further reduce its genetic diversity and threaten its long-term viability.F-statistics36 is among the most common methods used to estimate the level of heterozygosity in a population. The FST is more sensitive in detecting intraspecific differentiation as compared to its analogue, the RST38. The RST, however, is thought to be a better predictor for interspecific divergence because it can effectively reflect the mutation patterns of microsatellites39. Therefore, both models were applied in the present study, revealing a strong population genetic structure of R. apiculata . We found that approximately 68.5% and 31.5% of genetic variations were distributed within and among R. apiculata populations, respectively. Other mangrove studies also revealed high population differentiations, namely in Avicennia marina (0.410)25, Ceriops tagal (0.529)40, and A. germinans (0.410)41.Wright’s 42. The ocean current movements along the Straits of Malacca and South China Sea are highly dependent on the monsoon winds during the north-east (December–January) and south-west (June–July) monsoons33. This enables the mangroves propagules to float in ocean water for an extended period and follow the ocean currents, transported from the source to the sink43. Due to the shallow waters at water depth ~ 30 m, which is narrow in the southern part of the Straits of Malacca before meeting the South China Sea42, the propagules of either region travelled to the sink population and formed the observed admixed populations (Sub-cluster 1b).All the three cluster analyses performed in this study showed similar results, whereby the 39 populations were divided into two major geographical clusters , with strong admixture pattern observed between southern part of western and eastern regions of Peninsular Malaysia  method46 and purified using High Pure PCR Template Preparation Kit ver. 20 .Sampling was carried out along sheltered coasts of Peninsular Malaysia, where R. apiculata sampling sites have experienced some form of anthropogenic activities either due to logging or development  bases and more than 50% low-quality bases in raw reads were filtered out from the raw data set.The total RNA was extracted using Qiagen RNeasy kit  and purified using the TURBO DNA-free kit . The quality of RNA sample was then checked using NanoDrop 2000 spectrophotometer . Transcriptome sequencing was carried out on an Illumina HiSeq 4000 sequencer  with default parameters at Novogene Bioinformatics Technology Co. Ltd. . The raw data underwent quality checking, trimming, and assembling using FastQChttps://pgrc.ipk-gatersleben.de/misa)50 was used to identify microsatellite sequences of di-, tri, and tetranucleotide motifs. Markers were then designed with Primer3 (https://bioinfo.ut.ee/primer3-0.4.0/)51. We used the following criteria for marker selection: microsatellite motif length of ≤ 30 base pairs (bp); amplicon size of between 80 and 400 bp; and rejecting markers and amplicons with multiple mononucleotide repeat sequences. Based on these criteria, 60 primer pairs were synthesised and those that showed clear polymerase chain reaction (PCR) products on 1.5% agarose gel were fluorescently-labelled at the forward primer with HEX or 6-FAM. We performed PCR on a GeneAmp PCR System 9700  in a final reaction volume of 10 μL. The PCR thermocycling parameters consisted of an initial denaturation step of 4 min at 94 °C followed by 40 cycles 94 °C for 1 min, 55 °C annealing temperature for 30 s, and 72 °C for 40 s, and the final extension step at 72 °C for 30 min. The PCR products were genotyped on an ABI 3130xl Genetic Analyzer  with ROX400 as the internal size standard. The alleles were scored using GeneMarker v2.6.4 . The assembled contig sequences of the successfully developed microsatellite markers were assessed for reliability by blasting them to the R. apiculata genome sequence22 using BLASTN.MicroSAtellite program  and linkage disequilibrium (LD) using Fisher’s exact test in Genetic Data Analysis (GDA) v1.153. The sequential Bonferroni’s correction was conducted to adjust critical values for multiple comparisons, with a significance level of 5%54. Allelic frequencies for each locus in each population were obtained. The levels of genetic diversity within each population were estimated using Microsatellite Toolkit55 based on several parameters, including the average number of alleles per polymorphic locus (Aa), effective number of alleles per polymorphic locus (Ae), observed heterozygosity (Ho), and expected heterozygosity 28. Allelic richness (Rs) was estimated using FSTAT v2.9.356 and GDA v1.1, respectively. On the other hand, the inbreeding coefficient (FIS) was calculated using FSTAT v2.9.356, and its significance was tested with GDA v1.1. Additional statistics, such as polymorphic information content (PIC) and Nei’s genetic distance (Nei’s DA)57, were calculated using POWERMARKER v3.2558.Micro-Checker software was used to detect possible genotyping errors and null allelesR. apiculata populations using the molecular fixation index (FST)59, the divergence parameter (RST)38, and Analysis of Molecular Variance (AMOVA), which were all determined by GenAlEx v6.5 at the significance level of 5%60. A Mantel test based on 9,999 permutations was carried out to examine if there was correlation between geographical distance and genetic differentiation , by analysing the Isolation-by-Distance (IBD) in GenAlEx v6.5. To infer the populations’ genetic structure, we applied a model-based Bayesian clustering method using STRUCTURE v2.3.161. Dataset was explored using admixture model, which can detect structure among populations that are potentially similar due to shared ancestry or migration, with a burn-in of 250,000 steps followed by 850,000 Markov Chain Monte Carlo (MCMC) iterations. The StructureSelector software62 was then used to select and visualise the optimal number of clusters (K) in order to identify the highest level of genetic division hierarchy. Additionally, principal component analysis (PCA) was carried out using PCAGEN v1.263 to assess the goodness-of-fit between simulated and real datasets, visualizing genetic distance and relatedness between populations in a two dimensional (2D) standard plot. To complement the analysis of the population structure, a UPGMA dendrogram was constructed based on Nei’s DA using MEGA v5.064. Bootstrap of 1,000 times was applied to acquire a reliable tree with correct branch topology.We also analysed the levels of genetic differentiation in Supplementary Information 1.Supplementary Information 2.


Cyt‐b gene, microsatellite (SSR), and single nucleotide polymorphism (SNP) data to evaluate the demographic history and genetic structure of the eastern golden frog (Pelophylax plancyi), by sampling 407 individuals from 15 local populations across Shanghai, China. All local populations experienced bottlenecks during historical urbanization, while the local populations in urban areas maintained comparable contemporary effective population sizes (Ne) and genetic diversity with suburban and rural populations. Nevertheless, the rapid modern urbanization has already imposed significant negative effects to the integrity of populations. The 15 local populations were differentiated into eight genetic clusters, showing a spatial distribution pattern consistent with the current urbanization gradient and island–mainland geography. Although moderate gene flow still occurred from the rural peripheral cluster to urban and suburban clusters, population fragmentation was more serious in the urban and suburban populations, where higher urbanization levels within 2‐km radius areas showed significant negative relationships to the Ne and genetic diversity of local populations. Therefore, to protect urban wildlife with limited dispersal ability, improving conditions in fragmented habitat remnants might be most essential for local populations living in more urbanized areas. Meanwhile, we highlight the need to preserve large unfragmented rural habitats and to construct corridor networks to connect discrete urban habitat remnants for the long‐term wildlife conservation in intensively urbanizing environments.Understanding the mechanisms of how urbanization influences the evolution of native species is vital for urban wildlife ecology and conservation in the Anthropocene. With thousands of years of agriculture‐dominated historical urbanization followed by 40 years of intensive and rapid urbanization, Shanghai provides an ideal environment to study how the two‐stage urbanization process influences the evolution of indigenous wildlife, especially of anuran species. Therefore, in this study, we used mitochondrial  Huangpu River, the largest river in Shanghai, flows through the mainland area, dividing it into eastern and western parts. We collected 407 samples of P. plancyi across 15 sampling sites , the 15 sampling sites were categorized into urban, suburban, and rural groups . Each pool was amplified using 14 PCR cycles in 25 μl reactions containing Phusion High‐fidelity PCR reagents, library DNA, and a unique indexing primer for each pool following the standard Illumina multiplexed sequencing protocol. DNA libraries were quantified using the high‐sensitivity DNA analysis kit in a 2100 Bioanalyser (Agilent Technologies). Pools were combined in equimolar concentration and sequenced in Illumina HiSeq 2500 2 × 150 bp pair‐end sequencing by Personal, Shanghai, China.Ten samples were randomly selected from each sampling site, so a total of 150 individuals were used for SNP data collection by double‐digest RADseq (ddRAD). Genomic DNA was extracted using the hexadecyltrimethylammonium bromide (CTAB) method. Double‐digest restriction‐associated DNA libraries were prepared using 500 ng of DNA per sample following the protocol described by Peterson et al.  with somm) to four when creating a stack, and setting the maximum distance (in nucleotides) between stacks (M) to two in ustacks. The number of mismatches allowed between sample loci (n) was 2 when building a catalog in cstacks. In the populations module, retained SNP loci had to be present in >75% (r) of the 150 individuals, and in at least 12 (p) of the 15 local populations with a minimum minor allele frequency (min_maf) of 0.05. In total, 71,910 SNP loci were obtained using the above parameters. An extra parameter (write_single_snp) was added to retain only the first SNP locus of each read; thus, a 44,469 SNP loci subset was kept to avoid linkage disequilibrium in the population structure analyses. To avoid the impacts of missing data and compromise with the computation limitation of the program, another subset with 1,611 SNP loci without missing alleles was obtained for gene flow analyses.FastQC v0.11.7 Andrews,  was used2.4P. plancyi samples in the laboratory. The quantity and quality of extracted DNA were verified by electrophoresis in 1% agarose gel. All individuals were sequenced at a partial fragment of the Cyt‐b gene using the primers (B104F and B829R) and the PCR conditions described by Liu et al. (Genomic DNA was extracted using a Genomic DNA Tissue Kit (Tiangen Biotech) from all 407 u et al. . PCR pro2.5P. plancyi  showed deviation from HWE in more than half of the 15 local populations, and thus, were deleted; 13 SSR loci were retained for further analysis.All 407 individuals were genotyped at the 15 SSR loci. GENEMAPPER v4.0 (Applied Biosystems) was used to perform allele scoring. We randomly selected 10% of all samples to carry out a second amplification to confirm the accuracy of genotyping. The primer information and thermal cycling details are listed in Table 2.6VarEff v1.2  was used with an additional coefficient (C) of 0.22, as recommended by Peery et al.  and of the strongest bottleneck effect (TMG) were evaluated in each local population. For Tbot, a bottleneck was considered to start once there had been a 5% loss of the initial effective population size. TMG was the time when the bottleneck showed the strongest effect and caused the fastest declining rate in each local population.The R package y et al. . For eacy et al.  which waTanc ≤ 5,000; 10 ≤ Tbot ≤ 500; 1,000 ≤ Nanc ≤ 5,000; and 10 ≤ Nbot ≤ 1,000; contemporary effective population size (Ne) was set with default parameters. We generated 1 × 106 simulations for each scenario. Three single‐population summary statistics for the 5,000 randomly selected SNP loci were chosen to perform simulations: (a) mean and (b) variance of gene diversity across polymorphic loci, and (c) mean gene diversity across all loci. Using a polychotomous logistic regression, the optimal scenario was chosen with the highest posterior probability value calculated with 1% of simulated data sets closest to the observed data sets. We then selected the 1,000 closest‐to‐observed pseudo‐observed data sets (PODs) to evaluate the posterior predictive error rate for the optimal scenario. Posterior parameter estimation was performed for the optimal scenario on the 1% of closest‐to‐observed PODs. Using the Model Check option, we ran the principal component analysis (PCA) to assess the goodness of fit of the optimal scenario from the set of 10,000 PODs simulated from the posterior predictive parameter distributions. For quantifying confidence of parameter estimations, the bias and precision of parameter estimates were assessed with 1% PODs drawn from posterior distributions.For SNPs, DIYABC v2.1.0 , haplotype diversity (h), and nucleotide diversity (π) for each local population. For SSRs, GenAlEx v6.503  and the observed heterozygosity (HO). For SNPs, the populations module in Stacks was used to calculate HO, π, and the mean frequency of the most frequent allele at each locus (PM) in each local population concerning only the variant sites across the reads .For 2.8FST between local populations. For SNPs, vcftools v0.1.17  and aligned with P. plancyi sequences using MEGA v7  to present the best BI tree. TCS v1.21  from 1 to 15 with 1 × 106 burn‐in and 2 × 106 MCMC iterations for each run. The optimal K value was derived by the ΔK statistic  and SNP (STRUCTURE) analyses (see details in Results part). Using BayesAss3  to the urbanization gradient as 1 for urban, 2 for suburban, and 3 for rural.To test whether the local scaled UI showed a consistent trend with the cityscape urbanization gradient, we used a linear regression model (LRM) to test the relationship between UI and the urbanization gradient where the sampling site was located. To do so, we assigned values (GA) and local (UI) scales. The genetic variation indices of each local population as dependent variables involved in LRMs included all genetic diversity indices and contemporary effective population sizes (Ne) calculated by SSRs and SNPs, and the urbanization level was the independent variable. Given that all the genetic variation indices tend to be correlated, and we wanted to test their relative priority of reaction to the urbanization, only one index in each LRM simulation was tested.Moreover, LRMs were used to evaluate the relationships between genetic variation and the urbanization level at both the cityscape (http://www.r‐project.org/), and the power of LRMs was evaluated by adjusted R2.All statistical analyses were performed using R v3.5.1  ranged from 2,067.5 to 5,212.2, while the contemporary effective population sizes (Ne) decreased to a range from 218.6 to 569.4 (Table Tbot), except for GQ, where the bottleneck started 588 generations/years ago  of all local populations was 452 ± 261.3  generations/years ago. The maximum magnitude of bottleneck effect (MG) showed a moderate decrease of 7.8 ± 2.8 (2.7–13.8) individuals per generation/year  to the smallest  through bottleneck effects that happened almost 400 years ago, except for 73.4 years ago in CS  and followed by recovering Ne  of local populations ranged from 4 to 13. Most of the local populations had haplotype diversity (h) that ranged from 0.583 to 0.897, although LG showed the lowest value of 0.470 (Table NA) ranged from 6.077 to 8.769. The observed heterozygosity (HO) ranged from 0.559 to 0.664 (Table PM) ranged from 0.821 to 0.843; HO was similar, at ~0.214 (± 0.024) with the highest detected in WG (0.301) and the lowest in BG (0.197); and π ranged from 0.230 to 0.268  and in the two islands (PS and CJ) showed higher differentiation than the other local populations .Pairwise ns Table . The FSns Table . Neither3.4Cyt‐b fragment were obtained from 364 individuals. Among these haplotypes, H1 and H3 were the two main haplotypes, with 53 and 151 individuals, respectively , three urban clusters , two suburban clusters , and one big peripheral cluster containing all the other local populations  and SNPs (STRUCTURE), the 15 local populations were categorized into eight genetic clusters as follows: CP, BG, GQ, CS, WG, PS, CJ, and a peripheral cluster including the local populations of SN, PJ, XY, JB, QX, LX, BF, and LG . Linear regression model (LRM) showed that UI decreased significantly along the cityscape gradient from urban to rural areas (regression coefficient (RC) = −0.223, Radj2 = 0.321, p = .016; Table According to the PCA of the seven landscape variables Table , the UI NH of mtDNA , NA of SSRs , and π of SNPs  showed significant negative relationships with UI . Neither genetic diversity nor Ne were detected to have significant regression relationship with urbanization gradient at the cityscape scale.Moderate, but significant negative relationships between genetic variations and UI were detected at the local scale. 4P. plancyi. The ongoing population fragmentation of this anuran species with limited dispersal ability provides a good example to discuss the conservation biology of native wildlife in intensively urbanizing environments.Urbanization is one of the most important impacts of human development in the 21st century. Although populations have been shown to adapt to urban environments, urbanization frequently has negative effects on the movement, demography, and genetic diversity of populations , and consequently, causes different intensities of genetic drift between local populations in areas with different urbanization levels. In the lower Yangtze River areas, agricultural development and urbanization have had substantial environmental impacts since 2800–2200 B.P. .In amphibians, their aquatic‐terrestrial biphasic life cycles and limited terrestrial dispersal ability usually cause them to be more vulnerable to the severe habitat fragmentation caused by modern urbanization  populations  and side‐blotched lizard (Uta stansburiana) populations in Los Angeles . Yue . Yue  found thy Figure .P. plancyi populations, the correlation between the distribution of the mainland genetic clusters with modern city development . However, we did not observe significant genetic differentiation between the west and east sides of the Huangpu River Figures  and 5. B4.4P. plancyi (Huang et al., P. plancyi being the most abundant and widely distributed anuran in Shanghai (Gu, Ne values of the 15 sampled local populations (Table Protecting wildlife in urbanized areas is important not only for conservation, but also for a better and healthier urban ecosystem (Yang et al., ghai Gu, . In thisns Table  suggest ns Table , strategP. plancyi adults are available, Smith and Green (Ne (Table Many studies have suggested the importance of protecting the core habitat area based on philopatry and the limited migration ability of adult amphibians (reviewed by Cushman, nd Green  reportednd Green  suggestend Green  and amphnd Green . There and Green  with an e Table  and compe Table  of the lAlthough core habitat area protection might be effective for urban amphibian conservation, a larger scale habitat matrix to support larger populations with rich genetic exchange will be more precious (Semlitsch, P. plancyi and other amphibian species in Shanghai City, the importance of environmental factors, such as forest and wetland composition (Zhang et al., Maintaining gene flow between populations is important for the long‐term persistence of populations (Miles et al., P. plancyi, knowledge of their dispersal behavior is limited (Smith & Green, To the majority of amphibian species including 5P. plancyi could have already begun more than one thousand years ago during the historical low‐level urbanization dominated by agriculture, while the intensive modern urbanization for dozens of years more significantly influenced the gene flow among local populations and caused urban wildlife population differentiation along the urban‐to‐rural gradient. However, urban local populations can still keep comparable Ne and genetic diversity with those in rural areas, which suggested that protecting core habitat areas would be an effective method to maintain local populations of urban wildlife species with limited dispersal abilities. Nevertheless, for long‐term conservation planning and management plan, a corridor network to maintain gene flow between local populations in the large rural agricultural areas and discrete urban local populations is imperative.In this study, we confirmed that long‐term urbanization could influence the population genetics of native wildlife species in different stages during a process of thousands of years, resulting in profound evolutionary and conservational consequences to the urban wildlife. Population bottlenecks of wildlife species with limited dispersal ability like None declared.Supplementary MaterialClick here for additional data file.


In the main distribution area the genetic pattern of silver birch is dominated by two haplotypes: haplotype A located in the western and north-western Europe, and haplotype C in eastern and southeastern Europe, characterized by high levels of neutral genetic variability within populations, and low differentiation among populations. Information about the amount and structure of genetic variation in the southern marginal areas, representing rear populations left during the expansion of this species from southern glacial refugia, are lacking. The general aim of the study was to investigate the existence of the climatic characteristics typical of the environmental niche of the species, jointly to genetic organization, variation and gene flow, in marginal populations on the Italian Apennines and Greek Southern Rhodope and compare them with populations of the southern part of the main distribution range on the Alps and Balkans. Genetic analysis was performed using nuclear microsatellites loci on 311 trees sampled from 14 populations. Environmental analysis was performed on the multivariate analysis of derived climatic variables. The allelic pattern was analyzed to assess genetic diversity, population diversity and differentiation, population structure and gene flow. The geographic and environmental peripherality did not always match, with some Apennine sites at higher elevation enveloped in the environmental niche. In the peripheral populations on the Apennines, we observed a lower genetic diversity and higher differentiation, with evident genetic barriers detected around these sites. These characteristics were not shown in the marginal Greek populations. Unexpectedly, the southern Italian marginal populations showed genetic links with the Greek and central area of the distribution range. The Greek populations also showed evident gene flow with the Alpine and Balkan areas. The disparity of results in these two marginal areas show that it is not the geographic peripherality or even the ecological marginality that may shape the genetic diversity and structure of marginal populations, but primarily their position as part of the continuous range or as disjunct populations. This outcome suggests different considerations on how to manage their gene pools and the role that these rear populations can play in maintaining the biodiversity of this species. Geographical distribution of European tree species and their genetic structure are the result of the climatic oscillations throughout the Quaternary . Many stBetula pendula Roth) is a diploid (2n = 28), monoecious, wind-pollinated tree with small seeds that rapidly recolonize open areas. Its current distribution range covers central Europe, the Balkans and northern Europe, where the distribution is nearly continuous in pure stands and mixed forests. In the western and southern parts of the range, as in the Italian Apennines and southern Rhodopes (northern Greece) the distribution is patchier and occurs mostly at higher altitudes  monthly data (0.5° resolution) to scale-free point data  accounting for as much as possible of the variance in environmental data, avoiding collinearity between variables, an expected issue in ecological analysis.The sampling sites covered a gradient from the Alps to Sicily and to Greece . Populatint data  and calcint data  and withint data  by the d®) and diluted to 5 ng/μl.A total of 311 individuals were randomly sampled from the 14 populations . Leaves ® pro. Each sample was amplified in a 12.5 μl total volume reaction according to the QIAGEN Type-it® Microsatellite PCR kit. The cycling protocol included: 95°C for 5 min; 28 cycles at 95°C for 30 s, 57°C for 90 s, 72°C for 30 s; 60°C for 30 min. 1 μl of each amplification product was added in a mixture of 20 μl formamide (Applied BiosystemsTM) and 0.3 μl GeneScanTM 500 LIZTM, and denatured at 95°C for 5 min. Samples were run on ABI Prism 3130 Avant DNA sequencer (Applied BiosystemsTM). Results were analyzed using the GeneMapper® Software v4.1 (Applied BiosystemsTM), and allelic profiles were scored by automatic binning and visual checking.Samples were analyzed with a set of eight polymorphic markers  developeNA), and effective (NE) alleles; observed (HO) and expected (HE) heterozygosity (GENEALEX v6.5 (FIS) for each population and the fixation index (F) at each locus were obtained by computing a hierarchical AMOVA using ARLEQUIN v3.5.2.2 (AR) and the number of private alleles (PA) were computed using the rarefaction method with HP-RARE software (FST) was estimated in GENEALEX v6.5 ; each set of populations is then sampled, a test for genetic homogeneity is applied, and the proportion of significant outcomes is used to estimate the power (the chance of detecting the minimum amount of genetic differentiation) under the actual conditions. We set the program with an effective population size Ne = 150, number of generation t = 35 and 500 runs. To delineate the major ordination pattern of birch populations based on a multivariate approach, a discriminant analysis of principal components (DAPC) was performed by R  in the R Studio environment . To test if any isolation by distance (IBD) has been occurred, correlation between genetic distance and geographic distance was tested in GENEALEX v6.5 by the Mantel test, with 999 permutations.In order to assess the level of genetic diversity at the population level, measures of intra-population and inter-population genetic parameters were assessed by different approaches. The number of observed . We applied the three single-sample methods, namely the linkage disequilibrium (LD), heterozygote-excess (HE) and molecular coancestry (MC), as implemented in the software NEESTIMATOR v2.1 . The most likely number of clusters was determined by the Evanno method  in R  of the genetic relationship of populations, implemented in EDENetworks v2.18 (FST). EDENetworks illustrates the distribution of links among populations using percolation theory and without an a priori hypothesis based on population identity or sampling location. The percolation theory allows for the splitting of a fully connected network into discrete clusters, and the critical threshold distance is known as the percolation threshold  varied between 3.8 and 7.9  and to the core populations ITN1, ITN2, ITN3, and SRB . The three Balkan populations did not differ in terms of AR (on average 7.2).On average, Italian MaP populations showed a lower level of PA; PA equal to 0.35, but this value decreased along the North Apennines - Central Apennines gradient from ITC1 to ITC5 and then it rose again in ITS1 and ITS2. A low value of PA was recorded in Greek populations (on average 0.18). Southern core populations ITN1, ITN2, ITN3, and SRB showed a mean number of PA equal to 0.31.The mean number of private alleles PA;  ranged bHE; HE equal to 0.71 was detected; ITC3 had the highest HE (0.80), while ITC6 and ITC5 presented the lowest values . Greek MaP populations (GR1 and GR2) tended to show a higher HE, compared to Italian MaP populations (0.79 vs. 0.71); In addition, their HE was not significantly different from that of the Alpine and SRB populations (both averaged 0.79).The level of heterozygosity HE;  was on aFIS; FIS for the Italian MaP populations was on average 0.036. A significant departure from FIS = 0 was measured in ITC6. In Greek MaP populations, FIS averaged 0.062. In the Alpine and Serbian populations, FIS was 0.062 and 0.026, respectively.The inbreeding coefficient FIS;  ranged bPOWSIM, applied to the 14 populations sampled in this study, with an Fst = 0.11 and 8 SSR markers, resulted in a significant power of 1. When the drift steps were omitted (t = 0), the probability of error when assuming divergence among populations was α = 0.04.The power analysis by The cluster analysis DAPC;  showed tFST = 0.146, p < 0.05), while diversity within populations (FIS = 0.022) resulted not significant. The other cluster ITS1 – ITS2 – ITN1 – ITN2 – ITN3 – SRB – GR1 – GR2 .Based on this evident existence of two main clusters, the analysis of molecular variance AMOVA;  was perfR1 – GR2  presenteFST pairwise population comparison  of 0.11.The mparison  revealedr = −0.27, p = 0.15). On the contrary, the transect along the Balkans, from northern Greece to SRB, throughout the Alps showed a weak positive significant correlation between geographic and genetic distances .Considering all the Italian populations (the Alps to Sicily transect), the Mantel test resulted in no correlation between geographic and genetic distances (NE) showed large values, with confidence intervals (CI) ranging to infinite in most cases and for all methods  and the other that included the southernmost Italian populations, the Alpine and the Balkan populations .The analysis  revealedk = 5 as the most likely group partitioning  was observed, with the Alpine populations sharing a common gene pool and the Apennines populations more differentiated among each other  generally presented a lower level of allelic richness and, to less extent, gene diversity compared to the putative central populations ITN1, ITN2, ITN3, and SRB. Differently from the Italian MaP populations, Greek MaP populations revealed a higher allelic richness and heterozygosity compared to the Italian ones and similar to the Alpine and Serbian populations. This pattern highlights that stochastic events, like genetic drift and low gene flow, might have affected the genetic diversity of the Italian MaP populations, while displays the overall favorable conditions of the Greek populations, in terms of genetic diversity. GR1 and GR2 reflect the other accepted hypothesis about the MaP populations and their level of gene diversity. In fact, according to other authors, marginal populations may harbor the bulk of genetic diversity at the species level  and in ITC6, concomitant with a fewer number of private alleles and allelic richness, while the highest genetic diversity was observed in ITC4, ITS1, and ITS2. The detection of a high level of private alleles, as observed in ITC1, may help to detect putative refugial region; newly colonized areas are characterized by low genetic diversity and lack of private haplotypes, as might be the case for ITC5. However, according to A slight gradient of diversity along the Apennines at the higher elevation was observed, with a high genetic diversity in the southern Italian MaP populations (ITS1 and ITS2), a lower value in ITC5 and a rise again toward ITC3 and ITC1. In a study on birch genetics by Two genetically different groups were distinguished, separating the six MaP populations in central Italy from the two southern Italian populations, which share their gene pool with Alpine, Serbian, and Greek populations. The separation of the six populations of the central Apennines from those in the southern Apennines resembles the result found for silver fir by Fagus sylvatica L.) populations in different European regions  in the Apennines and Balkans found genetic similarity between the southern Apennines and eastern European populations  or even the ecological marginality issue that may shape the genetic diversity and structure of MaP populations, but primarily their position as part of the continuous range or as disjunct populations. Greek populations, besides being at the edge of the natural distribution and in an ecologically marginal environment, retain the genetic characteristics typical of central populations due to their genetic connectivity with the rest of the natural continuous range. On the other hand, Italian MaP populations are clearly disjunct. Their genetic composition is the direct outcome of peripheral location and/or ecological marginality, compounded by disjunction and lack of gene flow. The results are important for the protection of the silver birch genetic resources in these areas. A future goal is to extend this study of putatively neutral genetic variation to an investigation of quantitative genetic variation in populations across the geographical range in order to gain a better understanding of the future adaptive potential of the southern and south-eastern silver birch populations.The datasets generated for this study are available on request to the corresponding author.GD, FD, and FA conceived and designed the study. GD, IG, EA, PB, and SS carried out fieldwork. AT processed samples, in collaboration with colleagues in CNR-IRET in Porano. GD, AT, and CM designed and performed the statistical analyses. GD wrote the original draft and all authors contributed in preparing the manuscript in its final form. All authors have read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Saccharina latissima, using microsatellites and double digest restriction site-associated DNA sequencing ( ddRAD-seq) derived single nucleotide polymorphisms (SNPs) to analyze the genetic diversity and structure in 11 sites spanning the entire European Atlantic latitudinal range of this species. In addition, we checked for statistical correlation between genetic marker allele frequencies and three environmental proxies . Our findings revealed that genetic diversity was significantly higher for the northernmost locality (Spitsbergen) compared to the southern ones (Northern Iberia), which we discuss in light of the current state of knowledge on phylogeography of S. latissima and the potential influence of the recent climatic changes on the population structure of this species. Seven SNPs and 12 microsatellite alleles were found to be significantly associated with at least one of the three environmental variables. We speculate on the putative adaptive functions of the genes associated with the outlier markers and the importance of these markers for successful conservation and aquaculture strategies for S. latissima in this age of rapid global change.Temperature is one of the most important range-limiting factors for many seaweeds. Driven by the recent climatic changes, rapid northward shifts of species’ distribution ranges can potentially modify the phylogeographic signature of Last Glacial Maximum. We explored this question in detail in the cold-tolerant kelp species  The extent and distribution of genetic variation within a species are of fundamental importance to its evolutionary potential, and determine its chances of survival. Assessments of genetic variation are therefore essential for the development of effective conservation strategies and for the management of genetic resources ,2.The spatial distribution of genetic diversity within and between populations is the result of gene flow, genetic drift, and natural selection. Historical events, like the succession of expansion and contraction in species’ ranges during the glacial period and afterwards during post-glacial recolonization, are thought to be a major factor influencing the genetic diversity patterns currently observed in a wide variety of organisms ,4. Such Elucidating the drivers of the genetic structure of populations observed across the range of a species thus requires a clear understanding of the relative influences of the historical processes resulting from stochastic demographic effects and the selective processes, particularly those linked to global warming. Specific regions of the genome can be affected by adaptive selection processes. Modern approaches in molecular biology allow to characterize this adaptive variation even in non-model organisms, providing tools to answer fundamental and applied questions in evolution and ecology ,16. The Laminaria digitata: [L. hyperborea: [L. ochroleuca: [Saccorhiza polyschides: [Saccharina latissima: [L. digitata: [Sargassum fallax and Scytothalia dorycarpa: [Kelp forests are considered as one of the most diverse and productive temperate and cold-water ecosystems ,21. For igitata: ,30,31,32erborea: ,33,34; Lroleuca: ; Saccorhschides: ; Sacchartissima: ,36,37,38igitata: ; Sargassrycarpa: ). The exrycarpa: .Saccharina latissima (Linnaeus) (sugar kelp) is a brown macroalga (Phaeophyceae) that belongs to the family Laminariaceae and has a circumpolar distribution. It is found in cold and temperate coastal waters of the lower intertidal with a lower depth limit of about 30 m [S. latissima forms largely continuous dense stands on rocky shores, occurring in both clear and murky waters, preferably in areas sheltered from strong waves [S. latissima’s range extends from Spitsbergen in the north to the northern part of Portugal in the south. Multiple studies suggested that S. latissima has a circumpolar origin [S. latissima ice age refugia  has been proposed based on ecological niche modelling [S. latissima genetic diversity but their sampling regime either did not account for the entire European range of this species (Iberian Peninsula to the Arctic Ocean) [S. latissima compared to the other proposed refugia currently is not clear. The dispersion and settlement of S. latissima propagules requires hard rocky substrate coastal environments and its populations cannot establish in places where there are long stretches of sandy coastline [S. latissima suggests the occurrence of local adaptation along its distribution range. Indeed, the presence of ecotypic differentiation between populations has been reported with regard to temperature  ,38, or toastline . The widlations, ; Arctic lations, ,47,48; slations, , and incS. latissima along the European coast in light of the previously hypothesized refugia areas, their putative role in post-glacial recolonization, and the importance of connectivity. We also conducted STF outlier analysis to identify loci potentially associated with several environmental variables at the Pan-European scale. Investigation of population genetic structure was performed using expressed sequence tag (EST)-derived [In this study we analyzed the structure and genetic diversity of -derived  and geno-derived  microsatS. latissima sporophytes were sampled between 2014 and 2016 at 11 sites situated along a latitudinal transect parallel to the European Atlantic coast. The transect ranged from northern Portugal (latitude 41.622) to Spitsbergen in the Arctic Ocean (latitude 79.334), covering both the putative LGM refugia of this species as well as the post-glacially colonized areas , except for samples from Ellenabeich (ELL) where the sporophytes were collected as drift material from the beach. As the sporophyte density was low at the sampling sites Castelo do Neiva (CAS) and Fermanville (FER), fewer than 15 individuals were collected from these localities. A small disc of tissue was cut at the base of the blade from each of the sampled individuals . Dried tissue samples were preserved in individual zip-locked plastic bags containing silica gel and stored at room temperature until DNA extraction.ed areas . S. lati® 96 II kit  following the manufacturer’s protocol. The lysis step was performed at room temperature rather than at 65 °C to minimize extraction of polysaccharides (which may interfere with PCR amplification). DNA extraction was performed on between 10 and 20 mg of dried tissue utilizing the NucleospinS. latissima individuals, a subset of which were used in this study, were sequenced in eight libraries, two of which were in part sequenced twice due to insufficient number of reads resulting from the initial sequencing effort. Three individuals were sequenced in each of the ten libraries to assess the consistency of the genotyping.Double digest restriction site-associated DNA sequencing (ddRAD-seq) library construction and sequencing  were performed as described in . A largeRead demultiplexing (process_radtags module), and locus assembly and variant calling (denovo_map.pl module), were performed in Stacks 1.40 . The popS. latissima sporophytes collected at ten sites were genotyped with the SSRs  within each locality (ISF) was computed with an exact test in genepop 1.0 utilizing dememorization = 100,000, batches = 5000, and iterations = 10,000.For each of the localities we computed several within-locality genetic diversity indices. Allelic richness (Ar) was obtained for each locus for the SNPs utilizing the allelic.richness function from R package hierfstat , whereasepop 1.0  R packagEH were plotted against the latitude of each of the localities. The significance of the correlation between these genetic diversity indices and the latitude was tested in R with a Pearson’s product-moment correlation. In order to estimate how the localities differed from one another in terms of within-locality expected heterozygosity, we performed a locus-by-locus pairwise Welch’s t-test among the examined localities . Corrections for multiple comparisons were performed using the p.adjust function in R to control for the false discovery rate (FDR) . FurtherSTF values amongst all the localities. The significance of the comparisons was tested using 10,000 permutations . The R function p.adjust was employed to control for FDR in order to correct for multiple comparisons. As all of the pairwise STF comparisons were high and significant (see Results), the degree of genetic variation between and within the sampling localities was further assessed using discriminant analysis of principal components (DAPC). This analysis, performed in the R adegenet package [To investigate the genetic structure of the populations, Arlequin 3.5.2.2  was used package , clusterTo further explore levels of population structure amongst the sampling localities, a likelihood-based genetic clustering was performed using the snapclust function of adegenet . The optSTF/(1- STF)), and computing the significance of the IBD using Mantel test in Genetix 4.05 [Isolation-by-distance (IBD) for both marker types was assessed by plotting the geographical distance  against the genetic distance (tix 4.05  with 100http://gher-diva.phys.ulg.ac.be/web-vis/) and ERDDAP (https://coastwatch.pfeg.noaa.gov/erddap/griddap/erdMHcdom8day.html) web-servers  or balancing selection .SNP and SSR markers were screened for candidate outliers using the Arlequin 3.5.2.2  fdist fuS. latissima life history and/or the current local selective processes. This methodology, based on correlation between allele frequencies and environmental data variation, was preferred to other environmental correlation methods  and 45 pairwise tests for the SSRs . This method, in turn, provided a compressive list of loci that exhibited non-neutral behavior due to both the , Bayenv ) because, Bayenv ,68, and https://blast.ncbi.nlm.nih.gov/Blast.cgi). The ddRAD-seq consensus sequence tag (150 bases) of each candidate outlier SNP was used to perform a nucleotide-BLAST search using the default alignment settings. This procedure replicated a methodology previously performed in similar studies by other authors [The potential function of a gene in which each putative outlier marker was located was investigated using a nucleotide-BLAST search against Genbank .http://heatmapper.ca/) [An autocorrelation test was performed in PAST 3.26  in orderper.ca/) .Sequencing of ddRAD-seq libraries yielded a total of 1,294,743,101 reads , which, after initial filtering steps, were assembled into 1,377,662 loci. Locus filtering resulted in 13,122 polymorphic loci and 103,963 SNPs remaining. This set of SNP markers was further reduced to 4069 SNPs that were utilized in the study.S. latissima sampling sites situated along a latitudinal gradient spanning the entire European Atlantic range of this species  populations at the southern limit of the range of S. latissima. The EH values were higher, and equivalent to one another, within the four French Brittany sites (Locmariaquer (LOC), St. Guenolé (STG), Lanildut (LAN), Lézardrieux (LEZ)). These sites and the surrounding coastline are characterized by the presence of long stretches of continuous rocky shores. There was a marked decrease in EH for the populations sampled from the eastern part of the English Channel and beyond (FER to Helgoland (HEL)). All these sites are situated on rocky shores but are separated from each other by large areas of sandy substrate. This is especially the case for the Helgoland archipelago (HEL), which exhibited the lowest EH of all sites for the two types of markers  and especially within HEL  when measured in terms of the percentage of private alleles whereas the lowest value was again found for HEL . This pathin HEL . HoweverHE, allelic richness, and percentage of private alleles with latitude was always non-significant for both marker types . The highest FST values were observed between HEL and the southernmost or the northernmost localities ; without NYA, G = 3.008, p-value < 0.01, (r =0.869); and for the SNPs: G = 2.639, p-value < 0.01, (r = 0.633); without NYA, G = 3.904, p-value < 0.001, (r = 0.873)).Similar patterns of genetic differentiation were observed for the two marker types even if the absolute pairwise for SSRs . All popS. latissima distribution were again clearly separated on the second axis from the more central sites  amongst the four Brittany localities  was six for the SNPs  and sevecalities .Population genetic structure assessed after removal of putative outlier SNPs (3730 loci remaining) and SSRs (13 loci remaining), see below, was broadly congruent with the results obtained with full marker sets. See r = 0.946, p < 0.001; avg-SST vs. max-SST, r = 0.898, p < 0.05, and avg-SST vs. cvar-SST, r = −0.911, p < 0.01; min-SST vs. cvar-SST, r = −0.930, p < 0.01)  and max-salinity   showed six significant outcomes out of 66 possible pairwise tests. These six tests showed significant autocorrelation between parameters belonging to SST and salinity but not between any parameters belonging to the different environmental variables. For SST, average SST correlated significantly with all the other SST parameters  . For sal< 0.001) .The fdist screening for candidate outliers detected a total of 339 candidate outlier SNPs (out of 4069 loci), and 10 SSR loci that potentially deviated from neutrality . Out of the 339 candidate outlier SNPs, 40 significantly matched  to sequences in Genbank. These outliers represented 11.80% of the examined candidate outliers (40/339), and 0.98% of the total SNP set (40/4069). The 40 candidate outliers matched 97 different sequences originating from 23 different taxa that belonged to seven different phyla of five kingdoms see . The larS. latissima  identified 7 out of 26 candidate outlier SNPs that might reflect the historical population structure of atissima A. It alsatissima A. p< 0.05) with the SST parameters ; one SNP locus (SNP629) correlated significantly with salinity , and five SNP loci  correlated significantly with CDOM   B. In detar-CDOM) B.p < 0.05) with the SST parameters ; two SSR alleles  correlated with salinity ; and eight SSR alleles  correlated significantly with CDOM   . Furtherax-CDOM) .R2) for the SNPs and SSR alleles which correlated significantly with the 12 environmental parameters identified four main clusters of associations. The first cluster comprised four SNPs  and seven SSR alleles   B that shN54-349) B. A secoN54-349) B. A thirN54-349) B. The foN54-349) B.The correlation of allele frequency variation within the outlier SNP loci and environmental parameters identified three main clusters of loci with respect to how these loci behaved within the different sampling localities C. The fiConcerning the three EST-derived microsatellite loci  that were significantly correlated with the environmental parameters, the association patterns revealed pairs of alleles belonging to the same locus for which each allele showed opposite patterns of correlation with the same environmental parameter. Specifically, alleles Sacl33-182 and Sacl33-186 were both correlated with min-CDOM but with positive and negative correlation, respectively . The allS. latissima sampled along a latitudinal gradient accounting for the entire eastern Atlantic distribution range of this species. Our results demonstrated a high degree of inter-population genetic differentiation with an absence of significant variation in genetic diversity with latitude. There are several potential non-mutually exclusive reasons, including both historical and contemporary causes, which may explain the reported patterns of S. latissima genetic diversity. The location of the ice-free refugia a species was occupying during the LGM has been proposed to have had a major influence on the genetic diversity patterns observed across that species’ present-day range [S. latissima [S. latissima Arctic LGM refugia proposed by [S. latissima, as suggested by [S. latissima compared to the refugia located further north, depending on whether there was long-term persistence of mostly continuous distribution of this species from Iberia to the English Channel, or if alternatively there was a lack of gene flow between the two distinct refugial zones. Given that we observed the highest levels of genetic diversity within the two northernmost localities of our sampling range, it might also be that the high latitude S. latissima populations presently inhabiting the formerly glaciated regions originated exclusively from the refugia that were closest to them , resulting in genetically divergent populations currently found at the lower latitudes. Thus, most likely the southern refugia did not substantially contribute to the post-glacial recolonization of the high latitude areas.In this study we investigated the genetic diversity and population structure of cold-tolerant kelp ay range . For Euray range . In our atissima ,38,45. Hposed by . This reposed by  proposinested by , one locS. latissima populations could potentially be explained by the rising seawater temperatures at the southern edge of distribution of this temperate-cold adapted seaweed species. Such a change in the environmental conditions could be highly detrimental to S. latissima [Saccorhiza polyschides occupying the rear edge of this species’ distribution range in southern Portugal [S. polyschides, persistence of high genetic diversity at the regional level within the southern Portugal rear edge area occurred despite the drastic population size reductions. For S. latissima, it may be that the recent extinction of the majority of populations in the Iberian Peninsula  rear edge area driven by climate change has erased the more ancient phylogeographic signature of genetic diversity.On the other hand, the relatively low genetic diversity of the Iberian atissima ,72, resuPortugal . HoweverS. latissima within-population genetic diversity and population genetic structure deduced based on the two marker types employed in this study. Although the within-locality expected heterozygosity values that we had obtained were 5 to 13 times higher for the SSRs than for the SNPs depending on the analyzed population, importantly the relative differences in EH between the studied populations were highly similar based on both marker types. Similar variations in the magnitude of within-locality EH between SSRs and SNPs have been observed before [EH values that we observed were approximately an order of magnitude lower than those obtained for several western Atlantic S. latissima localities [S. latissima populations on either side of the Atlantic Ocean to environmental change or rather from the different methodologies used to obtain the SNP markers in our study and in [There was a broad concordance of the patterns of d before  and are d before , brown td before , coral rd before , and pikd before . The SNPcalities . Whethery and in  is sometS. latissima is in agreement with previous analyses of the population structure in this kelp species [S. latissima populations when separated by at least 300 km. The high and significant pairwise STF values revealed that there was substantial genetic differentiation between all pairs of the populations we analyzed, whereas the DAPC suggested that the sampling localities were largely independent entities, as there were only a few occurrences of individuals that were not assigned to their locality of origin or that displayed mixed ancestry, and in those instances the exchange of migrants largely took place between the nearby localities. In addition, even though the snapclust algorithm grouped the sampled localities into fewer genetic clusters than there were sampling sites, each cluster was clearly composed of only neighboring sampling sites, thus suggesting that long range exchanges of migrants are an unlikely occurrence. Nevertheless, the occurrence of well separated genetic clusters for each of the southernmost populations is in agreement with what is expected at the rear edge of the distribution of S. latissima and provides support for the existence of the Iberian Peninsula S. latissima LGM refugia. The identification of the AUD locality as an independent cluster by the snapclust analysis performed with the SSR markers contrasted with the output of snapclust algorithm run with the SNPs. This apparent discrepancy could be explained by the hypothesis that the SSR locus Sacl-33 was under selection at this locality, as demonstrated by its significant statistical association with the CDOM environmental parameter . Indeed, when this locus was removed and the snapclust analysis was rerun on a neutral SSR marker panel, the AUD locality was included in the same genetic cluster as the neighboring English Channel localities of FER and HEL. The above results were further supported by a significant IBD signal for both marker types, even with the NYA locality included in the analyses. The substantial geographic distance separating NYA and the other sampling localities meant that there likely was very little gene flow between NYA and the other sampling sites, and thus not in agreement with the stepping-stone IBD hypothesis.Overall, the strong genetic structuring that we report here for  species ,37,76. CL. digitata [L. digitata samples from the Helgoland archipelago exhibited the weakest heat stress response in [L. digitata might have counterbalanced the deleterious effects of genetic drift. Examination of non-neutral genetic variation could therefore provide a more complete understanding of the potential for local adaptation [The extremely low within-population genetic diversity of the AUD and HEL localities deserves a special mention. It suggests that these populations experienced elevated levels of genetic drift that can be explained by their geographic isolation  and their low effective population size. We predict that these populations will become extinct in the near future. Such low levels of genetic diversity within the HEL locality was also reported for the kelp digitata , and malponse in . This reaptation ,16,77,78latissima and assessed how this may have influenced historical and recent local adaptive processes. In our study, we identified seven outlier SNPs putatively involved in functional adaptive responses. Three SNPs  showed allele frequency patterns that have likely been driven by historical events that shaped S. latissima population structure during the cycles of expansion and contraction of the species range following the LGM [Oceans are multifaceted and dynamic environments in both space and time where the patchy vertical (depth) and horizontal  distribution of various environmental stressors/features is likely to be an important driver of the local adaptive responses of all marine organisms, a phenomenon that can be better understood utilizing “seascape genetics” .  the LGM ,45. ThesSaccharina japonica [Pisum sativum after exposure to higher temperatures [S. latissima, a typical cold-adapted species, to expand and establish permanent populations in the warmer environments that characterize its current range of distribution.The tic20 protein plays a role in the transport of proteins into the chloroplast in plants and ensures the correct functioning of photosynthesis ,84. Thisjaponica . Not muceratures . Similareratures ,88. It iS. latissima SNP1865 marker and the female-specific marker Msj68/58/2 from S. japonica [S. latissima, suggesting that an investigation of the SNP1865 genomic sequence could help to uncover this aspect. The allelic variation at SNP1865 was significantly correlated with variation in SST and CDOM, suggesting the existence of an evolutionary sex-specific effect driven by these two environmental features. The idea that SST and light stressors might cause evolutionary differences at the sexual haploid stages (gametophytes) of S. latissima has been already suggested by several authors [S. latissima male and female gametophytes revealed that temperature has important implications for physiological processes which produced gender-specific effects in S. latissima such that the male gametophytes were able to tolerate higher temperatures than the female gametophytes [S. latissima female-specific marker considering that the divergent north-south allele frequency patterns at the SNP1865 marker strongly suggest a role for temperature along the examined latitudinal gradient. However, further investigations should be carried out to validate the correlation between temperature and the putative S. latissima female-specific marker SNP1865, as it has recently been suggested that genomic areas exposed to higher rates of recombination  might lead to false positive divergence of the detected outliers in genome scan analyses [Furthermore, we observed a significant link between the japonica . Althougjaponica , no fema authors ,92,93. Atophytes . This evanalyses ,95.Saccharina and might help to resist abiotic stress  [S. latissima sporophytes was suggested to be linked to higher seasonal temperature [L. digitata, for which heat-wave experiments implicated SST in varying mannitol content of sporophytes collected from a large latitudinal gradient  [S. japonica during events of hyposalinity and hyperthermal stress [S. latissima in response to CDOM.Among the remaining four outlier SNPs that correlated with SST, CDOM, and salinity, we identified potential associations with genes involved in alginate  and iodine (vanadium-dependent iodine peroxidase gene) metabolic pathways. These SNPs might be involved in local selective processes that may enhance the survival of sporophytes that experience high levels of variation in SST, CDOM, and salinity. Phosphomannose isomerase 1 (PMI1) (SNP629 and SNP1197) and the mannuronan C-5 epimerase (MC5Es) (SNP3660) are key genes in the metabolic pathways that lead to the biosynthesis of mannitol and alginate carbohydrates . Alginatalinity) ,99 and palinity) . Furtherperature . This hy Norway) . Vanadiu Norway) . A recenl stress , but notS. japonica [L. digitata [S. latissima has not been established [S. latissima proteins that responded to acclimation to temperature and light stress.Finally, we also observed a high proportion (38.88%) of SSR loci exhibiting non-neutral behavior, half of which were EST-derived markers . EST-SSRjaponica  and L. ddigitata , with sodigitata . The traablished ,104,105.ablished  were devablished  where thS. latissima genome. Generally, diversifying selection can result in significantly high locus-specific differentiation among populations relative to the neutral predictions and the usage of EST-SSRs is perfectly suited to uncover the ecological processes that may be involved in local adaptation [Eucalyptus, [Castanopsis fargesii, [Oryza sativa, [S. latissima strains under specific aquaculture conditions.Among the EST-SSR loci that were correlated with SST and CDOM, loci Sacl56 and Sacl33 stand out. These two loci showed divergent allele frequency patterns  that might suggest diversifying selection acting on these loci. The nature of the EST-derived SSR loci should allow the genetic variation at these loci to be linked with specific functional traits but we were unable to map any of the analysed EST-SSR markers onto the aptation . There aalyptus, ,109; theargesii, ; rice OrS. latissima. There are multiple other possible explanations for the associations between the potential outliers and the environmental responses that we detected in this study. These include the possible existence of (i) strong statistical bias , and (ii) the genetic linkage of the identified outlier loci with other distant genes (occurring in low recombinant regions of a chromosome) in the S. latissima genome. Lacking a fully annotated S. latissima reference genome, we nonetheless propose that the genome-wide scan approach that we adopted provided an opportunity to predict a set of markers that might suggest physiological adaptive responses. A confirmation for the involvement of these loci in adaptive processes must be validated with future studies designed specifically for this purpose.We are aware that the genome-wide scan methods for the identification of outlier loci, here treated as candidate markers associated with adaptive traits, are still too coarse to fully describe the short and long-term evolutionary responses to environmental changes in S. latissima populations distributed along the European Atlantic coast while also highlighting global warming and the associated environmental changes as an increasingly important factor in driving the distribution range of this kelp species. We observed the highest levels of genetic diversity within the Arctic population, a result which gives support to the hypothesis of the important contribution of the populations that persisted throughout the cycles of glaciation in the LGM Arctic refugia to the present-day patterns of genetic diversity of this species. Six distinct genetic clusters were delimited, knowledge of which will be helpful for the conservation management of the eastern Atlantic populations of S. latissima as it will allow specific geographic areas containing putatively locally adapted strains to be defined more accurately which is vital for sustainable management of these wild resources for kelp aquaculture. In addition to the recommendation of avoiding the transfer of algae material between disparate genetic clusters and across vast geographic regions because of the potential risks of genetic pollution and/or introduction of foreign pathogens [In conclusion, our study confirmed the importance of historical demographic processes in shaping the current genetic structure of athogens ,76,112, athogens . In this


Gypsophila paniculata L. . The presence of G. paniculata negatively impacts native species and has the potential to alter ecosystem dynamics. Our research goals were to (1) estimate the genetic structure of invasive G. paniculata along the Michigan dune system and (2) identify landscape features that influence gene flow in this area. We analyzed 12 populations at 14 nuclear and two chloroplast microsatellite loci. We found strong genetic structure among populations , and pairwise comparisons among all populations yielded significant FST values. Results from clustering analysis via STRUCTURE and discriminant analysis of principal components (DAPC) suggest two main genetic clusters that are separated by the Leelanau Peninsula, and this is supported by the distribution of chloroplast haplotypes. Land cover and topography better explained pairwise genetic distances than geographic distance alone, suggesting that these factors influence the genetic distribution of populations within the dunes system. Together, these data aid in our understanding of how invasive populations move through the dune landscape, providing valuable information for managing the spread of this species.Coastal sand dunes are dynamic ecosystems with elevated levels of disturbance and are highly susceptible to plant invasions. One invasive plant that is of concern to the Great Lakes system is  Ammophila brevigulata Fern.), Lake Huron tansy (Tanacetum huronense Nutt.), and Pitcher’s thistle (Cirsium pitcheri Torr. ex Eaton (Torr. & Grey)) are adapted to sand burial and will continue to grow above the sand height as it accumulates . We. WeG. pahe locus ; 300 µM Nicotiana tabacum L. [Each sample was also amplified at two universal chloroplast microsatellite loci (hereafter cpSSRs) previously developed for bacum L.  .We determined successful amplification by visualizing the amplicons on a 2% agarose gel stained with ethidium bromide. For both nSSR and cpSSR markers, we multiplexed PCR amplicons according to dye color and allele size range , added LPrior to any analysis, we used multiple approaches to check for scoring errors . We checIS) in GenAlEx 6.502 [We calculated the total number of alleles per sampling location, private alleles, Shannon’s Identity Index, observed and expected heterozygosity, and estimated the inbreeding coefficient  correction [To test for genetic differentiation between all pairs of sampling locations, we calculated Weir and Cockerham’s  pairwiseEx 6.502 ,64. In trrection . To testrrection ,64.K (1–16). The default settings were used for all other parameters. We identified the most likely value of K using the ∆K method from Evanno et al. [To examine the number of genetic clusters among our sampling locations, we used the Bayesian clustering program STRUCTURE v2.3.2 . Individo et al.  in CLUMPo et al. .K clusters (1–16). We retained a K-value of 3 based upon the Bayesian information criteria (BIC) value. DAPC can be beneficial, as it can limit the number of principal components (PCs) used in the analysis. It has been shown that retaining too many PCs can lead to over-fitting and instability in the membership probabilities returned by the method [To further explore the genetic structure of these populations, we performed a Discriminant Analysis of Principal Components (DAPC) in the R package adegenet, which optimizes among-group variance and minimizes within-group variance ,68. To iST (D = FST/(1–FST)) [TM 10.4.1, Redlands, CA, USA), and the latitude and longitude of these points was then used to construct a matrix of straight-line distances in km between each sampling location. The reported p-values are based on a one-sided alternative hypothesis (H1: R > 0). A Mantel test was run for all sampling locations together, and a test was also run separately for populations within each cluster identified in the STRUCTURE analysis.To assess the effect of isolation by distance (IBD), we used a paired Mantel test based on a distance matrix of Slatkin’s transformed F(1–FST))  and a ge(1–FST))  and Smou(1–FST)) . The meaFor the cpSSR dataset, we used the program HAPLOTYPE ANALYSIS v1.05  to calcuST distance matrix for both datasets and ran an AMOVA. The population pairwise ΦST matrix facilitates comparison of molecular variance between codominant and dominant data by suppressing within individual variation, thus allowing for the comparison between varying mutation rates [In order to compare the population structure of the nSSR and cpSSR data, we used the Φon rates ,75. To ton rates ,64.ST) from nine of the 12 sites that corresponded to individuals belonging to the cluster southwest of the Leelanau Peninsula. The reason for this is because many of these populations are in closer geographic proximity to one another and within a continuous portion of the dunes system, allowing us to gain a better understanding of how natural dune landscape features impacted the genetic distribution of these populations. We used the R package ResistanceGA [We conducted our analysis using genetic distance data  imagery from the National Agriculture Inventory Program (2016) in ArcGIS v 10.4.1 . We used the maximum likelihood classification method in the Image Classification tool to classify the landscape into five categories: forest, water, sand, grass , and open field . In addition to land cover, we used a 30-m digital elevation model (DEM) and ArcGIS Toolboxes ,79 to geuitscape .G. paniculata to the Great Lakes has the potential to disrupt the dynamism of the dune landscape and biological community in Michigan, and this threat has led to increased concerns over its pervasiveness regionally and nationally. Estimating the genetic structure of invasive populations can lead to a better understanding of the invasion history and the factors influencing the success of an invasion [G. paniculata populations probably results from a combination of invasion history and demographic processes—isolation and admixture, along with landscape level processes. The topography of the dunes is heterogeneous but also constantly shifting, and the G. panculata invasion is one example of how this dynamic system can shape the establishment, gene flow, and spread of invasive plant populations.The invasion of invasion ,81,82. T


Twenty-three known mosquito species from the genera Aedes, Armigeres, Culex, Mansonia, and Anopheles and nine unconfirmed mosquito species were identified. Aedes albopictus, Armigeres subalbatus, and Culex pipiens quinquefasciatus were the most prevalent mosquito species on Hainan. The regions north of Danzhou, Tunchang, and Qionghai exhibited high mosquito diversity (26 species). The order of the total haplotype diversity and nucleotide diversity of the populations from high to low was as follows: Culex tritaeniorhynchus, Ar. subalbatus, Culex pallidothorax, Culex gelidus, Ae. albopictus, and C. p. quinquefasciatus. Tajima’s D and Fu’s Fs tests showed that Ae. albopictus, C. p. quinquefasciatus, C. tritaeniorhynchus, and C. gelidus had experienced population expansion, while the Ar. subalbatus and C. pallidothorax populations were in genetic equilibrium. Significant genetic differentiation existed in the overall populations of Ae. albopictus, Ar. subalbatus, C. p. quinquefasciatus, and C. pallidothorax. The Ae. albopictus populations on Hainan were characterized by frequent gene exchange with populations from Guangdong and four other tropical countries, raising the risk of viral disease outbreaks in these regions. Two subgroups were reported in the Ar. subalbatus populations for the first time. Our findings may have important implications for vector control on Hainan Island.Hainan is a tropical island in southern China with abundant mosquito species, putting Hainan at risk of mosquito-borne virus disease outbreaks. The population genetic diversity of most mosquito species on Hainan Island remains elusive. In this study, we report the diversity of mosquito species and the genetic diversity of the predominant species on Hainan. Field populations of adults or larvae were collected from 12 regions of Hainan Island in 2018 and 2019. A fragment of the mitochondrial cytochrome c oxidase subunit I ( The climate of Hainan is a tropical maritime monsoon climate with an annual average temperature of 24.2°C and an annual average rainfall of 1,684 mm. Hainan has become a China Pilot Free Trade Zone, with increasing international tourism and commercial trade, under the Belt and Road policy. The natural and cultural conditions of Hainan result in abundant mosquito species. A total of 44 mosquito species in 9 genera have been reported in Hainan based on classical morphological classification, among which 28 species have available molecular markers, such as mitochondrial cytochrome c oxidase subunit I (coxI) gene sequences , Wenchang (WC), and Lingao (LG) in the north; Sanya (SY), Lingshui (LS), and Ledong (LD) in the south; Dongfang (DF) and Danzhou (DZ) in the west; Qionghai (QH) and Wanning (WN) in the east; and Tunchang (TC) and Wuzhishan (WZS) in the central part of Hainan Island, from June to October 2019 . In sevecoxI gene fragment. Polymerase chain reaction (PCR) was performed in a reaction mixture containing 12.5 μL of Premix Taq , 1 μL of 10 mM primers, 1.5 μL of DNA, and 10 μL of distilled water. The thermal cycling conditions included a 5 min initial denaturation step at 94°C, followed by 34 cycles of 30 s of denaturation at 94°C, 30 s annealing at 55°C and 41 s elongation at 72°C, and a final elongation at 72°C for 12 min. The product was checked by 1% agarose gel electrophoresis and sent to a company  for sequencing.Genomic DNA was extracted from one leg of each specimen using the hot sodium hydroxide and Tris (Hot SHOT) method . BrieflycoxI sequences from 611 to 626 bp were obtained from 1,227 mosquito samples and deposited into the GenBank database. These sequences were aligned with the coxI gene sequences of different species of mosquitoes downloaded from GenBank using ClustalW of MEGA7.0  between the Hainan populations was calculated with the distance method. The Fst between Hainan and other regions of China or overseas sites was calculated with haplotype frequencies. The significance level was tested with 10,000 random permutations (Fst)/2Fst  in MEGA 7.0. The statistical significance of tree branching was tested by performing 1,000 bootstrap replications.After removing the bases corresponding to irregular peak patterns, clean  MEGA7.0 . When thle sites . The parle sites . The paiutations . Gene flst)/2Fst . Tajima’e values . PhylogecoxI sequences of single mosquitoes from Hainan were obtained and aligned with the coxI sequences of different species of mosquitoes downloaded from GenBank. Twenty-three known mosquito species in five genera were identified in the two years of the investigation in Hainan  was 0.62, and the nucleotide diversity (π) was 0.17. The highest diversity was found in the DF population, and the lowest diversity was found in the WN population (Fst) using the distance method (Fst between 0.17 and 0.24). However, the Nm values between DF and the other populations were larger than 1 (from 1.55 to 2.44), indicating frequent gene exchange between them (Fst < 0.1) from some populations due to more frequent gene exchange. The molecular variance analysis (AMOVA) showed that the majority of the genetic variance occurred within populations (92.68%) (Fst was 0.07 (P < 0.001), and Nm was 6.64, reflecting low population differentiation. Tajima’s D value (−2.10) and Fu’s Fs value (−29.15) for the overall populations both reached a significant level, reflecting significant population expansion  . The totxpansion . RegardiFst values between Hainan populations and those of other regions from China or overseas were also calculated according to the haplotype frequencies , Italy, the Lao People’s Democratic Republic, Singapore, Japan, Thailand, and Pakistan were downloaded from GenBank. The Hainan populations exhibited the largest divergence from the United States population  and the least divergence from the Congo population . There was frequent gene flow between the Hainan populations and the Henan, Yunnan, Guangdong, Congo, Lao People’s Democratic Republic, Singapore, or Thailand populations (Nm from 1 to 5.3).The quencies . The hapAr. subalbatus was collected from nine regions of Hainan. The phylogenetic analysis showed that two subgroups were clustered with over 70% bootstrap values. The TC, WZS, LS, HK, DZ, and WC populations contained individuals from both subgroups (ubgroups . GeneticHd) and 0.42 (π), respectively. HK exhibited the lowest haplotype diversity, and SY exhibited the lowest nucleotide diversity. WC showed the highest haplotype and nucleotide diversity , and Nm was 4.50. Most of the total variation existed within populations (89.52%) (Fst between subgroups was 0.77 (P < 0.01), and Nm was less than 1, indicating that gene flow failed to prevent the subgroup differentiation caused by genetic drift.There were 16 haplotypes with 22 variable sites, and only one haplotype appeared in all populations . The twoiversity . Tajima’xpansion . Signifi(89.52%) . However(89.52%) . The FstAr. subalbatus populations from those of Pakistan or India was analyzed using haplotype frequencies. The Hainan populations exhibited greater differentiation from the Pakistan population  than the Indian population  but showed frequent gene flow with both populations , but LD and DZ showed the highest diversity . Tajima’s D tests and Fu’s Fs test for the overall populations presented statistically significant negative values . HK exhibited significant differentiation from all six other populations, followed by LD and DZ, which showed significant differentiation from five populations (Fst was 0.10 (P < 0.01), and Nm was 4.50. The majority of the variation (90.43%) existed within populations , and these populations experienced expansion during their history with significant negative Tajima’s D and Fu’s Fs values  due to limited genetic exchange between them (Nm less than 1) (Fst was 0.33 (P < 0.001), and Nm was 1.01. A considerable proportion (33.06%) of genetic variance existed among populations  . The totulations .Aedes, 11 Culex, six Anopheles, one Mansonia, and one Armigeres species based on the coxI sequences. In addition, nine specimens were not confirmed due to their low identities with the coxI sequences of known mosquitoes in GenBank. Although coxI has emerged as the most commonly used marker for barcoding, this marker sometimes does not contain enough information to distinguish certain mosquito species of Anopheles and Culex   existed between the two subgroups. This is a dominant cause of the high haplotype and nucleotide diversity of the Ar. subalbatus populations on Hainan. The genetic divergence between the two subgroups was quite high (Fst = 0.77), and gene flow between them was blocked. It is possible that in the future, the accumulation of genetic differences will lead to reproductive isolation between the two subgroups and, thus, the formation of new species.ancrofti . Two subY440299)  and YunnY440299)  are closIn conclusion, our results showed a high diversity of mosquito species and their population genetic characteristics on Hainan Island. These results may have important implications for vector control and shed light on understanding the evolutionary processes of these mosquito species.https://www.ncbi.nlm.nih.gov/genbank/, MT541015–MT541156, MT541161–MT541779, MT566458–MT566913, MT575769–MT575771, MT576036, MT586701, MT590372, MT596915, MT606009, and MT613992.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: FC, QX, and LK designed the experiments. FC and SL wrote the manuscript. SL performed the experiments and conducted the data analysis. SL, FJ, HL, XK, YW, ZZ, DW, AZ, CL, QL, and FC collected mosquitoes from the fields. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.