Cyclura ricordii is an endemic iguana from Hispaniola Island and is threatened on the IUCN Red List. The main threats are predation by introduced mammals, habitat destruction, and hunting pressure. The present study focused on two nesting sites from Pedernales Province in the Dominican Republic. The hypothesis that natal philopatry influences dispersal and nest‐site selection was tested. Monitoring and sampling took place in 2012 and 2013. Polymorphic markers were used to evaluate whether natal philopatry limits dispersal at multiple spatial scales. Ripley's K revealed that nests were significantly clustered at multiple scales, when both nesting sites were considered and within each nesting site. This suggests a patchy, nonrandom distribution of nests within nest sites. Hierarchical AMOVA revealed that nest‐site aggregations did not explain a significant portion of genetic variation within nesting sites. However, a small but positive correlation between geographic and genetic distance was detected using a Mantel's test. Hence, the relationship between geographic distance and genetic distance among hatchlings within nest sites, while detectable, was not strong enough to have a marked effect on fine‐scale genetic structure. Spatial and genetic data combined determined that the nesting sites included nesting females from multiple locations, and the hypothesis of “natal philopatry” was not supported because females nesting in the same cluster were no more closely related to each other than to other females from the same nesting site. These findings imply that nesting aggregations are more likely associated with cryptic habitat variables contributing to optimal nesting conditions. These species are the largest native herbivores on the island, and they fulfill a crucial ecological role in their dry forest ecosystems as seed dispersers, and by contributing to nutrient cycling through foliage grazing , has continually monitored C. ricordii at all localities. The focal population under study is in the southwestern region of the Dominican Republic in Pedernales Province  in the resolution 05‐2005 of the Pedernales Province City Hall  and Pedernales (PED), separated by ~40 km , 0.04 µl forward primer, 0.2µl reverse primer, 0.2 µl fluorescent tagged primer, 0.4 U Taq polymerase, and 1.0 µl of DNA template). Fragment analysis was carried out at Arizona State University service laboratory, and alleles were manually annotated with Peak ScannerTM Software v1.0 (Applied Biosystems).Whole genomic DNA was extracted from blood and tissue samples with a Maxwell 16 Tissue DNA Purification Kit in a Maxwell® 16 MDx Research Instrument (Promega). Noncoding microsatellites were used to infer patterns of population structure and rates of gene flow. Over seventy microsatellite markers were screened and characterized for this species with the 2012 samples of hatchlings and adults  and Cabritos Island  were sequenced according to Malone, Wheeler, Taylor, and Davis  using pr2.4genepop v. 4.2 was used to detect null alleles and to estimate gene flow (Nm) for the polymorphic microsatellites  were made using the linkage disequilibrium (LD) method  per locus, expected and observed heterozygosity  per locus with their associated p values and standard deviation  to assess genetic differentiation. d Figure , to eval Jombart . A discr Jombart  consider2.6r created by Baddeley and Turner  tested for a homogeneous Poisson process, assuming complete spatial randomness (CSR) for our dataset  function is:K(r) refers to two‐dimensional spatial data, λ is the density (number per unit area) of events, and E refers to the number of extra events within distance r of a randomly chosen event Kr=K(r) (Equation K(r) estimator that biases the results  function  = r.assuming CSR, L(r) – r can indicate two distinct deviances from a random distribution. If L(r) – r < 0, then spatial data points are regularly distributed or overdispersed. If L(r) – r > 0, then points are underdispersed or show evidence of clustering  to assess the goodness of fit of a point process model to the point pattern data  (Equation K^lo(r), and upper, K^hi(r), boundaries of a 95% confidence envelope , (b) among nests within clusters (FSC), (c) among individuals within nests (FIS), and (d) within individuals (FIT). These variance components were assessed with Arlequin v. 3.5.1.3  to describe the amount of genetic variation for each hierarchic level according to Weir and Cockerham  among clusters  and Y (latitude) coordinates from each individual. The null hypothesis was that the two distance matrices are independent. The alternative hypothesis is that of a positive association between the two distance matrices, suggesting the presence of isolation by distance  and Pedernales (PED). The Pedernales population is spread across a large area, and identifying areas with high densities of individuals has been challenging. Of the 52 total adult samples gathered from both locations, 15 (28.8%) were animals killed by dogs, 12 (23%) were captured with Tomahawk traps, and 4 (7.7%) were from animals found dead on site. The rest of the wild adult captures were made with nooses and nets . The sampling success reflects the high level of threat these iguanas face, given that most of the adults sampled were carcasses.Two of the three populations of A total of 26 nests from Malagueta and 23 from Tierra were sampled during 2013, and the number of individuals captured per nest ranged from 1 to 23. Some individuals were removed from the dataset because of poor DNA quality . Twenty‐three nests from Malagueta and 22 nests from Tierra were used for analysis, and the number of individuals per nest used for the analysis ranged from 1 to 15. The 84 hatchlings sampled in 2012 were used for the screening of molecular markers and excluded from further analysis, because they only represented a very small area of Tierra and sampling effort could not be compared with the 2013 sampling.3.2C. ricordii. The polymorphic markers used were as follows: Ccste05  ranged from 4 to 16 for the thirteen markers across all samples  and when only adults were considered only for the Pedernales population  using the LD and the Coancestry methods for both populations range between 3.5 and 105.7, and 95% confidence intervals were highly variable (Table ex), they were inclusive due to the limited sample size  and Pedernales (PED) adults revealed that a significant portion of the differences in the genetic makeup of these two areas can be explained by relative isolation and lack of gene flow when only adults were considered  from 2008 to 2013 occurred within a 1,100 x 1,500 m rectangular plot. K(r) was estimated for distances up to 250 m. Above this cutoff distance, the spatial distribution of nests appears to be random. Observed variation in node density for all K(r) estimates, as measured by K^obs(r), exceeded the expected variance that assumed a random distribution of points, Ktheo(r). This indicates that nests are significantly clustered when evaluated at a coarse scale  from 2008 to 2013 that were within a 170 x 476 m rectangular plot were measured. K(r) was estimated for distances up to 40 m  was estimated for distances of up to 100 m  estimates, as measured by K^obs(r), exceeded the expected variance assuming a random distribution of points, Ktheo(r). This suggests a similar pattern as the one found at the finer scale for the nesting habitat in Pedernales, where nests are significantly clustered even when the finest scale is evaluated  – r, also suggests that the degree of clustering in relation to distance (r) varies between sites. Because of the preexisting clustering pattern of the nesting site at the Pedernales site and due to the significant degree of clustering observed for each nesting site individually, both nesting sites are analyzed separately from this point forward.Ripley's 3.4.3K at the finest scale and to evaluate whether the clustering pattern observed changes over time. Dotted lines on Figures Spatial points for each nesting site for every year from 2008 to 2013 were plotted to evaluate the pattern of clustering suggested by Ripley's 3.5Distances below the minimal plateau distance for the data points from 2013 that were obtained from the edge thinning technique were combined with molecular data. Even if plateaus were not clearly defined in the results of the 2013 edge thinning procedures and only one pattern of aggregation was observed Figures  and 8, mF‐statistics for each of the clustering patterns tested are shown in Table FCT) and (c) among individuals within nests (FIS) was not significant. This indicates that the spatial genetic structuring suggested with the threshold distances used was not supported when the genetic structuring involved clusters and individuals within nests. Smaller distances were tested, and no significant differences in the AMOVA were detected. To further decrease the radii of distances used, a higher number of nests and multiple years should be included in this type of analysis. The most significant level of differentiation was (b) among nests within clusters (FSC). This result indicates that 20% of the variation in Tierra and 17.5% of the variation in Malagueta can be explained among the nests within clusters. This suggests that nests within a single cluster are not more closely related than nests from other clusters. The hierarchical level related to the degree of differentiation (d) within individuals (FIT) was moderately significant for Tierra, but not significant for Malagueta. This suggests that there is a significant deviation of alleles from Hardy–Weinberg expectations within individuals relative to the entire nesting site  was still present but very little of the variation can be explained with this model (only 0.7%). When one hatchling per nest was considered, no significant correlations were detected. In this respect, the alternative hypothesis of a positive association between matrices was supported when all hatchlings were included; however, the signature of isolation by distance was lost when only one hatchling per nest was considered. In general, very little of the genetic variation could be explained by the model, which is only consistent with a limited degree of fine‐scale genetic structure.To evaluate natal philopatry for both Tierra (TIE) and Malagueta (MAL), a Mantel's test was performed using 13 microsatellite markers for 22 nests from Tierra and 23 nests from Malagueta where all hatchlings were included and analyses were rerun with one hatchling per nest Table . When al4FST = 0.134, p « 0.01; Nm = 0.99), suggests limited dispersal between geographic regions for the species. This pattern of genetic structure was expected because of the magnitude of the geographic barriers between sites. The Bahoruco mountain range, which reaches almost 2,000 m asl, and Enriquillo Lake are important barriers for dispersal between Pedernales and Cabritos Island populations. Many studies have demonstrated how these types of barriers influence genetic divergence of other species of Cyclura  and determined that iguanas may disperse passively  over water channels, which are prominent in the Andros Island landscape, but that migrations are unsuccessful over these water channels. Overall, many studies have shown clear evidence that Hispaniola Island landscape has important barriers which limits dispersal for many mobile animal species . Hatchlings were collected from discrete nesting sites, and the assumption that these animals belong to the same population seems appropriate. Collection of adults was more haphazard. Many of the adults sampled were deceased as a result of predation by feral dogs. Because a precise origin of adult samples is unknown, we must accept that these samples may be more representative of a broader geographic range. Hence, independently of the origin of adult samples, the apparent elevated homozygosity may in part reflect small population size and a high degree of relatedness and could be a result of inbreeding, which could be a cause of concern and should be further evaluated.Descriptive statistics for adults collected from Pedernales and Cabritos Island showed a significant excess of homozygotes in both populations. When the 4.2C. ricordii using the same neutral molecular markers to test the hypothesis of natal philopatry. We focused on two nesting sites in Pedernales Province: Tierra and Malagueta. We found support for high levels of spatial clustering of nests within nesting sites consistent with a high return rate of females to nest in specific areas within these communal sites. The hypothesis of “natal philopatry,” however, was not supported when spatial and genetic data were combined because females nesting in the same cluster were no more closely related to each other than other females in different clusters. Further, the relationship between geographic distance and genetic distance among hatchlings within nesting sites was indicative of a slight fine‐scale genetic structuring.We also analyzed the nesting behavior of FST = 0.019, p « 0.01; Table Data on the genetic variation of hatchlings collected from Tierra and Malagueta showed an excess of homozygotes for both nesting sites, though it was only significant for Tierra. The homozygosity observed in hatchlings from Pedernales, along with elevated levels of homozygosity for adults, suggests that positive assortative mating may occur in the Pedernales population and that limited dispersal is present between nesting sites within the Pedernales geographic region. This may indicate that the breeding population that nests in Pedernales is too small. Natal philopatry in a small population may reinforce patterns of inbreeding among the adult population. Within nesting sites, fine‐scale genetic structuring observed for iguanas indicates that complete random mating is not present (Sphenodon punctatus) and found an overall genetic differentiation of 1.2% among subpopulations that were only 400 m apart . When the authors expanded their analysis to include a wider spatial range (750 m), the pattern disappeared . However, this pattern varies through the years. The degree of clustering between nesting sites, at the coarse spatial scale, was expected due to the preexisting clustering of these communal nesting sites in Pedernales. However, when combined, spatial and genetic data do not support the return of related females to a specific nest aggregation within fondos. However, a strong fidelity toward specific areas, from females of unknown origin, within these nesting sites was supported with spatial data. Ripley's FSC = 0.204, p « 0.01 for Tierra and FSC = 0.175, p « 0.01 for Malagueta) suggests that the patterns of aggregation observed with Ripley's K estimate are independent of the genetic structuring observed within each nesting site. These results are inconsistent with natal philopatry limiting dispersal for nest‐site selection within these nesting sites. Nests within each of the putative clusters are not more related to each other than the ones from other clusters. If natal philopatry were present, nests grouped within a single cluster should be more related to each other than nests from other clusters and variation among clusters should be higher and significant. Nevertheless, unrelated females may select the same nest site due to other environmental reasons, and elucidating these differences in relatedness may benefit from the gathering of ecological and behavioral data at the individual level for the Pedernales population. Further, the continued protection of these nesting sites since 2004 by an NGO, Grupo Jaragua, has led to the conservation of appropriate nesting habitat for multiple generations, and females may be returning to areas where increased protection facilitates nesting.The amount of genetic variation detected among nests within clusters , this indicates that natal philopatric behavior, if present, may not be strong or exclusive to finer spatial scales. This evidence could also be overcome by a more general “homing” behavior driven by other ecological factors such as imprinting on habitat features. The significant 1.9% of genetic differentiation between nesting sites within Pedernales shows how, even with a long‐lived reptile, very fine‐scale (<1.5 km) genetic structuring can be present and limited dispersal may be an outcome of natal philopatry for the Pedernales population. Changes in patterns of aggregations by year indicated that the observed patterns are not constant through space and time. Multiple factors may influence these yearly changes in the patterns of nest‐site aggregations. First, there is the possibility that females are not nesting every year , training of field techniques, submission of grants, manuscript edits, and financial support of fieldwork. Glenn P. Gerber involved in the experimental design, field training, grant submission, manuscript edits, and financial support of fieldwork. Christopher P. Brooks contributed to the design, analysis, and interpretation of the spatial analysis data. Ernst Rupp involved in the experimental design and provided nest data points for 6 years of his research (2008–2013) for the spatial analysis. Mark E. Welch involved in the experimental design, grant writing and submission, manuscript edits and revision, and financial support for the genetic analysis and training and served as an adviser. Click here for additional data file.


To evaluate the origin, genetic diversity, and population structure of domesticated rabbits in Kenya, a 263-base pair region of mtDNA D-loop region of 111 rabbits sampled from Kakamega, Vihiga, and Bungoma counties in the western region, Laikipia and Nyandarua counties in the central region, and Kitui, Machakos, and Makueni in the eastern region of the country were analyzed. The average haplotype (0.40702) and nucleotide (0.01494) diversities observed were low, indicating low genetic diversity of domesticated rabbits in Kenya. This study resolved 5 unique haplotypes in the mtDNA D-loop region. A population genetic structure distinguishing Europe grouping and domesticated rabbits in Kenya was obtained on incorporating 32 known haplotypes. Domesticated rabbits in Kenya clustered together with rabbits from other geographic regions, suggesting common origin. The results suggested that the Kenyan domesticated rabbits may have originated from Europe. Integration of exotic breeds into breeding programmes could have contributed to the low genetic diversity. These results provide useful information for breeding and conservation decisions by the relevant stakeholders in the agriculture industry in Kenya. Oryctolagus cuniculus, which exists in both wild and domestic forms [Oryctolagus cuniculus cuniculus and Oryctolagus cuniculus algirus, coexist, with the former occurring in the north eastern part and the latter in the south west [Domesticated rabbits are descendants of the European rabbit, ic forms , 2. The uth west , 4. Anotuth west .th Century when missionaries came to Kenya [Rabbit rearing is a recent practice, and it is reported to have been followed by breeding which began in two localities, the Iberian Peninsula in first century BC and the ancient French monastery in Rome in the last 1,500 years [to Kenya . CollaboDomestication is reported to have had an impact on genetic diversity as is evident in the immense phenotypic diversity present in domesticated rabbit. Phenotypic diversity is an evidence of the underlying genetic diversity . DiversiApplication of molecular markers in diversity studies has been employed in a variety of animal species such as cows, goats, and sheep . The comThree key features that make mtDNA as an attractive marker for studying origin and diversity include high mutation rates, maternal inheritance, and availability in large quantities in the cell, facilitating easy isolation . The higRangoju et al.  used RAPRestriction fragment length polymorphism (RFLP) analysis of the mtDNA molecule by –15 reveaClearance for this research was granted by NACOSTI permit number NACOSTI/P/15/62961/8524. A purposive sampling strategy was adopted during the field surveys and collection of blood samples. Local and exotic rabbits were sampled from farmers practicing backyard small-scale rabbit farming in Kenya. Rabbits between 6 months and 5 years old, a male and a female whenever possible were sampled from each homestead. In some homesteads, only 1 rabbit was sampled due to genetic relatedness among the rabbits. A total of 111 rabbits were sampled from Kakamega, Vihiga, and Bungoma counties in the western region, Laikipia and Nyandarua counties in the central region, and Kitui, Machakos, and Makueni in the eastern region of the country.The selected rabbit was restrained, and blood was drawn from the marginal vein of the ear. The needle was jabbed and blood drawn to a 75% filling of the 10 ml syringe. All the blood was applied on four spots on a labelled FTA classic card (Whatman Biosciences) for each rabbit and allowed to dry under a shade. The FTA cards were packaged in paper envelopes with silica gel desiccant and transported to the laboratory. The FTA cards were stored away from direct sunlight at room temperature until they were used for DNA extraction.μL reaction volume containing 2.5 μL of 125 ng DNA, 5ul 5X Q5 buffer, 2 μL 10 mM dNTPs, 1.25 μL each 10 μM forward (CCACCATCAGCACCCAAAGCTG) and reverse (TGGGCCCGGAGCGAGAAGAG) primers, 12.4 μL PCR grade water, and 0.6 μL (2 U/μL) Q5High Fidelity DNA polymerase (New England Biolabs). Amplification conditions were set as follows: initial denaturation at 95°C for five minutes, 35 cycles of 95°C for 15 seconds, 60°C for one minute, and 72°C for two minutes and a final extension at 72°C for seven minutes on a PEQLAB thermocycler. The amplicons were purified using a DNA purification kit (ThermoFisher Scientific), and their concentrations were measured on a nanodrop. These concentrations were standardized to at least 50 ng/μL and sent for sequencing at Macrogen, the Netherlands.mtDNA was extracted using the Chelex protocol . DNA conOryctolagus cuniculus mitochondrion complete genome (accession number NC_001913.1) [Trimming sequences of the amplified fragment from Macrogen on CLC Main Workbench 7.9.1 (QIAGEN) resulted in 111 sequences. Subsequent comparisons and analyses were restricted to a 263-base pair region incorporating the hypervariable segment I (HVSI) from position 15,595 to 15,858. The contig sequences generated on CLC Main Workbench 7.9.1 were aligned using Clustal W in MEGA 6.0 against ST was calculated to estimate genetic differentiation and hence the population genetic structure. Relationships among the haplotypes were further inferred on a haplotype network constructed using Population Analysis with Reticulate Trees (PopART) software [Mitochondrial DNA haplotypes and their distribution in various regions, number of polymorphic sites, haplotype diversity, and nucleotide diversity were determined using DnaSP version 5.10.01 . Geneticsoftware . Geneticsoftware . The staAlignment of the 263-bp fragment gave a total of 17 single nucleotide polymorphisms (SNPs) with 16 transitions and 1 transversion. These polymorphic sites generated eight unique haplotypes. Among the eight haplotypes observed in this study, haplotype seven was the most common, occurring in 55% individuals, followed by haplotype three in 36% of individuals. Haplotypes five and six occurred in one individual rabbit from Nyandarua and Machakos counties, respectively. Haplotype two occurred in the rabbit population from Vihiga County and among the pure breeds while haplotype eight was found among the rabbit population from Bungoma and Machakos counties. Haplotype distribution in the sampled regions is represented in All the haplotypes from the eight populations were polymorphic with the number of haplotypes ranging from two to four . A wide Population structure as revealed by pairwise FST estimates revealed that the rabbits sampled from the eastern and central regions had the least genetic distance (−0.01181) compared with rabbits from eastern and western regions being more genetically distant (0.09382).Inference of the origins on the unrooted Maximum-likelihood tree incorporating the eight haplotypes and the 32 sequences downloaded from GenBank is shown in Alignment of the eight haplotypes and published sequences of the European rabbit revealed a total of 24 unique haplotypes. The current study obtained five new haplotypes , whereas the other three haplotypes  are identical to previously published haplotypes [p=0.035 (<0.05), suggesting a significant genetic difference in the studied populations and the incorporated haplotypes.Analysis of molecular variance (AMOVA) among and within the populations revealed a significant genetic differentiation among and within the studied regions The two indices for evaluation of mtDNA variation and genetic diversity of populations or breeds are haplotype diversity (Hd) and nucleotide diversity (Pi). Overall, the average haplotype 0.40702) and nucleotide (0.01494) diversities observed were low, indicating low genetic diversity of domesticated rabbits in Kenya. This could be attributed to breed exchange between the domesticated and exotic breeds by farmers. To confirm an expected effect of substantial structuring and low genetic diversity, it was observed that the number of rabbits that shared haplotype 3 was 40 whereas 61 individuals shared haplotype 7. Similar results were reported by Long et al.  and nucl. In thisOther causes of low genetic diversity include founder effects during population expansion because of domestication and high selection pressure during commercial animal production which leads to an inherent decrease in strain variability . ReducedLow genetic diversity is not good for livestock and even crops' improvement since loss in diversity could lead to loss of some lineages which could be harboring desirable traits. A possible mitigation strategy is the establishment of pedigree records followed by deliberate breeding strategies to further diversify desirable traits that are becoming extinct. This study has revealed rare haplotypes that can be conserved to be exploited in future breeding strategies. The haplotype network revealed distinct and heterogeneous population structuring in the rabbits sampled from western, central, and eastern regions in Kenya.AMOVA analysis among and within the entire population revealed a clear structuring in the population, suggesting underlying genetic differences in the population. The population genetic structure was further revealed on the haplotype network with population structuring and a heterogeneous population in rabbits sampled from western, central, and eastern regions of Kenya. The genetic structuring observed here can be attributed to the controlled breeding and mating in the sampled rabbit populations. This is because these rabbits are mostly caged or isolated, and as a result, they undergo a high degree of nonrandom mating and social structuring. Moreover, populations that are isolated undergo high differentiation, as observed by Hewitt  and in tOryctolagus cuniculus algirus whereas lineage B is predominantly the subspecies Oryctolagus cuniculus cuniculus [Rabbit domestication has been attributed to a single origin in France . Biju Duuniculus . All domuniculus . PhylogeNative rabbits from Middle Egypt belong to lineage A . The stuIn the current study, we inferred that domesticated rabbits in Kenya belong to lineage B and originated in Europe. Network analysis of the phylogenetic relationship of the eight haplotypes detected in this study and sequences retrieved from GenBank revealed associative patterns with the European rabbits, herein referred to as European exotics, such as rabbit in Spain and Argente de Champagne, whose origin is Western Europe . The res


Periplaneta americana) is a globally invasive pest that can cause significant economic loss and threaten human health. Although it is abundant and lives in close proximity to humans, few studies have investigated the genetic diversity of P. americana. Our study analyzed 1,053 P. americana and other Periplaneta species' samples from different locations in China and the United States. A traditional tree‐based method using 17 unique mitochondrial COI haplotypes of P. americana and 20 haplotypes of the other Periplaneta species accurately identified P. americana with a barcoding threshold of 5.1%. To identify the population genetic structure of P. americana, we investigated wingless gene and pooled them with obtained mtDNA data for a combined analysis. Although the genetic diversity of the USA group was relatively higher than the China group, the number of haplotypes and alleles of both groups was small. The analysis of molecular variance (AMOVA), intraspecific phylogeny, and haplotype networks indicated that P. americana had very little global genetic differentiation. The weak geographic genetic structure might reflect the human‐mediated dispersal of P. americana. Despite no apparent phylogeographic assignment of mtDNA and nuclear lineages was observed in both BI trees, the integrated COI sequence data identified four distinct P. americana haplotype groups, showing four ancient maternal lineages of P. americana in China and the United States.The American cockroach ( Periplaneta americana specimen from 18 sites in China using mtDNA and nDNA markers and then compared the genetic pattern of P. americana in China with the Americas. Although no clear pattern of genetic structure was detected within P. americana, four mitochondrial lineage units of P. americana showed clear genetic signatures of ancestor haplotypes. Additionally, we analyzed the COI barcode region, using traditional tree‐based, ABGD, and GMYC species delimitation methods to determine the intraspecific genetic distance threshold of P. americana in a larger range of sampling. Compared to GMYC and ABGD approaches, the traditional tree‐based method could accurately and effectively identify P. americana from other five Periplaneta cockroaches species with barcoding threshold 5.1%.Here, we assessed genetic diversity and genetic structure of  There are approximately 53 species of the Periplaneta genus  from 31 sampling locations in China  were amplified by PCR with the primers LCO1490/HCO2198 , and 0.5 μl of 25 μM respective primers. Successfully amplified fragments were purified using the DNA agarose gel extraction kit (TsingKe) and sequenced by ABI PRISM 3730 DNA sequencer .Total DNA was extracted from muscle tissue using the TsingKe Genomic DNA kit (TsingKe). The partial sequences of mitochondrial COI gene (658 bp) and nuclear 2.3P. americana specimens, 235 P. fuliginosa specimens, 52 P. australasiae specimens, and 3 P. brunnea specimens) were successfully amplified. Forty‐eight individuals from each of P. americana COI haplogroups  were selected for wingless amplification to corroborate the patterns of genetic structure, differentiation, and divergence of P. americana populations. The dataset, which included 853 COI and 48 wingless sequences, was submitted to GenBank (https://www.ncbi.nlm.nih.gov/) under the accession numbers MF149138–MF149711, MH184206–MH184379, and MK658782–MK658829. In addition to the new data we collected, 200 COI and 68 wingless sequences from GenBank for Periplaneta species were added for analysis (a detailed list of previous GenBank records of Periplaneta spp. is available on Dryad repository: https://doi.org/10.5061/dryad.280gb5mm1). We grouped the P. americana samples by country. The groups from China and the United States included 564 and 195 specimens, respectively. DNA SeqMan (DNAStar Inc.) was used to assemble sequences. Sequences were aligned using the program CLUSTAL W in MEGA 5.0 , and nucleotide diversity (iP).In total, mitochondrial COI sequences of 853 cockroach specimens (including 563 p < .8). All genotype information for each sample was presented on Dryad repository: https://doi.org/10.5061/dryad.280gb5mm1.For the nuclear marker, direct sequencing of PCR products indicated that many individuals were heterozygous. Alleles of heterozygous individuals were identified with DnaSP 5.10.01  tree was performed with bootstrap analysis  in MEGA 5.0 based on the Kimura 2‐parameter (K2P) distance model. Furthermore, intra‐/interspecific genetic distances with the same model were calculated.In addition to traditional barcoding analysis , we used GMYC and ABGD approaches to examine the congruence of OTUs . GMYC is a tree‐based approach for the delimitation of species. An ultrametric tree was produced using BEAST v1.10.4  with default parameters .The ABGD  and analysis of molecular variance (AMOVA) were performed using ARLEQUIN v3.5 /4FST. These analyses were conducted to assess genetic variation according to geographic distribution. The spanning network of COI haplotypes was constructed using TCS 1.21 at 95% confidence level  for COI sequences and HKY  for wingless sequences. Subsequently, BI analysis of nucleotides was implemented with MrBayes 3.2.2 , and the results were compared with the P. americana group from the United States  and nucleotide diversity (iP) within each sampling site in China ranged from 0.0 to 0.625 and from 0.0 to 0.01179, respectively. Among them, almost half of all Chinese sampling sites showed only one haplotype, and the haplotype diversity and nucleotide diversity of these sites were zero. When the P. americana samples from China were considered as a single group, they indicated relatively low haplotype diversity (0.375) and nucleotide diversity (0.00659) when compared to samples from the United States . Inclusion of 68 additional wingless sequences from GenBank from the United States produced a final alignment of 378 bp for 116 individuals. A total of seven distinct wingless alleles were identified with high probability  clustered together with a high support value . The maximum intraspecific divergence value (5.1%) within Periplaneta species was observed in P. americana, followed by P. australasiae (1.9%) and P. fuliginosa (1.2%). Higher levels of genetic distance were found between those six Periplaneta species. The minimum interspecific divergence was 5.8% between Periplaneta sp. and P. fuliginosa. When comparing P. americana to other Periplaneta species, the minimum and maximum interspecific divergence values were 11.0% and 16.9%, respectively. COI analysis showed no overlap between maximum intra‐ and minimum interspecific divergence values and a barcoding gap was apparently present . P. brunnea, P. fuliginosa, P. australasiae, P. japonica, and P. sp can be distinguished with prior intraspecific divergence between 0.77% and 1.29%. However, P. americana had two genetic groups with prior genetic distance thresholds between 0.77% and 1.29%. Using the values between 2.15% and 5.99%, the species were partitioned into four groups  and the USA groups formed four major mitochondrial clades  and per‐generation migration rate (Nm) between pairs of the 18 Chinese sampling sites were computed (data are available on Dryad: https://doi.org/10.5061/dryad.280gb5mm1). FST ranged from −0.250 to 1.000. A comparison of 64 of the 153 pairs of sampling sites showed no significant genetic differentiation (p > .05), implying that more than 50% of the pairs of sampling sites formed one genetic group. These results suggest that the 18 sampled areas of P. americana lacked genetic structure, which agreed with the phylogenetic and network analyses. When all Chinese specimens were grouped (18 sampling sites) to compare pairwise FST values with the USA samples, significant differences in haplotype and allele frequencies at both the COI  and wingless  loci were observed. Mean FST values within the 18 Chinese sampling sites (0.16 ± 0.18) based on the COI gene were significantly lower than that between China and the USA groups. Despite that, the American and Chinese groups both shared the same clusters and haplotype  can be attributed to variation within sampling positions. The rest of a small but highly significant amount of genetic variance corresponded to differences between countries  and among sampling sites within countries  led to an overestimation of species diversity by the ABGD method  of the genetic variation occurred within sampling sites and countries (Table P. americana groups from China and the United States. This high population admixture would lead to a wide spread of alleles and promote an increase in genetic diversity of invasive species (Gonçalves et al., Population genetic structure and genetic diversity can provide important biological information for the study of invasive species (Wongsa, Duangphakdee, & Rattanawannee,  Figures  and 4. TP. americana populations was observed in both mtDNA and nDNA markers. The analysis of COI and wingless fragments defined only 17 haplotypes from 741 individuals and 7 alleles from 113 individuals, respectively. Low population variation is common in other insects (Mazur et al., P. americana native to Africa. However, the successful distribution of P. americana around the globe shows that invasive species with low genetic diversity can also be widely distributed and spread explosively (Wang, Li, & Wang, Unexpectedly, the relatively low genetic diversity within 4.3P. americana COI haplotypes showed four divergent COI haplogroups (Figure P. americana. In contrast to mtDNA, there is recombination in autosomal DNA. Recombination would distort the information on evolutionary history carried by the DNA sequence (Zhang & Hewitt, wingless phylogenetic trees (Sota & Sasabe, Although no apparent phylogeographic assignment of mtDNA and nuclear lineages was observed in both BI trees, phylogenetic analyses based on s Figure . MitochoP. americana in China and the United States were each from three genetically divergent source groups, with a total of four clades. However, the rate of divergence for COI of Blattodea taxa was unknown, and a “universal” clock rate would cause error estimation in divergence time (Pfeiler, Bitler, Ramsey, Palacios‐Cardiel, & Markow, P. americana to estimate the ages of population genetic divergences in this species. Additionally, haplogroups B and D were shared between the USA and Chinese groups, as phylogenetic analysis did not exhibit obvious association between the haplotype phylogeny and geographic distribution (Figure P. americana, which is considered to be ongoing.A number of successful applications of COI in phylogeographic studies have been reported (Inoue et al., n Figure . This man Figure , which in Figure . Frequen5P. americana groups in China. Taking into consideration the scale of individuals tested, it is also the largest phylogeographic study of this cockroach species. Although no clear pattern of genetic structure was detected within P. americana, four mitochondrial lineage units of P. americana showed clear genetic signatures of ancestor haplotypes. P. americana is a non‐native invasive species in China and is native to tropical Africa yet molecular evidence on the biogeographical origins of P. americana remains unresolved. Future researches should focus on collecting samples from African populations to better understand the origin of P. americana and its invasion history throughout the world. Our cockroach samples presented a mix of individuals from genetically distinct source groups. Despite these nongeographic groupings, our study showed that traditional tree‐based methods could accurately identify P. americana with a barcoding threshold of 5.1%. We believe that the mitochondrial COI gene can be effectively used in studying intra‐ and interspecific divergences of cockroaches.This is the first study based on the COI gene to analyze the genetic diversity of None declared.Zhang X conceived the project. Ma J and Liu J collected samples. Ma J, Liu J, and Shen Y performed the experiments and analyzed the data. Ma J, Fan Z, Zhang X, and Yue B wrote the manuscript with help from all of the authors. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


The threatened eastern wolf is found predominantly in protected areas of central Ontario and has an evolutionary history obscured by interbreeding with coyotes and gray wolves, which challenges its conservation status and subsequent management. Here, we used a population genomics approach to uncover spatial patterns of variation in 281 canids in central Ontario and the Great Lakes region. This represents the first genome-wide single nucleotide polymorphism (SNP) dataset with substantial sample sizes of representative populations. Although they comprise their own genetic cluster, we found evidence of eastern wolf dispersal outside of the boundaries of protected areas, in that the frequency of eastern wolf genetic variation decreases with increasing distance from provincial parks. We detected eastern wolf alleles in admixed coyotes along the northeastern regions of Lake Huron and Lake Ontario. Our analyses confirm the unique genomic composition of eastern wolves, which are mostly restricted to small fragmented patches of protected habitat in central Ontario. We hope this work will encourage an innovative discussion regarding a plan for managed introgression, which could conserve eastern wolf genetic material in any genome regardless of their potential mosaic ancestry composition and the habitats that promote them. Neutral theory provides a strong foundation for the application of conservation genetics, which identifies evolutionary distinct lineages that are vulnerable to genetic erosion or extinction due to reductions in population sizes ,2,3. HisIsland species have been used as archetypal evolutionary models representing the consequences of isolated populations that can persist despite low effective population sizes ,6,7,8. HCanis anthus ) complex . Their rThe viewpoint described above prioritizes conserving genetic diversity across a gradient of admixed individuals. Adopting this view, canids of varying wolf and coyote ancestry should be conserved on the Ontario landscape to maintain unique eastern wolf genetic material and maximize evolutionary potential. A second viewpoint prioritizes ecological function and seeks to conserve roles that rare species play in ecosystems . In the We find that eastern wolves represent a unique genomic cluster that is geographically isolated to patchy regions of central Ontario and possibly southern Quebec, with a general increase in admixture outside of protected areas. Their unique genetics provides a solid foundation to identify them as a conservation priority, especially given their low effective population size and degree of isolation. Further genomic assessment of canids in southern Quebec would help clarify the extent of the eastern wolf range outside of Ontario. Moving forward, conservation of the eastern wolf genome would benefit from the connection of current protective zones across the Ontario landscape.


Silene ciliata across its southernmost distribution limit. We sampled three populations across an altitudinal gradient from 1850 to 2400 m, and we replicated this sample over three mountain ranges aligned across an E-W axis in the central part of the Iberian Peninsula. We genotyped 20 individuals per population based on eight microsatellite markers and used different landscape genetic tools to infer the role of topographic and environmental factors in shaping observed patterns along the altitudinal gradient. We found a significant genetic structure among the studied Silene ciliata populations which was related to the orography and E-W configuration of the mountain ranges. IBD pattern arose as the main factor shaping population genetic differentiation. Geographical barriers between mountain ranges also affected the spatial genetic structure (IBR pattern). Although environmental variables had a significant effect on population genetic diversity parameters, no IBE pattern was found on genetic structure. Our study reveals that IBD was the driver that best explained the genetic structure, whereas environmental factors also played a role in determining genetic diversity values of this dominant plant of Mediterranean alpine environments.The study of the drivers that shape spatial genetic structure across heterogeneous landscapes is one of the main approaches used to understand population dynamics and responses in changing environments. While the Isolation-by-Distance model (IBD) assumes that genetic differentiation increases among populations with geographical distance, the Isolation-by-Resistance model (IBR) also considers geographical barriers and other landscape features that impede gene flow. On the other hand, the Isolation-by-Environment model (IBE) explains genetic differentiation through environmental differences between populations. Although spatial genetic studies have increased significantly in recent years, plants from alpine ecosystems are highly underrepresented, even though they are great suitable systems to disentangle the role of the different factors that structure genetic variation across environmental gradients. Here, we studied the spatial genetic structure of the Mediterranean alpine specialist  Species resilience to changing environments largely depends on their genetic diversity . Thus, kper se is the main driver of genetic structure and considers that other factors like landscape features, range boundaries or environmental characteristics influencing gene flow are not relevant  pattern . It assurelevant . Nowadayrelevant . Thus, trelevant . Both IBrelevant . Isolatirelevant . In mounrelevant . All therelevant .Isolation processes related to geographic and environmental distances may produce profound demographic and genetic outcomes for plant populations within species distribution ranges . SpeciesPlants from alpine ecosystems provide a very interesting context to disentangle the various mechanisms that structure genetic variation within and among populations at different scales related to patterns of isolation between populations (IBD/IBR vs. IBE). Several studies have shown adaptive genetic differentiation and local adaptation processes related with the strong environmental variability in these ecosystems using phenotypic, genetic, and/or genomic data e.g., . In someSilene ciliata Poiret (Caryophyllaceae), distributed along the elevational range of the species in central Spain. As an alpine species, the distribution range of S. ciliata has experienced historical environmental fluctuations related to glaciations  Are S. ciliata populations genetically structured across mountain ranges and elevational gradients? (ii) If so, can observed genetic structure patterns be explained by isolation-by-distance (IBD), isolation by resistance (IBR) and/or isolation-by-environment (IBE)? and (iii) How do these factors affect genetic diversity?Mediterranean mountain ranges encompass a territory with wide environmental and geographical heterogeneity where many species reach their southernmost distribution range limits. They are also rich in endemic species and are biogeographically important as glacier refuges . In thisciations  and is pciations , 2007. Tciations . Our aimMost genetic approaches are addressed to species with limited distribution ranges, whereas more widespread species have not deserved so much attention from the conservation genetics community. The results of this study will provide useful information for the conservation of the genetic variation of a dominant species of the endangered Mediterranean alpine ecosystems  in one oSilene ciliata Poiret (Caryophyllaceae) is a dwarf cushion perennial plant which inhabits Mediterranean alpine habitats with marked environmental gradients. It is pollinated by nocturnal insects, mainly belonging to the genus Hadena , and diurnal insects . DNeasy Plant minikit  was used for DNA extraction of 10–20 mg of dried S. ciliata tissue. Based on a previous study (N = 36). MICRO-CHECKER ; (ii) number of private alleles (PA); (iii) mean number of alleles per locus (A); (iv) observed heterozygosity (Ho); (v) expected heterozygosity (He); and (vi) inbreeding coefficients Fis defined as [1-(Ho/He)] and (v) Fi, calculated as the probability that the two alleles at a locus are identical by descent following the definition of o, He and inbreeding coefficient Fi corrected for null alleles. We also tested for deviances from Hardy–Weinberg equilibrium (HWE) per locus in each population following diveRsity v. 1.9.90 R package  total number of alleles  genetic differentiation among and within the nine populations, (ii) genetic differentiation among the three mountain ranges considering the genetic variance among populations within mountain ranges and within populations and (iii) genetic differentiation between environments  considering the genetic variance among populations within environments and within populations , we tested for genetic differentiation measured as Fns Table . Fst val package . Conside package  to contradegenet R package (find.clusters function (adagenet R package) to study the optimal number of clusters regarding the maximum drop in BIC values. We used the a-score to set the number of PCs retained in the DAPC to control the possible overfit, which is a measure of the trade-off between power of discrimination and over-fitting the model   as imple package . In DAPC package  determinhe model .K clusters from one to nine. Each run assumed a burn-in period of 106 iterations, followed by 107 MCMC iterations considering the model of correlation frequencies and admixture origin. To elucidate the most plausible value of K, we followed the approach described in We also applied a Bayesian clustering method as implemented in STRUCTURE v 2.3.4 . We perf6 MCMC iterations after a burning process of 105 simulations, sampling each 1000 steps, ranging K values between 1 and 10 and applying spatial and null alleles corrections, to confirm analysis made with DAPC and STRUCTURE.A Geneland analysis  was alsoWe wanted to elucidate whether the observed genetic structure was caused by geographical distance (IBD), environmental conditions (IBE), geographical conformation of the landscape (IBR) or a combination of these factors. To achieve this, we first obtained four different types of distance matrices:st distance between the nine populations using FreeNA (st/(1-Fst)] and log(Euclidean distance), respectively, to linearize their relationship ((i) Genetic distance matrix, calculated as pairwise Fg FreeNA  to corretionship ; (iii) Ttionship . As annutionship , 2007, wtionship ; and . First, the partial Mantel correlation between one of the hypothesis  and the genetic distance (G.Dist), controlling for the effect of a second hypothesis  was calculated using partial Mantel test (G.Dist ∼ IBD| IBR). Second, a second partial Mantel test was developed but calculating the correlation between the genetic distance and the second hypothesis, controlling for the effect of the first hypothesis (G.Dist ∼ IBR| IBD). The relative support for IBD  relative to IBR  is the difference between the partial correlations of the two tests (IBD| IBR-IBR| IBD) and vice versa ,b. Thus,adegenet , ade4  as dependent variables and annual Tmax and Tmin as independent variables, considering the geographical coordinates of the locations a random factor. To account for non-linear responses of the environmental variables, we also tested models including their squared values. We tested for normality and homoscedasticity of the model residuals and made the necessary transformations when required. We also tested the possible spatial autocorrelation of the residuals performing a Moran’s I test  between the “full” model  and the “null” model  tested the effect of a given factor after applying the Bonferroni correction. We also performed an AIC rank test to select the best fitting model when more than one environmental variable had a significant effect on a genetic diversity estimator and to ensure the improvement of the “full” versus the “null” model.To study the possible relationship between genetic diversity estimators and geographical and environmental variables, we also developed different geographically explicit generalized linear mixed models  using genetic, geographical and environmental information. The models were built using spaMM R package . We useds I test . For eacP = 0.02). Observed heterozygosity values (Ho) were lower than expected heterozygosity values (He) for all populations except MOR where Ho was higher than He. Populations NAJ and SES had similar Ho and He values. All populations except NAJ and PEN (GDM) departed from the H&W equilibrium, and they showed a significant excess of homozygotes across loci (Table P < 0.05) except MOR (Fis = -0.08), NAJ (Fis = -0.01) and SES (Fis = -0.01), which were not significantly different from zero .The eight microsatellites scored a total of 107 different alleles across all individuals with an average of 5.2 alleles per locus. Number of alleles per population (Na) varied from 38 to 57 and number of alleles per locus from 4.30 to 6.05   than among populations (FPop/T) , although both were significant. The Fst hierarchical structure analyses of population nested within mountain ranges showed that all levels contributed to the hierarchical genetic structure with different magnitudes. Mountain range (FMt/T)  and population nested within mountain range (FPop/Mt)  showed a small but significant value. Individuals within populations showed the greatest genetic divergence (FInd/Pop/Mt) . The Fst hierarchical structure analyses of population nested within environment found no significant effect of environment (FEnv/T)  and a small significant value for population nested in environment (FPop/Env) . As in the Fst hierarchical structure analyses, individuals within populations had the greatest genetic divergence values (FInd/Pop/Env) . Results are summarized in Table When testing for population structure, hierarchical FK = 2 and K = 3 structures based on the BIC curve which represents the plausible number of clusters in the data   Figure . Genelan) Figure .IDB arises as the strongest overall hypothesis regarding to the relative support values of the RCM matrix Table , presentP < 0.05) and He  and a quadratic relationship between Tmin and mean number of alleles per locus (A)   and Ho  as shown by the K = 2 conformation in the clustering analysis. On the other hand, the K = 3 conformation was clearly related to the three mountain ranges in STRUCTURE, and with an admixture between BEJ and GRE in DAPC. These results show the relevance of the spatial configuration of the landscape at the mountain range level on the genetic structure. This could be related with the colonization pattern of the species along the East-West oriented axis of the Sistema Central  doi: 10.21950/GSTZ26.The dataset generated and used in this publication can be found in the Universidad Rey Juan Carlos data repository e-cienciaDatos (JM-L, AG-F, CL-R, and JI designed this study. JM-L and AG-F collected the samples and performed the laboratory work. JM-L, CG, AG-F, and DD analyzed the data. JM-L wrote the paper with the help of CG, CL-R, and JI. All authors reviewed the paper 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.


Dipodomys merriami. We characterized genetic diversity and structure with microsatellites loci, estimated home ranges and movement of individuals using telemetry—one of the first with rodents, generated a set of individual and composite environmental surfaces based on hypotheses of variables influencing movement, and assessed how these variables relate to individual‐based gene flow. Genetic diversity and structure results evidenced a family‐induced pattern driven by first‐order‐related individuals, notably determining landscape genetic inferences. The vegetation cover and soil resistance optimized surface (NDVI) were the best‐supported model and a significant predictor of individual genetic distance, followed by humidity and NDVI+humidity. Based on an accurate definition of thematic resolution, we also showed that vegetation is better represented as continuously  distributed. Hence, with a nonsubjective optimization framework for RS and telemetry, we were able to describe that vegetation cover, soil texture, and climatic variables influence D. merriami's functional connectivity at a microgeographic scale, patterns we could further explain based on the home range, habitat use, and activity observed between sexes. We describe the relationship between environmental features and some aspects of D. merriami‘s behavior and physiology.Gene flow in animals is limited or facilitated by different features within the landscape matrix they inhabit. The landscape representation in landscape genetics (LG) is traditionally modeled as resistance surfaces (RS), where novel optimization approaches are needed for assigning resistance values that adequately avoid subjectivity. Also, desert ecosystems and mammals are scarcely represented in LG studies. We addressed these issues by evaluating, at a microgeographic scale, the effect of landscape features on functional connectivity of the desert‐dwelling  Notably, studies regarding the importance of elements promoting gene flow on rodents from desert environments are significantly lacking.Rodents are considered a key ecological component of deserts due to the fundamental role they play for the structure and dynamics of these ecosystems, especially by the dispersal of seeds and soil removal . In particular, the Merriam's kangaroo rat Dipodomys merriami is one of the smallest species in the genus, with a distribution that encompasses the desert region of southwestern United States and northern Mexico. It is a burrow‐dwelling, nocturnal rodent characterized by a long tail with a tuft of hair at the tip, large rear legs for bipedal locomotion, and with sexual dimorphism where males are larger than females. It is considered solitary and territorial, characterized by dispersing adult males (mean of 60 m) and phylopatric females that make parental investment  and always building their burrows under bushes like mesquite and creosote (Larrea tridentata)  is affected by ambient temperature  defines what is known as home range Burt, ; a home Dipodomys merriami in northern Mexico. For that purpose, we first characterized genetic diversity levels and population genetic structure; next, we generated a set of environmental surfaces based on hypotheses of variables influencing the species movement, to finally assess how these variables relate to individual‐based genetic differentiation. In order to obtain estimates of the species habitat use and home range that will inform our genetic results, we evaluated movement of individuals with telemetry. Given that D. merriami is tightly linked to shrub cover and occurrence of fine‐sized soils for protection against predators, feeding, and burrow construction, we expected that (a) females and males will mostly overlap home ranges; (b) the presence of vegetation associated with sandy and gravel soils would be a key predictor of gene flow, while uncovered habitat  would restrict movement; (c) environmental variables  will significantly influence patterns of functional connectivity in this desert‐dwelling rodent.We here apply the optimization framework developed by Peterman et al.  and Pete22.1Prosopis glandulosa) and creosote bush (Larrea tridentata). Despite the zone is relatively flat, the landscape has been described as a toposequence, on the base of landforms, soils and vegetation units organized along an elevation gradient , “nopalera” (Opuntia sp.), and “pastizal” (Prosopis sp.)  of equal length radiating from a chosen center point, each line with live traps (T) separated between them at certain intervals . Sherman live traps (7.6 x 7.6 x 33 cm) were placed along each line, separated by 5 m, and baited with a mixture of rolled oats, peanut butter, and vanilla extract. Additionally, two more traps were placed at 1 m distance from each burrow entrance; thus, each web consisted of 22 traps , a protected natural area and a Man and Biosphere (MAB‐UNESCO) site Montaña,  Figure . The MBRs Figure . Our sams Figure . Trappeds Figure  and with2.2D. spectabilis, from which we successfully amplified nine with D. merriami  and linkage disequilibrium (LD) across the entire population using Fisher's exact test  with Rousset, . The valRousset, . We chec R Dyer, , while r R Dyer, .structure v.2.3.4  to the model by considering each trapping web as a different location. The posterior probability lnP(K)  of the information . This procedure has shown to improve accuracy on estimates of genetic structure  with adegenet in R  and Euclidean distances. Additionally, a Mantel correlogram was estimated based on 50 m classes considering the mean dispersal distance reported for D. merriami  was estimated as the proportion of shared alleles , temperature, elevation, plant cover (hereafter vegetation), and soil. Humidity and temperature data were collected using HOBO Data Loggers , and elevation was obtained with a GPS (Garmin). These three variables were measured at each trap location and at the center of the trapping web , for a total of 315 points; the values for the entire study area were obtained by the krigging interpolation method . According to the U. S. Geological Survey ( https://phenology.cr.usgs.gov/index.php), values for this index range from −1 to 1, based on the different behavior of vegetation and soils in the red and near‐infrared spectral regions: areas of barren rock or sand usually show very low NDVI values (0.1 or less), while sparse vegetation such as grasslands or shrubs may result in moderate NDVI values (approximately 0.2 to 0.5). Second, we performed a supervised classification based on our field data using the high‐resolution (approximately 1.3 m) imagery from Google Earth. This surface corresponded to a binary classification (presence/absence) of vegetation (hereafter Feature surface).We used two approaches to create the vegetation and soil surfaces. First, we calculated the normalized difference vegetation index ] and Ricker [y = r exp‐bx] are two exponential‐based functions used for ecological modeling, differing in the curve shape of the relationship they are modeling. This curve shape is mainly determined by shape (x) and magnitude (b) parameters, which produce a saturating exponential (growth or decay) curve for the monomolecular function, and a hump‐shaped curve (skewed to right or left) for the Ricker function  following two steps: First, all surfaces were independently optimized from pairwise resistance distances estimated with gdistance in R  and pairwise scaled and centered resistance distance, respectively. MLPE parameterization was done with lme4 . The lmem were fitted by the maximum‐likelihood population effects (MLPE) parameterization, to account for the nonindependence of values within pairwise distance matrices  with adehabitatHR Calenge,  in R v.3 Worton, , avoidin Worton,  that oth33.1p < 0.05); these same loci showed evidence of null alleles but not stuttering errors were detected. Because D. merriami‘s social structure encompasses groups of individuals with different degrees of relatedness (see relatedness results below), some evidence of deviation from HWE or null alleles is expected , 37 in T2, and 21 in T3. Eight microsatellite loci were polymorphic across all samples  and the number of effective alleles from 3.2 to 17.7 (mean=8.16). The mean observed heterozygosity and the unbiased expected heterozygosity across loci were 0.65 and 0.84, respectively; overall structure and DAPC with both datasets were equivocal. Five clusters were detected by structure for the full dataset (n = 76), with both statistics (mean lnP(K) = −2,628.435 and ∆K = 12.331) .Results about population genetic structure using Jombart, , we perfn = 59), one genetic cluster was obtained with structure (K = 1) by the mean lnP(K) = −2,195.545, whereas 11 clusters were detected with ∆K (20.781) , obtaining differentiation between groups but with clusters overlapping spatially .Regarding the unrelated dataset  between individuals for LG analyses was estimated based on the unrelated dataset , while the Mantel correlogram exhibited only one small positive and significant value at 1,700 m  , with different functional forms for temperature (inverse Ricker) and elevation (inverse–reverse monomolecular), in which resistance values were lowest around 44% humidity, 30ºC temperature, and 1,152 m Figure . Accordi3.3p = 0.003). The largest home range was a male's (R8), completely overlapping with that of another male (R11) and a female (R13). A 77.4% home range overlap was observed between a male and a female (radios R7 and R15), while among R8, R10, R11, and R13 varied from 10.3% to 100%  Table . We obtaD. merriami individuals with radiolocations, during 8 days, one from 21:30 to 00:55, and the other from 23:00 to 01:10 , Opuntia sp. (40%), J. dioica (18%), and P. glandulosa (6%), with no significant differences between sexes.Two activity cycles were recorded for the nine 0 Figure . Three p44.1Dipodomys merriami at the microgeographic area of the study are likely associated with the ecological complexity and social structure characterizing this desert‐dwelling species. Our results show moderate to high levels of genetic diversity when compared with other Dipodomys species  enabled us to suggest a link between the observed genetic pattern and the ecological processes underlying it . Finding these mechanistic links in landscape genetics research is one of the goals of the optimization framework we implemented , suggesting a strong influence of anthropogenic activities on the species movement. On the other hand, Khimoun et al. (Setophaga plumbea).Our findings that gene flow in n et al.  showed tD. merriami, exhibiting that gene flow is strongly limited on open areas and facilitated where shrub cover with sandy and gravel soils is present. The role of vegetation as a facilitator of gene flow has been demonstrated for other rodent species occupying a variety of habitats with different levels of heterogeneity. For instance, Munshi‐South  inhabiting fragmented landscapes like agroecosystems . Indeed, D. merriami exhibits a wider habitat use that includes preferentially L. tridentata, but also Opuntia sp., J. dioica, and P. glandulosa, highlighting the key role of this generalist species on desert ecosystem dynamics , a heat intolerant, and cool microclimate restricted species for which an increase in temperature adversely affects gene flow  refers to the temperature gradient where an organism's metabolism is minimized but also leads to higher rates of water loss, which ranges between 29º and 34ºC for this species  for water conservation  that promote gene flow across the desert environment. At the same time, these nonlinear responses exhibit the limits imposed to kangaroo rats by the desert conditions, directly impacting its genetic connectivity. Such a fine‐dependence on local microclimate has been observed for the terrestrial woodland salamander  surfaces. Moreover, our estimation of the species’ home range, habitat use, and activity based on telemetry and a probability‐based statistical kernel estimator, not only significantly contributed to the interpretation of D. merriami's functional connectivity, but it is also one of the first studies using telemetry performed with rodents  on individual movement and gene flow in natural populations has been challenged by the need to avoid subjectivity when assigning resistance values and landscape scales (Khimoun et al., The authors declare that they have no conflicts of interest.A.F.M., M.A.L.B. and E.V.D. conceptualized and designed the research; also performed fieldwork with other collaborators. A.F.M. performed laboratory work. A.F.M. and M.A.L.B. conducted data analyses with contributions of R.J.D. and E.V.D. All authors contributed in the interpretation of results and writing of the paper.10.5061/dryad.dk73qp7Microsatellites genotypes are available from the Dryad Digital Repository at doi: Click here for additional data file.


Planes crabs collected from oceanic flotsam and sea turtles. Our results indicate that species diversity in this clade is low—likely three closely related species—with no evidence of cryptic or undescribed species. Moreover, our results indicate weak population differentiation among widely separated aggregations with genetic indices showing only subtle genetic discontinuities across all oceans of the world (RADseq FST = 0.08–0.16). The results of this study provide unprecedented resolution of the systematics and global biogeography of this group and contribute valuable information to our understanding of how theoretical dispersal potential relates to actual population differentiation and diversification among marine organisms. Moreover, these results demonstrate the limitations of single gene analyses and the value of genomic‐level resolution for estimating contemporary population structure in organisms with large, highly connected populations.Population differentiation and diversification depend in large part on the ability and propensity of organisms to successfully disperse. However, our understanding of these processes in organisms with high dispersal ability is biased by the limited genetic resolution offered by traditional genotypic markers. Many neustonic animals disperse not only as pelagic larvae, but also as juveniles and adults while drifting or rafting at the surface of the open ocean. In theory, the heightened dispersal ability of these animals should limit opportunities for species diversification and population differentiation. To test these predictions, we used next‐generation sequencing of genomewide restriction‐site‐associated DNA tags (RADseq) and traditional mitochondrial DNA sequencing, to investigate the species‐level relationships and global population structure of  FST) of a species  plays a widely recognized role in the dispersal and connectivity of populations , Planes major , and Planes marinus   Chace, . While Ps Chace, . Recent l Chace, . Planes Planes, the ability to disperse as pelagic larvae and as adults associated with oceanic flotsam and sea turtles should facilitate transoceanic genetic exchange, limiting both species diversity within this group of crabs and intraspecific genetic differentiation among widely separated populations. To test this hypothesis, we conducted an analysis of the global species diversity and population‐level differentiation using next‐generation sequencing of genomewide restriction‐site‐associated DNA tags (RADseq) and traditional mitochondrial DNA (mtDNA) sequencing, to address three main questions. At the species level: (a) Is species diversity low with no evidence of cryptic species? At the population level: (b) Is population differentiation weak among widely separated aggregations? (c) If genetic discontinuities exist, where are there biogeographic corridors and barriers to rafting dispersal at a global scale?Traditional single gene analyses of intertidal grapsid crabs show weak genetic differentiation across wide latitudinal gradients, but limited evidence for transoceanic gene flow, indicating that large ocean basins represent significant barriers to pelagic larval dispersal  at 24 sites within all 13 ocean regions. Where applicable for each putative species, 1–5 individuals were obtained from each site. For Pl. minutus and Pl. major, larger samples  were collected when possible  evaluate statistical support for the relationship between Pa. laevimanus and Planes  quantify and compare the degree of intraspecific genetic variation in mtDNA between clades/species within Planes/Pa. laevimanus and other grapsid species. Mitochondrial sequences for Pa. laevimanus and Planes were generated specifically for this study, with additional mtDNA sequences from 168 specimens representing 19 other grapsid species provided by the Florida Museum of Natural History, University of Florida  DNAzol , (b) phenol–chloroform–isoamyl alcohol , or (c) Zymo Research Genomic DNA Microprep kits . For each method, extractions were performed according to the manufacturer's recommendations. For (b) and (c), extractions were performed following powderization in a Geno/Grinder 2010 .2.3cytochrome c oxidase subunit I (COI) gene was PCR amplified using degenerate universal metazoan primers (forward/reverse: dgLCO/dgHCO) following protocols described in Evans and Paulay , Pl. marinus (N = 11), Pl. minutus (N = 30), and Pl. major (N = 38) (Table π) was estimated in Arlequin v 3.5  and manually checked for ambiguous and erroneous base calls. Resulting high‐quality COI sequences for 8) Table . A maxim8) Table  using th2.4Genomic DNA quality was checked on agarose gels to ensure the majority of DNA fragments were of high molecular weight. Samples not meeting this criterion were excluded from RAD library development as degraded DNA has been shown to dramatically reduce the ability to recover comparable loci among individuals , a maximum distance for allele detection of two (‐M 2), and invoking the –r and –d options. In the cstacks module, a master catalog of all observed loci and allelic variants was compiled allowing an initial nucleotide mismatch of two between loci of different individuals (‐n 2). To improve computational efficiency and reduce the quantity of low frequency loci, the catalog was constructed using a subset of individuals (n = 35) representing all species and all populations. In the populations module, loci were filtered enforcing a minimum stack depth of three (‐m 3), minor allele frequency of 0.05 (‐a 0.05), and a minimum representation in 70% of individuals (‐r 0.7). Alternate parameter values were tested for each module and those used represent a compromise between dataset size, information content, and percentage of missing data  and RAD dataset 3 . While each of the three RAD datasets was assembled using the same parameter settings in each module of STACKS , the loci retained within each dataset were allowed to change to optimize analyses of population structuring at their respective scale .Because clustering programs can have difficulty identifying lower substructure in the presence of more dominant higher‐level organization , but AWCLUST is robust to small sample sizes within putative populations  and violations of demographic assumptions of Hardy–Weinberg and linkage equilibrium ; mean ± standard deviation) of each model and applying the deltaK method , observed and expected heterozygosity, and number of private alleles in the program Arlequin. Significant differences in FST values among clusters were determined by a 1,000 permutation test with Bonferroni corrections for multiple comparisons in Arlequin.For each RAD dataset, the genetic diversity within clusters and genetic differentiation between clusters detected in STRUCTURE and AWCLUST were estimated by calculating pairwise genetic distance (FST) were evaluated using a Bonferroni correction alpha value of 0.0009. To test for isolation by distance, Mantel tests implemented in GENALEX v. 6.5  resulted in consistently high bootstrap support (≥97%) for the monophyly of most species. However, COI data provide little to no resolution of relationships between genera or within species after collapsing nodes with weak bootstrap support (<60%) , which is consistent with the paraphyly of Planes due to the well‐supported inclusion of Pa. laevimanus as found by Schubart (Pa. laevimanus and Planes are available on GenBank (Accessions MH931286‐MH931370).A ML phylogenetic analysis of 253 COI sequences from 23 grapsid species  nested within a larger polytomy  and Pl. marinus (N = 10), but also seven Pl. minutus individuals from the Northeast Atlantic (NEA). Group 2 comprised mostly individuals of Pl. minutus (N = 23) and Pl. major (N = 38), but also one Pl. marinus individual from the Northwest Atlantic (NWA). The nucleotide diversity within each of these groups (π = 0.009) and within the entire Planes/Pa. laevimanus clade (π = 0.044) was similar to or less than that of other grapsid species (π = 0.0–0.074) at this mtDNA locus  and Pl. minutus from the NEA (N = 7) were identified as hybrids. Within Group 2, the single Pl. marinus from the NWA, a Pl. minutus in the NWA  and NEA  were identified as hybrids. An additional two hybrids from NEA were not sequenced for COI. Therefore, all individuals (N = 8) for which the morphological designation did not match mtDNA group were identified as hybrids. Excluding hybrids from the COI phylogeny , and then, based on the clustering and genetic analysis of this most inclusive dataset, two additional less inclusive datasets were constructed in order to evaluate further substructure. The putative hybrids were excluded in the two less inclusive datasets, which comprised Pa. laevimanus and Pl. marinus individuals  and Pl. minutus and Pl. major individuals . For the three RAD datasets, we recovered the following numbers of loci: RAD dataset 1 = 1,108 loci; RAD dataset 2 = 3,314 loci; and RAD dataset 3 = 1,288 loci. Most loci were unique to each dataset, while some loci were shared among datasets  between STRUCTURE and AWCLUST assignments  and most individuals segregated into two putative species clusters: One comprised of mostly Pa. laevimanus/Pl. marinus and another comprised of mostly Pl. minutus/Pl. major  and K = 4  corresponding primarily to different ocean basins and a priori species designations . Results from the phylogenetic analysis of RAD dataset 1 supported the overall patterns found in the clustering analyses at K = 2: two well‐support species groups (Pa. laevimanus/Pl. marinus and Pl. minutus/Pl. major) with a group of hybrid individuals with varying degrees of similarity between the two species groups  and Pl. marinus (N = 8), we found support for K = 2 and K = 3 in both STRUCTURE and AWCLUST  and Pacific Ocean (N = 5) clusters with some admixture. Results from the phylogenetic analysis of RAD dataset 2 support the overall patterns found in the clustering analyses at K = 3  and Pl. major (N = 77), we found support for K = 2 and K = 4 in STRUCTURE and AWCLUST , as well as the exclusion of erroneous clusters at higher values of K. Results from the phylogenetic analysis of RAD dataset 3 showed weakly supported geographic groupings, but no well‐supported nodes  between clusters identified in STRUCTURE and AWCLUST were highly significant . Table FST), and associated p‐values, observed and expected heterozygosity, and number of private alleles among clusters identified in RAD dataset 1  and a zone of hybridization between the two in the North Atlantic (FST = 0.244 and 0.400), as well as additional weak ocean‐specific differentiation within the Pl. minutus/Pl. major species group that was also consistent with a priori species designations (FST = 0.099).For each RAD dataset, all pairwise comparisons of genetic differentiation , and associated p‐values, observed and expected heterozygosity, and number of private alleles among clusters identified in RAD dataset 2 , which differentiate further by ocean basin .Table 2 Figure . CollectFST), and associated p‐values, observed and expected heterozygosity, and number of private alleles among clusters identified in RAD dataset 3  and Pl. major  that was comparable to differentiation within Pl. major . Results from the SNP‐based Neighbor‐Net support the overall patterns found in the clustering analyses at K = 4  among the regions designated in the AMOVA  among clusters identified in STRUCTURE and AWCLUST  or Pacific Ocean . Collectively, the results of RAD dataset 3 suggest that Pl. minutus and Pl. major are a single, globally distributed species that shows some geographic structure with weak genetic differentiation among widely separated aggregations.Additionally, for RAD dataset 3, an analysis of molecular variance (AMOVA) across 11 regions in three ocean basins showed that the majority of genetic variation was found among individuals within regions 87%) and that there was considerably more genetic variation between oceans (11%) than among regions within oceans (2%) Table . Pattern% and thaA Figure  were genT Figure ; Table 44Pa. laevimanus is sister to rafting Pl. marinus, (b) Pl. minutus and Pl. major comprise a single globally distributed species that is sister to Pa. laevimanus and Pl. marinus, and that hybridizes with Pl. marinus in the North Atlantic, and (c) Pl. minutus/major exhibit limited population structure at a global scale with weak genetic discontinuities associated with prominent oceanographic features. Our results show how life history changes that augment dispersal potential  can limit, but not prevent, species diversification and population differentiation, and highlight the value of genomic data in resolving phylogeographic patterns in organisms with large, highly connected populations.A major challenge in phylogeography is predicting the role that dispersal mode plays in shaping population structure and ultimately species diversification Palumbi, , 2003 . 4.1Planes is paraphyletic due to its well‐supported relationship with Pa. laevimanus  and rounder carapace and natatory fringes in Pl. marinus (similar to other Planes species). However, this current dataset is small and lacks geographic overlap between the two species—no Pl. marinus specimens from the southwest Pacific were included. The possibility that Pa. laevimanus and Pl. marinus are habitat‐specific variants of the same species cannot be ruled out. A more complete sampling regime would allow us to generate more resolved patterns and identify specific adaptive changes in larval recruitment, morphology, and reproductive and social behavior associated with changes in adult habitat and ultimately speciation.Our RADseq analyses indicate that intertidal Pl. minutus and Pl. major. The highly subtle and overlapping morphological traits that were used to separate Pl. minutus (only North Atlantic) and Pl. major  may simply be related to geographic variation in body size and concomitant allometric changes in traits related to limb length  have subsequently speciated following their colonization of the open ocean, although species diversity has remained fairly low  tend to show extensive cryptic diversity and high rates of endemism , the mechanisms leading to speciation in the open ocean are far more complex and might also involve behavioral changes associated with selection of different temperature and salinity profiles in the pelagic environment  and the Cape of Good Hope (Atlantic–Indian disjunction)  can provide valuable phylogeographic inferences when there is sufficient genetic resolution to elucidate population‐level differences, which is often the case for organisms that have low connectivity among populations. Because these markers were the primary tool available in the past and estimating population structure is more clear‐cut when populations are distinct, the literature is somewhat biased toward positive examples (Benestan et al., None declared.JBP, ACP, ABB, and KAB designed the study. JBP, ACP, and SFM performed the research. All authors wrote the paper. Click here for additional data file.