Mobula alfredi) are globally distributed in tropical and subtropical seas. Their life history traits  make them vulnerable to perturbations and therefore require informed management strategies. Previous studies have reported wide-spread genetic connectivity along continental shelves suggesting high gene flow along continuous habitats spanning hundreds of kilometers. However, in the Hawaiian Islands, tagging and photo-identification evidence suggest island populations are isolated despite proximity, a hypothesis that has not yet been evaluated with genetic data.Reef manta rays  on Hawaiʻi Island and Maui Nui . Strong divergence in the mitogenome (ΦST = 0.488) relative to nuclear genome-wide SNPs , and clustering of mitochondrial haplotypes among islands provides robust evidence that female reef manta rays are strongly philopatric and do not migrate between these two island groups. Combined with restricted male-mediated migration, equivalent to a single male moving between islands every 2.2 generations (~ 64 years), we provide evidence these populations are significantly demographically isolated. Estimates of contemporary effective population size (Ne) are 104 (95% CI: 99–110) in Hawaiʻi Island and 129 (95% CI: 122–136) in Maui Nui.This island-resident hypothesis was tested by analyzing whole mitogenome haplotypes and 2048 nuclear single nucleotide polymorphisms (SNPs) between Concordant with evidence from photo identification and tagging studies, these genetic results indicate reef manta rays in Hawaiʻi have small, genetically-isolated resident island populations. We hypothesize that due to the Island Mass Effect, large islands provide sufficient resources to support resident populations, thereby making crossing deep channels separating island groups unnecessary. Small effective population size, low genetic diversity, and k-selected life history traits make these isolated populations vulnerable to region-specific anthropogenic threats, which include entanglement, boat strikes, and habitat degradation. The long-term persistence of reef manta rays in the Hawaiian Islands will require island-specific management strategies.The online version contains supplementary material available at 10.1186/s12862-023-02130-0. Mobula alfredi) are planktivorous elasmobranchs that inhabit tropical and subtropical oceans between north and south latitudes of about 35 degrees [Reef manta rays  and their relationship in the family Mobulidae [In the past decade, genetic studies have revealed phylogenetic and geographic partitioning both among and within species of manta rays. Phylogenetic studies have provided robust support for the species level discrimination of obulidae –32. For obulidae , 33–35. obulidae  or alongobulidae . HoweverIn Hawaiʻi, reef manta rays occur throughout the archipelago , but areNe) to gauge population size and resilience. Overall, this study aims to provide insight into genetic stock structure and demographic parameters that can be used to inform management of reef manta rays in Hawaiʻi.Here, we test the hypothesis suggested by Deakos et al.  that eacMitogenomes were successfully assembled and haplotyped in 34 individuals, with an average sequencing coverage of 82.6x  Fig.  and highπ = 0.00017), number of haplotypes (H = 11) and average number of nucleotide differences (K = 3.02) compared to Hawaiʻi Island . The control region was the most diverse single region with four variable sites, and the remaining five variable sites were spread among four genes: NADH5 (2), NADH4 (1), 16S ribosomal (1), and cytochrome b (1) , which suggests a recent population expansion among the Maui Nui population. This result combined with the pattern that all unique variable sites were restricted to the Maui Nui population provides evidence that Hawaiʻi Island is an ancestral population, which has since expanded northward to Maui Nui. Among island populations, we found the mean number of nucleotide differences (Kxy = 4.44), mean number of nucleotide substitutions per site (Dxy = 0.00024), mean number of net substitutions per site (Da = 0.00013), and nucleotide divergence (K = 0.00024).Neutrality tests calculated from the mitogenome were not significant Table , except ΦST = 0.488, P < 0.0001, Table ΦST = 0.544–0.731, P < 0.001) for 4 of 5 genes including 16S, NADH4, cytochrome b, and the control region . This degree of differentiation suggests the existence of strong barriers to gene flow between Maui Nui and Hawaiʻi Island populations. Furthermore, the presence of a Hawaiʻi Island haplotype from a single individual in Maui Nui  of 0.023 (95% CI: 0.011–0.043) and 0.021 (95% CI: 0.008–0.047) moving northwesterly from Hawaiʻi Island to Maui Nui and southeasterly from Maui Nui to Hawaiʻi Island, respectively  to be equivalent to 1 female migrant moving between these island groups every 45 generations, or approximately 1305 years, based on the estimated 29-year generation time [Coalescence-based migration estimates determined by MIGRATE-N showed an overall pattern of net migration from Hawaiʻi Island to Maui Nui Fig. . The mition time , 25, 28.Na = 2.022, Neff = 1.594; HO = 0.508) compared to Hawaiʻi Island . The same pattern was true and more pronounced for the outlier loci with Maui Nui  presenting higher diversity indices than Hawaiʻi Island . Inbreeding coefficients revealed that the influence of inbreeding is negligible across all populations for both neutral and oultier loci datasets  was significant but notably weaker relative to the mitochondrial genome (ΦST = 0.488). The STRUCTURE analysis based on outlier loci recovered segregating populations between island groups , which coincided well with the DAPC analyses , differentiation at outlier loci was more than 60x higher , and showed a clear pattern of clustering among islands, yet with still some degree of admixture , three had blast hits to known sequences but were unmapped, and the remaining four were mapped and annotated with gene ontology terms Table . SequencNeM = 0.45 (95% CI: 0.06–0.88) compared to NeM = 0.44 (95% CI: 0.18–0.87) in the southeasterly direction. The magnitude of migration varied across nuclear datasets, however the overall pattern of net migration from Hawaiʻi Island to Maui Nui was concordant across all datasets  equivalent to 1 effective migrant moving between these island groups every 2.2 generations, or approximately every 64 years, based on the estimated 29-year generation time. Migration estimates were 20 times greater for nuclear loci than the mitogenome. The patterns of net migration in both the nuclear and mitogenome, coupled with the results of the haplotype network, which revealed the presence of Hawaiʻi Island haplotypes in Maui Nui (but not the inverse), supports a Hawaiʻi Island to Maui Nui net direction of migration.Coalescence-based migration estimates determined by MIGRATE-N varied among datasets but showed an overall pattern of net migration from Hawaiʻi Island to Maui Nui Table ; Fig. 3.Ne) based on neutral nuclear loci resulted in Ne(raw) estimates of 104 (95% CI: 99–110) for Hawaiʻi Island and Ne(raw) = 129 (95% CI: 122–136) for Maui Nui populations. Ne(adj) estimates were found to be slightly less conservative with Hawaiʻi Island and Maui Nui, estimated to be 122 (95% CI: 110–127) and 155 (95% CI: 141–157), respectively.Estimates of contemporary genetic effective population size  in the Hawaiian Islands using a combination of genome-wide nuclear loci and whole mitogenome sequences. Our assessment of genetic connectivity revealed that patterns of gene flow are associated with the geographic separation of island groups, with significant differentiation observed in the mitochondrial genome  as well as neutral  and outlier loci  across the nuclear genome  relative to the biparentally-inherited nuclear genome (FST = 0.003) is robust evidence that female reef manta rays are strongly reproductively philopatric. This signal of differentiation and geographic clustering of mitochondrial haplotypes  demonstrated that reef manta rays readily moved between the islands of Maui Nui but did not migrate to Hawaiʻi Island (and vice-versa). Therefore, photo-identification and tagging studies all provide no evidence of animal movements between Maui Nui and Hawaiʻi Island [The genetic patterns presented here are in concordance with evidence from photo-identification and tagging studies and thus confirm that Maui Nui and Hawaiʻi Island reef manta ray populations are distinct population stocks with restricted movement between them. First, no photo-identification matches have been made between catalogs on Hawaiʻi Island, which to date contains 318 unique individuals 1979–2023; ), and wi79–2023; i Island .Availability of resources may be driving this limited movement of reef manta rays between islands. Reef manta rays forage for zooplankton in generally nutrient-poor oligotrophic waters in tropical and subtropical oceans. To meet energetic needs of this large planktivore, reef manta rays require high densities of planktonic prey . IslandsAt small scales, reef manta ray feeding events coincide with localized high biomass of zooplankton driven by fine-scale oceanographic processes, such as strong tidal currents interacting with island topography , 63, colCollectively, these fine-scale and meso-scale oceanographic features, all enhanced by the Island Mass Effect, provide more biomass and greater predictability of planktonic prey near large islands . ReliablWithin the Hawaiian Archipelago, similar patterns of population and genetic breaks between Hawaiʻi Island and Maui Nui have been observed in several wide-ranging insular species including common bottlenose dolphins , 70, spiWe reject the alternative hypothesis that the lack of exchange between island groups results from isolation by distance. The shortest distance between Maui Nui and Hawaiʻi Island is only 49 km, and linear movements up to 91 km have been documented elsewhere in Hawaiʻi  and moreunpublished). Hawaiʻi Island and the Maui Nui island complex are large, high volcanic islands separated by the ʻAlenuihāhā channel, which has a minimum crossing depth of 1900 m, and plummets to depths > 4700 m on both eastern and western sides , which shows relative panmixia across their circumtropical distribution [Perhaps not surprisingly, the pattern of regional genetic structure observed in reef manta rays is in direct contrast to genetic patterns in the oceanic manta ray  are 104 for Hawaiʻi Island and 129 for Maui Nui. When sampled from a mixed-age group and overlapping generations, as in this study, Ne is an approximate estimate of the harmonic mean of the number of breeders (Nb) in the population over several generations [Ne and the minimum estimates for census size (Nc) across taxa [Ne estimates published to date [Ne estimated at 89 and a catalog size of 305 unique individuals [Ne estimated at 375 [Nc), the Ne/Nc ratios in these four populations are similarly between ~ 0.2–0.3 , howeveoss taxa , 91, our to date , 92. Thed at 375  and a cad at 375 , 93. Usi.3 Table , suggestNe/Nc ratios observed in reef manta rays are consistent with species with Type I survivorship curves, which well characterize manta rays and other viviparous elasmobranchs [Ne/Nc among taxa is driven primarily by age-at-maturity, adult lifespan, and variation in reproductive success [The relatively high obranchs . Several success –96. Reef success , 25, and success , 92.Ne. Precision and accuracy of Ne estimates derived from low numbers of samples (and loci) can decline resulting in infinite parameters or upper confidence limits [Ne for small population sizes [Ne confidence limits we report are finite and relatively narrow for both Hawai’i Island  and Maui Nui  populations, suggesting these data have sufficient power and precision for estimating Ne. Additionally, our relative number of samples to Ne estimates (13–15% of Ne) are above the 10% of Ne guideline proposed by Palstra & Ruzzante [We acknowledge that the relatively small sample sizes used in this study may reduce precision in our estimates of contemporary e limits . Howeveron sizes . FurtherRuzzante , 101. EfMost regions support relatively small populations of reef manta rays, typically less than 1,000 individuals. Long-term photo-identification studies have produced minimum estimates  as low as 54 animals in Yap, Micronesia  and up tGlyphis glyphis) revealed strikingly similar patterns of genetic variation  to thosobranchs , 108. Alobranchs . With coFs = -4.44. P < 0.01), however, other neutrality tests  did not show support of a bottleneck or recent expansion, suggesting these Hawaiian populations have not fluctuated dramatically in size. Thus, small population sizes and low genetic diversity may be the natural biological state for this species at least in this region.The concern regarding the consequences for populations with low genetic diversity is compounded when population sizes are small, as in reef manta rays. When low genetic diversity is observed in a population, it is often interpreted as an indication of inbreeding depression  and is tCombined with evidence from photo-identification and tagging studies, these genetic results indicate reef manta rays in the Hawaiian Islands have small resident island populations that are significantly genetically isolated and should be managed as discrete stocks. The lack of female migration among islands means extremely little potential for replacement females to enter and establish from other islands. The relatively low levels of male-mediated migration still indicate that replacement males cannot be counted on to replenish island populations should they decline. On the ocean basin scale, evidence of genetic differentiation between Hawai’i and the South Pacific and Indian Oceans  providesunpublished). Whether this is due to a reduction in population size or manta rays relocating elsewhere due to degradation of reef habitat remains unknown and requires further investigation. In addition, more than 10% of the Maui Nui population has evidence of entanglement in fishing line, primarily from shore-casting fishing gear used to target giant trevally (Caranx ignobilis) [Globally, several reef manta ray populations have been reported to be in decline  and has nobilis) . Injury Monitoring long-term population trends and breeding stock will be important for evaluating the population level impacts of local anthropogenic threats, which include fishing line entanglement , 20, polNe [Further research to assist with effective management strategies should include the following. First, identifying essential habitat areas that are used for cleaning, feeding, mating, and pupping  could beNe , and assLong-term stability of aggregation sites is beneficial for the stability of social structure, particularly mating behavior. In addition to benefits of cleaning, coral reef cleaning stations also serve as hubs for reproductive activity , 23, 25.We provide evidence of strong female reproductive philopatry and weak male-mediated dispersal that indicate genetic isolation of small resident island populations of reef manta rays in Hawaiʻi. Despite the proximity of these island-associating populations, they represent two genetically distinct stocks with varying geographic characteristics. The Hawaiʻi Island population demonstrates a much tighter home range but has immediate access to deep-waters whereas the Maui Nui population shares a relatively shallow bathymetry between the 4-island Maui Nui complex. The threats affecting Maui Nui’s population may be more dependent on entanglement in coastal fishing line and habitat degradation, whereas the Hawaiʻi Island population face a different set of challenges from direct interaction with boats and divers. These distinct differences between neighboring island populations, combined with their reproductive isolation and vulnerable life history characteristics, highlight the importance of local, island-specific management strategies.Most data were collected opportunistically while freediving or with open-circuit SCUBA, either from a boat or from a shoreline entry at known manta ray aggregation areas Table ; Fig. 1.Surveys on Maui took place during the daytime, and primarily focused on a known manta ray cleaning station located at the south end of the Olowalu Reef  and within a kilometer of the West Maui shoreline .Mobula alfredi. We recovered 9,872 to 16,825,862 reads  per individual library (Table Whole genomic DNA was extracted from each sample using an Omega E-Z 96 Tissue DNA Kit (Omega), following the manufacturer’s protocol. DNA extracts were quantified using the AccuBlue High-Sensitivity dsDNA kit  on a Spectramax M3 fluorescent plate reader  and visualized using gel electrophoresis. Samples were normalized (to 40ul) and 1-3ug of DNA per sample were digested overnight with DpnII restriction enzyme (NEB). We used the ezRAD approach  to constry Table .M. alfredi mitogenome (including the control region) from individual M03 from Maui  were aligned to this reference mitogenome using BWA v.0.7.17 [Due to the high prevalence of the GATC cut site in mitochondrial genomes combined with stochastic fragmentation, whole mitogenomes can be assembled from ezRAD libraries , 125. Wev.0.7.17 , Samtoolv.0.7.17 , and Bamv.0.7.17 . Freebayv.0.7.17  was usedv.0.7.17  and maskD [Fs [ΦST) among islands, using a Tamura-Nei model of nucleotide evolution  and the control region. A haplotype network was constructed for the mitogenome with network v.4.6.1.1 [We calculated molecular diversity indices using DnaSP v.6.12.01 . We impuD  and Fu’sD [Fs  were perD [Fs  to inferelTest 2 ). Using .4.6.1.1  using a .4.6.1.1  and defaOur nuclear SNP discovery and genotyping workflow included five major steps: (1) quality filtering , (2) de-novo pseudo-reference generation, (3) alignment to pseudo-reference RAD contigs, (4) variant calling, and (5) SNP quality control filtering. For quality filtering, raw reads were assessed using FastQC  and readMobula alfredi was generated de novo using Seanome [M. alfredi mitogenome (GenBank Accession: OP562409). Five contigs matched well to the mitogenome reference (98–100% identity), all with Scores > 400, very low E-values (1e-150) and overlapping lengths between 271 and 337 bases. We checked if any of these five contigs matched with the final post-filtering SNP set contigs (2048 SNPs on 459 contigs) and none were present. Therefore, this confirms the final SNP set contains only nuclear loci, with no hits to the mitogenome reference > 100 bases and an e-score > 1e-20.A pseudo-reference of ezRAD loci for  Seanome . In shor Seanome  using de Seanome  to remov Seanome  to excluThe dDocent pipeline  was usedP < 0.01 in both populations). This included the removal of SNPs with: low quality-to-depth ratios (< 0.25), discrepancies between mapping qualities and properly paired status of reference and alternate alleles, mean read depth < 20 and > 120x; and the removal of RAD loci (contigs) with excess SNPs (> 24) and those identified as possible paralogs. The final nuclear SNP set contained 2048 SNPs across 459 RAD loci (mean 4.5 SNPs per RAD locus) with 38 individuals  based on the dDocent protocol  and follls Table  containiFST for loci unlikely to be under strong positive selection. We ran OutFLANK implementing a left and right trim factor of 0.05, a minimum heterozygosity of < 10%, and a false discovery rate of 5% (q = 0.05). The contigs (RAD loci) containing outlier SNPs identified using OutFLANK were used as queries  against the nr database at the National Center for Biotechnology Information (NCBI), using Blast2GO Pro [− 6, annotation cut-off > 55 and a GO weight > 5).We assessed population structure using three nuclear SNP datasets: all loci (2048), neutral loci (2038), and outlier loci (10), which allowed us to make inferences regarding selection. To identify neutral and outlier loci we used the R package OutFLANK , 153, wht2GO Pro  to find FST statistics were generated to assess genetic structure between locations. False discovery rates were controlled for and maintained at α = 0.05 among all pairwise tests [Ne, and the parametric 95% confidence levels.Genodive was used to generate genetic diversity indices for all three datasets, as well as to test for population structure. Genetic structure among sample locations was evaluated with an analysis of molecular variance (AMOVA) in arlequin. Deviations from null distributions were tested with non-parametric permutation procedures (N = 9999). Pairwise se tests , 156. Gese tests , a Bayesse tests  and selese tests . Structuse tests , which ise tests  and minise tests . We impose tests . Contempse tests  as implese tests . Here, wse tests  and repoθ  and M . In the final analyses the mean prior values for θ and for M were set in both directions . After checking for data convergence, the mode and 95% percentiles of θ and M were used to calculate the effective number of migrants per generation (Me) between populations to determine the direction and magnitude of migration. A relative migration network was constructed in R using the divMigrate function in the diveRsity package [D [Me) to calculate the number of generations needed to achieve 1 effective migrant between populations, then multiplied by the estimated generation time for M. alfredi Below is the link to the electronic supplementary material.Additional file 1 Supplementary figures Additional file 2 Supplementary tables S1-S6.Additional file 3 (1) Step-by-step protocol for library prep benchwork and (2) Detailed steps of SNP filtering workflowAdditional file 4 Mitogenome Assembly & Alignment Summary Tables


Macrocarpaea (Gentianaceae) in the tropical Andes. These woody herbs, shrubs or small trees show complex and potentially reticulated relationships, including cryptic species. We show that populations of M. xerantifulva in the dry system of the Rio Marañón in northern Peru have lower levels of genetic diversity compared to other sampled species. We suggest that this is due to a recent demographic bottleneck resulting from the contraction of the montane wet forests into refugia because of the expansion of the dry system into the valley during the glacial cycles of the PCO. This may imply that the ecosystems of different valleys of the Andes might have responded differently to the PCO.The Pleistocene climatic oscillations (PCO) that provoked several cycles of glacial–interglacial periods are thought to have profoundly affected species distribution, richness and diversity around the world. While the effect of the PCO on population dynamics at temperate latitudes is well known, considerable questions remain about its impact on the biodiversity of neotropical mountains. Here, we use amplified fragment length polymorphism molecular markers (AFLPs) to investigate the phylogeography and genetic structure of 13 plant species belonging to the gentian genus  Mountain ranges are often considered as speciation centers that significantly contribute to enhancing species diversity on Earth ,2. They Climate change has also been proposed as a potentially important driver of speciation in montane regions, particularly in non-vagile organisms such as plants ,12. It iAmong neotropical mountains, the tropical Andes are of particular interest because they have exceptional levels of diversity and endemism . It has Palynological evidence has shown that the Amazon-facing slopes of the eastern Andean cordilleras remained fairly wet during the glacial periods of the PCO ,27. HoweMacrocarpaea (Gentianaceae). The genus is restricted to the mountains of the Neotropics  [Macrocarpaea species as monophyletic [M. xerantifulva and M. claireae since previously conflicting results were obtained by different approaches, with one of them contradicting the morphological and other traits  [Macrocarpaea claireae J. R. Grant is an unbranched shrub or small tree 1.5–2.0 m tall, with a 2 cm diam. trunk; wood hollow in trunk and in branches; stems terete to quadrangular, 6–8 mm diam.; leaves oval, elliptic to ovate, and petiolate. It is found around Valladolid in Zamora-Chinchipe province in southern Ecuador [M. xerantifulva J. R. Grant is found in Cajamarca and Piura provinces in northern Peru. It has similar characteristics to M. claireae but is notable in herbarium specimens in having stems that dry yellowish gold in color (vs. green), and calyces that dry brownish (vs. drying black) [Here, we used amplified fragment length polymorphism genetic markers (AFLPs) to examine the phylogeography and population genetics of plant species belonging to the genus nforest) . Currentnforest) ,40,41,42nforest) . Previouphyletic ,44,45. T clades) ,45. Macr Ecuador . M. xerag black) ,31.vs. vegetative spread, individual lifespan and climatic fit of the species. Here, we specifically focus on the impact of the PCO because, in previous studies [Similarly, despite other processes such as the impact of interspecific interactions, the genetic background of the above-mentioned species may be influenced by species dispersal distance, sexual reproduction  studies ,45, the M. claireae and M. xerantifulva is lower than in the other species, as expected if the “refugia model” was more plausible and the internal Andean valleys were dryer during the PCO, or not ; and (3) detect potential genetic (distance-based) variability among the previously morphologically determined lineages as a basis and indication for further studies.Here, we (1) explore and compare the spatial genetic structure of these species with the use of the AFLP technique; (2) test whether the genetic diversity of populations of the closely related K statistic of the STRUCTURE analyses performed on all the genotypes of all specimens sampled in the study supported an optimal value of K = 2 (M. claireae and M. xerantifulva and cluster B (white) being composed of the populations of all remaining species . Levels of admixture between these two clusters were generally very low ) increased steadily after K = 2 before reaching a plateau at K = 8. This discrepancy between the two statistics indicates that the ∆K statistic identified the highest level of hierarchical structure in our dataset but that additional layers of the genetic structure are likely present inside the clusters.The ∆of K = 2 . Here, wvery low I. ContraK and mean L(K) favored K = 4  is found as dominant among the central and southern populations. In between, cluster A2 (yellow) is often found in central populations, showing mixed genetic information with A1 and A3. Its prevalence tends to decrease toward the south and it is absent from the two northernmost populations (A1). The populations with the highest prevalence of A2 are M. xerantifulva 19 and M. xerantifulva 2 but both are formed by only two individuals. Finally, the A4 (violet) cluster is relatively rare but is present along the entire geographic distribution. The only population where all individuals show this characteristic is M. xerantifulva 9. Overall, the level of admixture in individuals is low, except in Peruvian populations close to the border with Ecuador . Inside cluster B, the ∆K statistic favored K = 3 while the mean L(K) only reached a plateau for K = 6 . The cluster B1 (green) regroups populations from eight different species and covers a very large geographic distribution  than in those of cluster A  and the difference in means between the two clusters is highly significant (T(34.5) = 7.076, p < 0.001). The results of the hierarchical AMOVAs performed either by grouping populations by species or by their prevailing assignment with Bayesian clustering (F statistics tested with permutations were highly significant (SC statistics (variation among sub-groups divided by the sum of variation among sub-groups and variation within sub-groups) are significant indicates that populations inside the groups are still appreciably differentiated.Gene diversity Hj, see  is almosustering  revealednificant . The facM. xerantifulva 9, which is the only population predominantly assigned to the sub-cluster A4, is well supported as being well differentiated within the cluster. Then, inside cluster A, populations do not group according to their STRUCTURE assignment. Similarly, internodes are short and bootstrap support is low, indicating potentially little divergence among populations. Inside cluster B, the bootstrap support is in general higher and the internodes are much longer than in cluster A, very likely indicating a larger divergence between populations inside cluster B. The only sub-cluster identified by STRUCTURE that is strongly supported as monophyletic is cluster B3. M. dies-viridis (893/1000), M. illuminata (845/1000) and M. quizhpei are strongly supported as monophyletic (920/1000).The NJ dendrogram computed from Nei’s genetic distance  displaysijF), measured for cluster A  and cluster B . The two clusters have relatively similar Sp statistics with Sp = 0.0158 and Sp = 0.0172 for cluster A and cluster B, respectively. Finally, it should be noted that the intra-individual kinship (F(0)), which corresponds to the FIT when individuals from different populations are compared [F(0) = 0.22) than for the cluster A (F(0) = 0.13). This indicates that the sum of inbreeding inside the populations and the overall differentiation between populations is higher in group B. As gene diversity is higher in the populations of cluster B : M. claireae, M. cortinae, M. dies-viridis, M. illuminata, M. lenae, M. pacifica, M. pringleana, M. quechua, M. quizhpei, M. sodiroana, M. sp. nov., M. umbellata, and M. xerantifulva. We performed STRUCTURE and NJ analyses to examine the genetic structure of the populations and to shed light on the effect of the PCO on the biodiversity of neotropical mountains.Here, we analyzed a dataset of 203 loci of AFLP markers from 345 individuals of 13 closely related plant species belonging to the genus M. pacifica that occurs on the Pacific-facing slopes of the western cordillera in southern Ecuador and the unique populations of M. sodiroana and M. umbellata that occur on the Pacific facing slopes of the western cordillera in northern Ecuador. Cluster A comprises the two populations of M. claireae in southern Ecuador and the 18 sampled populations of M. xerantifulva from the Rio Chinchipe valley in Peru. The low bootstrap of populations detected is probably a result of the fact that most of the populations belong to the same species and have very small samples.The unrooted NJ dendrogram constructed from matrices of genetic distances between populations and the Bayesian clustering analyses performed at the individual level (STRUCTURE) identified the same basal dichotomy in the genetic structure of the group of species we studied. Cluster B is formed by species with populations occurring on the Amazon-facing slopes of the eastern cordilleras from northern Ecuador to northern Peru, plus the unique population of Ceroxylon echinulatum Galeano (Arecaceae) for the colonization of the eastern and western cordilleras of the Andes followed by subsequent migration toward the north during the Quaternary [Macrocarpaea species from different clades were collected at a higher elevation. Visits further south, on the other side of the Rio Marañón, were also unfruitful.Interestingly, one of the rare studies that addressed the phylogeography of a montane plant group from the same region identified the Rio Chinchipe valley as a source population of aternary . Here, iMacrocarpaea species complex. Notably, neither the genetic distance-based dendrogram nor the Bayesian clustering analyses support the species boundary defined based on morphological data and field observations for M. claireae and M. xerantifulva. Macrocarpaea claireae in cluster A is relatively deeply nested in the middle of the populations of M. xerantifulva on the dendrogram. The Bayesian clustering analyses reveal that M. claireae 1 and the northernmost population of M. claireae 2, which were sampled a few kilometers apart from one another (<3 km), are members of the same genetic cluster (cluster A1). The fact that individuals belonging to cluster A1 are also found mixed with other genetic clusters in other populations close to the border between Ecuador and Peru indicates that M. claireae and M. xerantifulva may be the same species that displays a geographic genetic structure. The relatively low branch length at the internodes for clade A on the dendrogram also suggests relatively low genetic differentiation between populations inside the cluster, which support the hypothesis of the presence of a single species inside cluster A. However, as the samples of the populations of cluster A are very small, the structure detected within this cluster is probably not sufficiently strong from a statistical point of view and the species boundaries need to be tested with more solid approaches. Thus, future studies should revisit the taxonomic status of M. claireae and M. xerantifulva.Several elements from our results raise important questions regarding the definition of the species boundaries inside this K statistics [K); K = 6 and thus indicates the potential presence of additional levels of genetic structure. The comparison of the partitioning of the genetic variance  in comparison to the populations from cluster B (mean jH = 0.150). Compared with estimates in the literature for other perennial and predominantly outcrossing plants [M. xerantifulva. The very low levels of gene diversity found in M. xerantifulva indicate that this species very likely went through a demographic bottleneck, which fits the prediction of the dry refugia model [M. xerantifulva re-colonized the valley only recently. An alternative hypothesis to explain the low genetic diversity in M. xerantifulva could be that it has recently been founded by a small number of individuals  which limits its significance. Another approach to identifying refugia could consist of assessing the diversity of genetic clusters inside populations (genotype diversity). Using this approach, M. xerantifulva 18, which is in northern Peru in the proximity to the border with Ecuador, and M. xerantifulva 18, which is located about 20 km further south, are the best candidates. Considering that if an intensification of drought occurred in the Rio Chinchipe valley, it should have been more severe in the south, the position of refugia in that part of the valley is not illogical. Nevertheless, this pattern of genotype richness cannot be taken as the ultimate evidence for the position of refugia. Secondary contact zones can also generate a hotspot of genotype diversity (genetic cline) and both scenarios are relatively difficult to set apart [We found a significant deficit of about 40% in gene diversity in the populations of ia model . This, ir event; ). This hme 2 Myr . Accordiet apart .M. xerantifulva and genetic cluster B. Both groups show significantly high kinship over a relatively long distance (6–30 km) and thus have a relatively weak SGS. The regression slopes of the relationship between pairwise kinships and pairwise logarithms of distances (bF) were significantly more negative than expected by chance, which indicates a significant effect of isolation by distance. However, this last assertion should be taken with caution as the maximal distances we considered were very large in comparison with other studies (124 km for M. xerantifulva and 847 km for cluster B). Therefore, it is not surprising to detect an effect of isolation by distance at such a large spatial scale. In addition, despite their similarity, the SGS estimates for cluster B are likely to be meaningless as this group is potentially composed of several species while SGS is usually estimated at the intraspecific level [M. xerantifulva. The significantly high kinship we found at a relatively large distance in M. xerantifulva suggests that the populations of this species are relatively well connected genetically. Macrocarpaea species are usually predominantly pollinated by nectar-feeding bats [Sp statistic for M. xerantifulva (Sp = 0.0158) is extremely similar to the rare estimate that exists in the literature for bat-pollinated plant species [Analyses of the spatial genetic structure (SGS) revealed a strikingly similar pattern of SGS between ic level . Consequing bats ,54 whiching bats . It is t species ,57.M. claireae 2), while some were more distant from each other both horizontally and vertically , which is the case of, e.g., M. claireae 1 where the samples were found at altitudes in the range of 100 m. These discrepancies, sometimes caused by the biology of the respective species and sometimes by the conditions at the locality, might have also affected the observed genetic diversity within and between populations.We recognize that our study and the interpretation of the results have limitations and that there may be alternative explanations to our observations and conclusions. One of the limitations is the uneven sampling due to the extremely difficult accessibility and possibilities of finding of the populations and sample size. For example, some of the populations in cluster A, compared to cluster B, include only a few representatives, which might have biased the result showing low genetic variance, i.e., a low genetic difference observed among few samples may be low by chance and would be different if more individuals were sampled. However, the mean sampling size per population in cluster A is 8.5 samples/population and in cluster B it is 10.3. This difference is not substantial. Moreover, in the cases where only a few individuals were sampled, the populations were also small, i.e., all or the majority of the detected individuals at the given locality were sampled. Such small populations usually indicate that the genetic variability would be low due to the effects of limited gene flow and inbreeding ,59. In aMacrocarpaea [M. claireae analyzed previously was missing plastid data which might have affected the analyses, as for other data both plastid and ribosomal markers were used, see Appendix S1 in [M. claireae was sister to M. quizhpei, while in Appendix S3, it was sister to M. xerantifulva. Conflicts between plastid, mitochondrial, ribosomal and nuclear data are commonly reported; also, AFLP data are not particularly convenient for phylogenetic reconstruction. The figure presented here is a dendrogram, not a phylogenetic tree; however, the results presented here support the sister relationship of M. claireae and M. xerantifulva, which also corresponds to their morphology and other biological traits. As previously mentioned, more extensive sampling and application of different methods are needed for more precise phylogenetic conclusions.The results shown in the dendrogram in this study are different to those found in previous molecular studies on ocarpaea ,45. ThesMacrocarpaea species were collected between 2011 and 2013 at 37 localities in nine regions of Ecuador and Peru  occur on Pacific-facing slopes of the Andes, while the other ten occur on Amazon-facing slopes of the eastern cordilleras in the Amotape-Huancabamba (AHZ) zone in southern Ecuador and northern Peru  in northern Peru between the Cordillera Real in the west and the Cordillera del Condor in the east, in the Rio Chinchipe valley -chloroform extraction followed by isopropanol precipitation and ethanol washing . The DNAEcoRI and MseI enzymes  were used for digestion. All cycles of digestion-ligation were performed on the same thermocycler machine . After a preliminary test on 24 selective primers combinations, three were retained based on their levels of polymorphism and reproducibility: M-CGA/E-AGC, M-CCA/E-ACA and M-CCG/E-ATC, labelled with the fluorescent dyes FAM, VIC and NED , respectively. Amplified PCR products were pooled with GeneScan 500 LIZ Size Standard , sent to Macrogen Inc.  and separated on the ABI 3730XLs DNA Analyser . Fragment sizes were estimated with GeneMapper v4.0  using the AFLP default peak detection parameters. Marker bins were set manually for each primer combination and only fragments within the range of 50–500 bp with a peak height of a minimum of 50 relative fluorescent units (rfu) were considered for generating a marker (bin). Peak scoring on the bin sets was performed automatically by the software and resulting tables with peak heights and sizes were exported and processed with scanAFLP v. 1.3 [Amplified fragment length polymorphism markers (AFLPs) were generated for 345 individuals and 103 duplicates (29.7% of the dataset), following the protocol of Vos et al.  with theP v. 1.3  using thP v. 1.3 . This scP v. 1.3 , that weP v. 1.3 . Every lK was determined using the modal distribution of the ∆K statistic of Evanno et al. [K = 2), the dataset was subset according to the results of the individual assignments for K = 2 and analyses were repeated for each cluster independently. For the analysis of the complete dataset, K = 1–16 was used, while analyses on the subsets were performed for K = 1–12 and K = 1–8 based on the estimated number of populations. For each type of analysis and each K value, three replicate chains of 175,000 MCMC iterations were run and the first 25,000 iterations were discarded as a burn-in. STRUCTURE was used with the default settings except for the application of the recessive allele option and the admixture model with correlated allele frequencies. The average membership coefficients for the three simulation runs of a given K value were generated with CLUMPAK v. 1.1 [The hierarchical structure in the AFLP dataset was investigated using the Bayesian genotype clustering method adapted to dominant markers, implemented in the program STRUCTURE v. 2.3.4 ,66. The o et al.  with STRo et al. . In dataK v. 1.1 .jH) [st) using 1000 permutations. A thousand matrices of Nei’s unbiased genetic distances were computed by bootstrapping over AFLP loci in AFLPsurv and exported to PHYLIP software package v. 3.6 [Allele frequencies were estimated for each population from AFLP fragment frequencies with the Bayesian method of Zhivotovsky , implemeHj)  for eache v. 3.6  to builde v. 3.6 . PopulatM. xerantifulva and M. claireae  and with 11 distances classes for the cluster composed by the other species . These relatively large distance classes, compared with what is found in the literature, were selected to accommodate our sparse sampling design. While it does not allow us to determine the fine SGS, it will already indicate how genetic structure is influenced by distance. The significance of the average kinship coefficient in every distance class was tested using 1000 permutations of spatial locations and individuals, while standard errors were estimated by Jackknifing across loci. The permutation procedure also allowed testing of whether the regression slope of the kinship coefficient over the distance was significantly negative, as expected under a scenario of isolation by distance. Both the kinship coefficient and the regression slopes are affected by the sampling design and thus are not appropriate for comparison between species. To compare the strength of SGS between genetic clusters, the Sp statistic [Sp = −bF/(1 − F(1)), where bF is the slope of the regression of kinship against ln distance and F(1) is the average kinship of individuals in the first distance class (here 0–100 m). Because this statistic is calculated on the logarithm of the distance it is less affected by the sampling design and thus has the desirable advantage of being comparable across studies.To estimate the spatial genetic structure (SGS) in the main genetic clusters identified by STRUCTURE, the pairwise kinship coefficient was calculated with the software SPAGeDi v1.5.a . The esttatistic  was compMacrocarpaea species complex composed of several morphological cryptic species requires new consideration. However, the highly asymmetrical sampling in terms of the number of individuals and populations per species, as well as the relatively small AFLP dataset included in this study, does not allow unambiguous estimation regarding their genetic structure, phylogeny, evolution history and prevailing evolutionary processes. More extensive sampling with even representation of all populations and application of modern genetic methods (such as next-generation sequencing) and corresponding analyses more suitable for population genetics, evolutionary reconstructions and related questions are required for more precise conclusions. This is especially valid for the genetically complex cluster B that regroups the essential of the supposed taxonomic diversity in this species complex.We showed that the species delimitation in this young M. claireae and M. xerantifulva may form a single species that evolved in relative isolation from the rest of the species complex. Relying on denser sampling, we show that this species has relatively low gene diversity that could have resulted from a recent demographic bottleneck. We suggest that the intensification of drought induced by the PCO in the Rio Chinchipe valley might have compressed this species in refugia. While remaining highly speculative, this statement suggests that the different Andean valleys might have responded in a dramatically different way to the PCO. The easternmost valleys remain wet while the more internal ones, which are currently in contact with dry systems such as the Rio Marañón, suffer from drought. However, it would be highly desirable in the future, with the application of more modern methods and extensive sampling, to perform a reevaluation of the effect of the Pleistocene climatic oscillations compared to other potential evolutionary processes, as well as mountain geomorphology and climatic and potential other influential factors to confirm or correct our findings.Nevertheless, we were able to demonstrate that Macrocarpaea (Gentianaceae) occurring in the tropical Andes. We test which climatic scenario was the most plausible during the Pleistocene glacial periods and what impact the abiotic changes had on montane forest populations.The effect of the Pleistocene climatic oscillations on species evolution in the neotropical mountains is poorly known. Here, we used amplified fragment length polymorphism (AFLPs) genetic markers to analyze the phylogeography and population genetics of several lineages belonging to the plant genus


G. arabica) occurs only in small, scattered populations on the Arabian Peninsula and is classified as ‘vulnerable’, due to intensive hunting and competition with livestock. The taxonomy of this threatened species is still under debate, hampering conservation efforts while ex-situ breeding programs could be an appropriate conservation measure to prevent the species from going extinct. In our study, we attempted to elucidate the radiation of G. arabica on the Arabian Peninsula, and to ask whether the population genetic structure allows to distinguish between discrete conservation units. We used mitochondrial markers, microsatellite markers, and three intron markers to identify conservation units, to match them with genotypes found in the captive breeding stock held in Saudi Arabia, and to ensure that genotype diversity of potential founder individuals corresponds to that prevailing at targeted reintroduction sites. The sequence divergence was low among nuclear and mitochondrial markers, with gazelles originating from the north of the Arabian Peninsula showing the largest diversity, while south-western and eastern populations showed a decreased diversity. A haplotype network based on the relatively heterogeneous cytochrome b gene found no signs of a prolonged separate evolutionary history of any investigated mainland population, suggesting limitations of gene-flow after the colonization of the Arabian Peninsula leading to a founder effect-like distribution of mitochondrial haplotypes. The ex-situ breeding population held in Saudi Arabia showed a good haplotype diversity, underlining its general suitability for reintroductions. However, it is recommended that genetic data of founders should be assessed prior to future reintroduction.Today, the Arabian gazelle ( Most samples (N = 37) were obtained from captive individuals kept at KKWRC. Other samples were collected from wild animals in three geographic regions in which y occurs , i.e., tb gene, and primers published in DNA extraction was performed using the Qiagen DNeasy Blood & Tissue Kit and the Qiagen QIAamp DNA Stool Mini Kit following the instructions provided by the manufacturer. For the Polymerase chain reactions the primers KKWRC5 and KKWRC9  for the mitochondrial cytochrome 2.2(1)b alignment with a length of 391 base pairs of N = 88 G. arabica specimens, incorporating most available samples, especially those with known provenance, as well as N = 5 outgroup sequences , we calculated pairwise Kimura 2-Parameter p-distances (K2P) using MEGA 11 b to further evaluate possible differentiation between groups.For N = 42 specimens, population genetic data, inferred from a STRUCTURE analysis based on microsatellite length-polymorphism sequences, were available (for details see (3)b and the nuclear intron markers NLRP2, PANK4 and Smoc1 with a total length of 2032 base pairs. To make use of the best-fitting partitioning scheme and the respective nucleotide substitution models, we used the greedy search algorithm with PhyML , i.e., cytochrome b (HKY), NLRP2 and Smoc1 (HKY + I), and PANK4 (GTR + I + G). This partition format was set in a Bayesian analysis performed in BEAST 1.10.4  of the mitochondrial sequence marker cytochrome th PhyML  implementh PhyML . We testT 1.10.4 . No outg. The K2P-values of comparisons between G. gazella and geographic groups of G. arabica were larger than two indicating species-level divergence between both taxa. However, within the geographic groups of G. arabica, the K2P-values were all smaller than 1.5. Even if only individuals from the Farasan Islands with the unique haplotype C were considered, K2P-values increased only slightly.To elucidate the geographic structure of our data, we created a haplotype network and plotted it onto a map of the Arabian Peninsula A. WithinLooking at the available population genetic data  published by b and the intron markers NLRP2, PANK4 and Smoc1, indicated high posterior probability support for the clades comprising G. dorcas (PP = 1) and G. gazella (PP = 0.99). For the monophyly of G. arabica, a posterior probability of 0.78 was estimated with a divergence time from G. gazella during the Calabrian period . Within G. arabica one clade comprising the majority of Farasan samples (16 out of 19) and two captive specimens from KKWRC was uncovered with a divergence time of 39 kya . However, this clade received only weak statistical support (PP = 0.64).The phylogenetic tree , based o44.1G. arabica specimens included in our study was rather homogenous with relatively low variation across the Arabian Peninsula. However, nuclear intron markers were not only proven to be capable of distinguishing between gazelle species  but also between more sedentary species like Gazella dorcas or G. arabica. According to The genetic sampling of  species  but also. dorcas  and G. areshurii . Most ofe-biased . Nowadaya marica , suggest4.2G. arabica was located in the East-Mediterranean Levant. This result corresponds to findings reported by The largest variety of haplotypes in our study was found in the north of the Arabian Peninsula, suggesting that the place of origin of G. arabica  because it may have only survived due to the new, introduced mainland genes, preventing a higher degree of inbreeding within this isolated island population  of different geographical origin within Saudi Arabia (N = 6) within the collection, confirming the different origins of founder individuals. Apart from two haplotypes , Puma concolor couguar).The captive breeding stock of i Arabia . The majpression . In suchmeta-population was observed in Milu (Elaphurus davidianus), a reintroduced deer species in China, after animals dispersed into adjacent suitable habitats , and the gene pool of the original population could be enriched, making outbreeding depressions less likely due to local adaptation of reintroduced populations. Such a viable habitats . SuccessThe author confirm that all research activities were conducted in accordance with the relevant laws of Saudi Arabia and the institutional guidelines of KKWRC and the NCW. The authors further ensure that the appropriate institutional committee(s) have authorized the ethical standards of breeding gazelles at KKWRC and using samples for genetic analysis.Deputyship for Research and Innovation at the Ministry of Education in Saudi Arabia for providing the funding to realise the present research project (IFKSUOR3-535-1).The authors further express their gratitude to the The study was designed by MAM and NAH. WM and MAM collected the samples and conducted the laboratory analysis. Data analysis, and interpretation of results was done by HL, TW, and MAM. HL, TW, and MAM wrote the manuscript draft. MAB made significant revisions to the text and provided funding for the open access publication. All authors read and approved the final manuscript.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Begonia L., one of the 10 largest plant genera, contains over 2,100 species, most of which have a very limited distribution range. Understanding the spatial genetic structure and distribution dynamics of a widespread species in this genus will contribute to clarifying the mechanism responsible for Begonia speciation.ndhF-rpl32, atpI-atpH, and ndhA intron), coupled with species distribution modeling (SDM), to investigate the population genetic structure and distribution dynamics of Begonia grandis Dryand., the species of Begonia with the widest distribution in China.In this study, we used three chloroplast DNA markers , strong genetic differentiation (FST = 0.835), and significant phylogeographical structure  were observed. The distribution range of B. grandis migrated northwards after the last glacial maximum, but its core distribution area remained stable.Thirty-five haplotypes from 44 populations clustered into two groups, and haplotype divergence began in the Pleistocene (1.75 Mya). High genetic diversity (B. grandis. BEAST-derived chronogram and haplotype network analysis do not support the Flora Reipublicae Popularis Sinicae and Flora of China for subspecies classification based on morphological characteristics. Our results support the hypothesis that population-level allopatric differentiation may be an important speciation process for the Begonia genus and a key contributor to its rich diversity.Combined, the observed spatial genetic patterns and SDM results identified the Yunnan-Guizhou Plateau, the Three Gorges region, and the Daba Mountains as potential refugia of  SouthweBegonia L., belonging to the family Begoniaceae, is widely dispersed in pantropical forest ecosystems across Africa, America, and Asia. With over 2,100 accepted speciesBegonia is one of the ten largest plant genera and is also the genus with the fastest increase in the number of new species published in the last 20 years , Begonia species have a restricted distribution range, especially these native to limestone karsts , and limited gene flow  A.DC, is one of the few widely distributed begonias native to China. Its distribution ranges from c. 75 m to 3400 m elevation, 97.45° to 121.78° E longitude, and 22.98° to 40.67° N latitude   Irmscher, and B. grandis subsp. holostyla Irmscher]  . Howeverrmscher] . AlthougB. grandis  from a wide range of habitats and assessed its genetic variation and population structure based on three chloroplast DNA (cpDNA) markers , coupled with species distribution modeling (SDM). We aimed to (1) reveal the population genetic pattern of B. grandis, (2) infer its potential glacial refugia and dispersal corridor, and (3) provide a useful reference for subspecies classification, germplasm conservation, and utilization of this widespread species.In this study, we collected samples of 22.1B. grandis plants were sampled from 44 wild populations (8 per population) covering all native distribution regions in China except Tibet , following the manufacturer’s protocol. In a preliminary investigation of chloroplast variation, 24 cpDNA markers were sequenced for 12 samples from 6 natural localities. Because the hF-rpl32 , atpI-atA intron  chloropl2O, 4 μL of 5× Fast HiFidelity PCR buffer, 2 μL of DNA template, 1 μL of 20× Fast PCR Enhancer, 0.8 μL of each forward and reverse primer, and 0.4 μL of Fast HiFidelity Polymerase (Tiangen Biotech). PCR was carried out using the following program: An initial denaturation at 94°C for 2 min, followed by 35 cycles of denaturation at 94°C for 15 s, annealing at 60°C for 10 s, and elongation at 68°C for 30 s, with a final elongation step at 68°C for 5 min. The amplification products were sequenced by Shanghai Maipu Biotechnology Co., Ltd. and Sangon Biotech Co., Ltd. .PCR amplification was carried out in 20-μL volumes containing 11 μL of ddHNucleotide sequences were manually edited in SeqMan , and the2.3Hd), and nucleotide diversity (π) were calculated using DnaSP v5.10 (HT), within-population gene diversity (HS), GST, and NST based on 1,000 random permutations. GST is an unordered measure of genetic differentiation based solely on haplotype frequencies that do not incorporate phylogenetic distance, while NST estimates genetic differentiation based on considering similarities among different haplotypes that incorporate phylogenetic distance. A value for GST significantly lower than that for NST indicates the presence of phylogeographic structure. Analysis of molecular variance (AMOVA) was computed in Arlequin 3.5  and P-values were computed to test the significance of the population expansion model. All these analyses were conducted in Arlequin 3.5 (FST) were regressed against geographic distance using a Mantel test with 999 random permutations in GenAlEx 6.5  were reconstructed using a Bayesian approach implemented in BEAST v1.8.2  was set for cpDNA based on the range of the synonymous substitution rates of chloroplast genes (1 × 10−9 to 3 × 10−9 s/s/y)  tree was generated with a 10% burn-in using TreeAnnotator v1.6.1 (Phylogenetic relationships of the haplotypes and the outgroup (T v1.8.2 . The divT v1.8.2 . As ther9 s/s/y)  to estimr v1.6.1 . Finally2.5B. grandis has not changed since the last glacial/interglacial cycle and will not change in the future  and the future. All herbarium specimens were validated before being used for data analysis. After removing duplicate records, 332 points of B. grandis were obtained from field collections, the Chinese Virtual Herbarium,Under the assumption that the climatic preference of e future , maximume future  was usedr > 0.8) were reduced to single variables (Na), habitat expansion extent (Ne), and locality habitat stability (NStab). Na = (distribution areas of the present)/(distribution areas of the LGM or future), where a value close to 1 denotes a stable distribution, and a value noticeably higher or lower than 1 denotes a change in the distribution region of a species. Ne = [1 − (overlap distribution areas of the LGM or future and present/present distributions area)] × 100% represents the percentage of expansion or contraction between the LGM or future and the present. NStab = 1 − | NPre − NLGM|, where NPre and NLGM mean habitat suitability of the present and LGM distribution area, respectively.Nineteen bioclimatic variables at a 2.5-arcmin resolution for the present (1960–1990), the LGM , and the future  were downloaded from WorldClim 1.4.ariables . Three iB. grandis since the late Quaternary. The specific steps for this method were as follows: Firstly, a resistance layer was created by inverting the SDMs (1−SDM), and the resistance layer was then used to create a cost distance raster for each sample locality. Secondly, corridor layers were created between two localities that only shared haplotypes using the cost distance raster. Thirdly, the least cost path (LCP) method was used to better depict environmental heterogeneity in dispersal. The value of each corridor layer was classified as low, medium, or high, and then these three levels were subdivided into new values . Finally, all of the reclassified corridor layers were summarized and standardized from 0 to 1, and the dispersal corridors of B. grandis were eventually identified.SDMtoolbox  in ArcGI33.1ndhF-rpl32, atpI-atpH, and ndhA intron sequences ranged from 708 to 875, 747 to 847, and 716 to 1072 bp, respectively. The combined length of the three aligned chloroplast fragments was 2,164 bp. Based on the three sequences, 35 haplotypes representing 46 polymorphic sites, including three singleton variable sites and 43 parsimony informative sites, were identified from 352 samples (Hd) and nucleotide diversity (π) were 0.894 and 2.9 × 10−3, respectively  and within-population gene diversity (HS) were estimated to be 0.910 and 0.138, respectively  and ZG  populations had the highest haplotype diversity and the highest nucleotide diversity, respectively  was lower than that of the populations in clade II  , and clade II-2  were calculated  were grouped into clade II , with 83.52% of the total variation found among populations, and only 16.48% within populations (FST = 0.984) was greater than that in clade II (FST = 0.774). However, hierarchical AMOVA indicated that 39.96% of this differentiation was distributed between clade I and clade II, 48.13% was explained by variation among populations within clades, and only 11.90% was found within populations  and in clade II , but not in clade I . Clade II-1  exhibited no significant phylogeographic structure, but clade II-2  did  indicated that this species had not recently undergone demographic expansion at the species level. Populations in geographic regions clade I  and clade II-2  had also not undergone demographic expansion. The investigation of mismatch distributions revealed multimodal distributions that are in line with stable population size  unfolded demographic expansion in neutrality tests inconsistent with the investigation of mismatch distributions that revealed multimodal distributions (A permutation test Table 2 3.2B. grandis with a posterior probability (PP) of 0.96. Thirty-five haplotypes were clustered into two clades  (Begonia grandis and B. pedatifida diverged c. 6.0 million years ago (Mya) with the 95% highest probability density (HPD) date ranging from 2.28 to 12.35 Mya ; (2) from the present to the future (2070), the potential range of B. grandis will experience northward migration, with the loss of distribution area occurring mainly in parts of central and southern China  . The present distributional predictions of the species were consistent with its extant natural distribution Figure 2The supposed dispersal corridors of the LGM and the present were visualized based on SDM results Figure 344.1B. grandis has high genetic diversity , which is very similar to that found for B. heracleifolia Schltdl. & Cham. (HT = 0.937), another widespread species of Begonia , low genetic diversity within populations (HS = 0.138), and variation primarily among populations (83.52%), suggesting that the genetic diversity of this species was mainly due to interpopulation differences. Notably, we detected significant genetic differentiation (FST = 0.835) and phylogeographic structure  in this species. Begonia grandis inhabits stone walls, slopes, waterfalls, stone crevices, and caves along gullies. It is also highly dependent on a specific microenvironment and has requirements for water, relative humidity, light, and temperature within specific ranges. Accordingly, B. grandis is usually fragmented and sporadic in distribution, and most of its populations are small  as well as high nucleotide diversity (π = 1.02 × 10−3). The ZG population in the Three Gorges region had the highest nucleotide diversity (π = 3.56 × 10−3) and also a very high haplotype diversity (Hd = 0.607). Populations (SNJ and WX) in the Daba Mountains also had high genetic diversity . We speculate that the Yunnan-Guizhou Plateau, the Three Gorges region, and the Daba Mountains were glacial refugia and dispersal corridors for B. grandis based on the long-term stability of the habitats and the high genetic diversity of the local populations , and their haplotypes were near the end of the haplotype network rather than being ancestral. This suggested that these populations were not derived from refugia but were a result of northward migration after the glacial period. The eastern populations may have migrated through the Daba Mountains, the Wushan Mountains, and the Yangtze River valley, while the northern populations may have migrated through the Taihang Mountain Range, although the dispersal corridors analysis only weakly supported this possibility. Notably, because B. grandis has significant ornamental value, some eastern populations may have been introduced as ornamental plants from Southwest China, such as population YT found in hills beside temples, and populations XN, LA, and WYS that are found in nature reserves or forest parks. Having asexual bulbils and underground tubers, which become dormant in winter, B. grandis is well adapted to low temperatures, which may explain why its habitat has expanded northward since the LGM.The notable genetic differentiation and phylogeographic structure of  the LGM Figure 24.3B. grandis subsp. holostyla Irmsch., distributed in northwestern Yunnan province, is styles-free and has an unbranched stigma, unlike the populations in other places of this province, it is not monophyletic based on molecular marker analysis. This group may be a transitional type and cannot, therefore, be treated as a subspecies. Our results suggested that B. grandis should not be divided into subspecies as done by FRPS and FOC, and more morphological and genomic data must be combined to support subspecies treatment in future work.The results of the phylogenetic and haplotype network analysis do not support subspecies classification of the FRPS and FOC based on morphological characteristics . There w4.4Begonia grandis has important ornamental value and is often cultivated as a landscape plant in scenic or tourist sites in China. It is also an important traditional medicine. Effective protection of the wild sources of B. grandis is a basic requirement for the sustainable use of this species. Based on the pattern of genetic diversity distribution and the results of SDM, populations with high genetic diversity, unique haplotypes, stable habitats, special traits, or extreme distribution should be protected in situ or conserved ex situ as a priority. Specifically, the populations in southwest regions with potential as refugia, such as the Yunnan-Guizhou Plateau, the Three Gorges region, and the Daba Mountains, have high genetic diversity, and their habitats are stable. The populations in Lingyuan City of Liaoning Province and Chayu County of Tibet Province are in extreme distribution points and have the highest cold resistance. Attention should also focus more on the conservation and utilization of some populations with special traits, such as those with stable, white-spotted leaves in Yongshun county of Hunan province. Meanwhile, as the populations of southern China are the most vulnerable to climate change, they should be continuously monitored.5Begonia grandis is more tolerant to low temperatures than any other species of Begonia. The high haplotype diversity and total gene diversity of B. grandis may indicate that its adaptation to low temperatures allowed it to survive in small but ecologically suitable and isolated habitats throughout the Pleistocene. Thus, its niche has undergone a broad expansion, especially after the glacial periods. The asexual reproductive bulbils in the leaf axils were an important feature in the short-distance dispersal of this species. Given their significant ornamental value, some populations of B. grandis located near temples and scenic sites in eastern China may have been introduced from southwest China. The characteristics of B. grandis mentioned above increase its competitiveness and may be an important reason for its wide distribution. Like other begonias, the seeds, pollens, and bulbils of B. grandis have limited dispersal ability in relatively closed forests. Moreover, B. grandis strongly depends on a specific microenvironment. This leads to fragmented geographical distribution patterns that limit gene flow, which may be an important reason for the significant genetic differentiation between populations. The population genetic structure of B. grandis, with high total genetic diversity, high haplotype diversity, low within-population gene diversity, and significant genetic differentiation between populations, is consistent with a macroevolutionary pattern , our study sheds light on the evolutionary mechanisms responsible for generating and maintaining species diversity in one of the world’s largest plant genera. However, the information on polymorphism based on the chloroplast markers used in our study is limited. Further genome-wide data are needed to more thoroughly reveal the population genetic structure and population history dynamics of B. grandis. In addition, population genetic studies of other widespread species, such as B. longifolia, B. palmata, B. handelii, and B. fimbristipula, are also warranted. pattern . Restricon level . Begoniahttps://www.ncbi.nlm.nih.gov/, OQ433949-OQ433994.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: D-KT, CL, X-LJ, and YX designed the study; D-KT, X-JL, X-PL, CL, and YX conducted the field surveys; X-JL and YX performed the laboratory work; YX and X-LJ analyzed the data; YX, X-LJ, and D-KT prepared the manuscript; D-KT, YX, X-LJ, and W-PL revised the manuscript. All authors contributed to the article and approved the submitted version.


Zabelia tyaihyonii is a familiar shrub, called “Hardy abelia” and “Fragrant abelia” growing in the karst forests of Korea, where it is one of the most threatened species. We investigated the genetic structure and demographic history of Z. tyaihyonii, which allow us to develop appropriate conservation and management strategies. The genetic structure was evaluated using a total of 187 samples from 14 populations, covering the entire distribution of Z. tyaihyonii in South Korea. We utilized 254 and 1753 SNP loci obtained via MIG‐seq (Multiplexed ISSR Genotyping by sequencing) for structure and demographic analyses, respectively. The population demographic modeling was performed with site frequency spectrum. To gain further historical insights, we also employed ENM . We found two distinct clusters (CLI and CLII) of ancient origin (ca. 490 ka). Despite CLII experiencing a more severe bottleneck, both clusters showed similar levels of genetic diversity, indicating mutual historical gene flow. Their historical distribution range seems to have changed very little. We proposed a historical distribution scenario for Z. tyaihyonii, taking into account its intrinsic factors, and emphasized a more complex response to Quaternary climate change beyond simple allopatric speciation models. These findings provide valuable insights for conservation and management strategies for Z. tyaihyonii.Similar to the global phenomenon, many plant species endemic to Korean limestone karst forests are at risk of extinction due to human intervention.  Zabelia tyaihyonii is a familiar shrub, called “Hardy abelia” and “Fragrant abelia” growing in the karst forests of Korea, where it is one of the most threatened species. We explored the evolutionary history and demographic dynamics for populations of Z. tyaihyonii using genome‐wide SNP markers. Here, we provide effective strategies on how to optimally conserve the historical genetic determinants of Z. tyaihyonii, known to have adaptively evolved on calcareous soils. Hara is a temperate deciduous, broad‐leaved shrub in the family Caprifoliaceae that is endemic to the dry karst forests on the Korean Peninsula , excellent fragrance, and strong cold tolerance  Nakai: Chung et al., Saussurea chabyoungsanica Im: Jeong et al., Z. tyaihyonii have sampled a very narrow range, and lacked historical inferences  provides a powerful framework for investigating the interplay between ecological and evolutionary factors that have contributed to the genetic diversity of populations  to investigate their genetic diversity and structure, (2) to evaluate the evolutionary potential and conservation value to the populations from inferring the demographic history, and (3) to provide effective conservation guidelines for the recovery and management from a long‐term conservation genetics perspective.In this study, we aimed to explore the evolutionary history and demographic dynamics for populations of 22.1Z. tyaihyonii. Controversy exists over whether the taxa distributed in the Korean Peninsula should be treated as the genus Zabelia (Rehder) Makino or Abelia R. Br.  collected in South Korea and Abelia mosanensis [= Zabelia mosanensis (T. H. Chung ex Nakai) Hisauti & H. Hara] collected in North Korea  with hairs on the filaments. However, distinguishing these two taxa is inherently difficult because the reference specimens of Z. tyaihyonii were collected during the fruiting season  according to the manufacturer's instructions. The concentration of extracted DNA was determined using Nano‐300 micro spectrophotometer (Allsheng), and diluted to 15 ng/μL to obtain the same concentration of template DNA in each sample.We collected 187 leaf samples of 2.2To obtain genome‐wide single‐nucleotide polymorphism (SNP) data, we used the MIG‐seq method. Preparation of the MIG‐seq library was conducted under standard conditions, according to Suyama et al. , without2.3http://hannonlab.cshl.edu/fastx_toolkit/) so that the length of each read became 134 bp. The low‐quality reads were removed using the program quality_filter in the FASTX‐Toolkit, and extremely short sequence reads were then removed by TagDust 1.12 , observed heterozygosity (HO), expected heterozygosity (HE), and inbreeding coefficient (FIS). Nucleotide diversity (π) was calculated using the ‘populations’ command of Stacks. Allele richness (AR) and genetic differentiation among populations were determined according to the method of Weir and Cockerham  assumed ancient migration during from T1 to T2. Model 4 (secondary contact model) assumed recent migration during from current to T1. We also assumed different population size change in different three time periods, from current to T1, from T1 to T2 and before T2.In order to identify divergence times, patterns of migrations, and population size changes, a coalescent based maximum likelihood analysis estimating parameters of the population demographic model was performed with fastsimcoal2 version 2709 . Missing data was compensated by a bootstrapping within the cluster.To make the input data for fastisimcoal2, as we need information that how many SNPs were obtained from sequences of certain lengths, SNPs were re‐extracted using populations of stacks with options of ‐p 2 ‐r 0.80 ‐‐max‐obs‐het 0.60 ‐‐min‐maf 0.0. The re‐extracted data was constructed from 242,107 all sites, 4178 variant sites (SNPs) and 1753 loci (stacks). Two dimensional minor allele site frequency spectrum (2D‐mSFS) was calculated from the .vcf file with our own R script  Rehd., takes 10–20 years to reach its ultimate height  optimization cycles, and 100,000 coalescent simulations. Mutation rate was set to 5.39 × 102.6Z. tyaihyonii. We first developed a model of current distribution based on occurrence data, and then past distribution was estimated by projecting the model to paleo‐climatic data. We used only 14 occurrence data obtained from our investigations in the analysis because of the rareness of the species. We downloaded 19 bioclimatic variables from Climatologies at High resolution for the Earth's Land Surface Areas . After the quality control of the raw reads, 234,710,807 reads were retained for SNPs calling. Sample coverage for genotyping of Z. tyaihyonii was 32.36x. From the population program in Stacks with the parameter combination of ‐p 14 ‐‐max‐obs‐het 0.60 ‐‐min‐maf 0.03 and write‐single‐snp, a total of 3, 21, 47, and 254 SNPs (loci) were detected under r = 1.00, 0.90, 0.85, and 0.80, respectively. Genetic diversity was estimated from 254 SNPs.In total, we obtained 462,669,080 raw reads from the 187 samples of Z. tyaihyonii, are shown in Table Z. tyaihyonii populations showed relatively similar allelic richness, expected heterozygosity, and nucleotide diversity  across all populations except for KY_H1 and CJ_S6. At the population level, AR and HE ranged from 1.217 to 1.570 (mean 1.471) and 0.086 to 0.198 (mean 0.167), respectively. π ranged from 0.093 to 0.202 (mean 0.175). At the pooled cluster level, the levels of genetic diversity were almost equivalent between cluster I  and cluster II . Also, each of the two clusters harbored private alleles .Genetic diversity parameters, evaluated at the population and pooled cluster levels for all 187 individuals of Z. tyaihyonii, we performed STRUCTURE, PCoA, and Neighbor‐Net phylogeny analysis with 254 SNPs from MIG‐seq. The results clearly demonstrated that the two clusters are genetically distinct. The genetic structure strongly supported K = 2 as the optimal number of clusters for the datasets, based on ΔK statistics in the STRUCTURE analysis  and cluster II . The results of the PCoA for individuals were not clearly separated, but were divided into two clusters based on similarity indices  between genetic differentiation and geographic distances  was significantly larger than that of CLII  because NCLI_0/NCLI_1 and NCLII_0/NCLII_1 were significantly smaller than 1.0. CLI also showed significant increase in population size at its divergence. Divergence time between the two clusters (T2) was 490 ka (95% CI: 292–671 ka). Strengths of migrations between clusters denoted by the number of migrants per generations (Nm) were significantly larger than 1.0 in both direction, and there was no statistically significant difference between directions, as their 95% CIs overlapped.Isolation with the migration model model 2) was selected as the best model . The variable showing the highest percent contribution is glim  and second one is bio04 . The current predicted distribution shows that it is significantly associated with the limestone area in Korean Peninsula , and we were able to identify the historical and intrinsic factors that shaped their genetic composition. Despite CLII having a more severe bottleneck, both the clusters had similar levels of genetic diversity. This can be attributed to bidirectional historical gene flow that contributed to the genetic diversity of both groups without compromising their genetic uniqueness. We propose a historical distribution scenario for Z. tyaihyonii that considers its intrinsic factors, and highlights a more complex scenario that takes into account its response to Quaternary climatic fluctuations, beyond simple allopatric speciation models.We used the MIG‐seq technique to study the genetic diversity of 4.1Z. tyaihyonii populations are structured in two genetically different clusters, as shown in the STRUCTURE, Neighbor‐Net phylogeny, and PCoA analyses with a significant IBD pattern. However, genetic variation in the CJ_S6 population appears to be inconsistent with the geographical proximity of the two clusters in the limestone zones. This population is isolated from other populations by a physical barrier of non‐calcareous substrata. Despite this, the CJ_S6 population does not show unique genetic characteristics and instead forms a clade with geographically more distant populations within CLI, indicating genetic homogeneity. Because a previous study conducted by Kang et al.  can withstand minimum temperatures from −28.9 to −23.3°C, thus it is considered cold hardy , our idea regarding their persistent distribution is considered reasonable. It is, therefore, conceivable that the extant populations are descended from ancestor populations  that had lived in the same (much not different) place as those of the present.We noted that ENM simulated in bedrock conditions revealed that the potential distribution converges to zero across the Korean Peninsula, as if 4.2We detected signs of a recent bottleneck in both CLI and CLII, which can be inferred from the change in the effective population size Table . HoweverZ. tyaihyonii . Due to their flowering time (May), strong floral scent, and floral structure, these shrubs are considered to be active in cross‐fertilization, but often give rise to generations through vegetative reproduction  Blume: Zhu et al., Z. tyaihyonii could mitigate the negative effects of locally occurring or varying strength bottlenecks. This would have allowed for the maintenance of similar genetic diversity throughout the species' distribution range.The one of most plausible factors can be found in symmetric and persistent historical gene flow, as shown in our demographic analysis Figure . Althoug4.3Z. tyaihyonii populations in South Korea should be developed to maintain the unique genetic identity of each cluster. Additionally, since it is uncertain whether other Z. tyaihyonii populations exist in North Korea, it is important to consider that the few remaining populations in South Korea may represent the entire distribution range of this species. This fact should be a fundamental consideration when contemplating industrial development in specific habitats of this species. The possibility of the species existing in North Korea could potentially make it more vulnerable to extinction of this shrub by providing a more favorable perspective towards development.Based on full range of analyses, we recommend that conservation strategies for Z. tyaihyonii may be a strategic outcome that has contributed to their long‐term survival, potentially due to their flexible outcrossing and vegetative reproductive systems. Moreover, our analysis suggests that the uniform genetic diversity across the entire populations may be a result of historical environmental changes, rather than recent human‐induced destruction ; data curation (lead); methodology ; writing – original draft (lead); writing – review and editing . Eun‐Kyeong Han: Formal analysis ; methodology ; software ; visualization (lead). Martin Wojciechowski: Writing – review and editing . Tae‐Im Heo: Conceptualization ; investigation ; project administration ; resources . Jong‐Soo Park: Methodology ; software ; visualization (supporting). Jong‐Cheol Yang: Investigation ; project administration ; resources . Amarsanaa Gantsetseg: Data curation (supporting); formal analysis ; visualization (supporting). Kyeong‐Sik Cheon: Writing – review and editing . Ichiro Tamaki: Methodology (lead); software ; visualization (supporting); writing – review and editing . Jung‐Hyun Lee: Conceptualization ; supervision (lead); visualization (supporting); writing – original draft (supporting); writing – review and editing .This research was funded by a research grant from the Baekdudaegan National Arboretum (KIAM‐2021‐KS‐OB‐02‐01‐02).The authors declare no conflict of interest.Figures S1–S2Click here for additional data file.


Paeonia decomposita, Paeonia rotundiloba, and Paeonia rockii are three closely related species of Sect. Moutan is distributed in the montane area of the Eastern Hengduan Mountain region. Understanding the population history of these three tree peony species could contribute to unraveling the evolutionary patterns of undergrowth species in this hotspot area. We used one nuclear DNA marker  and two chloroplast DNA markers  to reconstruct the phylogeographic pattern of the populations. In total, 228 individuals from 17 populations of the three species were analyzed in this study. Three nuclear clades (Clade I – Clade III) and four maternal clades (Clade A – Clade D) were reconstructed. Molecular dating suggested that young lineages diverged during the late Pliocene and early Pleistocene, younger than the uplift of the Hengduan Mountains but older than the last glacial maximum (LGM). Significant population and phylogeographic structures were detected at both markers. Furthermore, the populations of these tree peonies were overall at equilibrium during the climatic oscillations of the Pleistocene. The simulated palaeoranges of the three species during the LGM period mostly overlapped, which could have led to cross‐breeding events. We propose an evolutionary scenario in which mountain orogenesis around the Hengduan Mountain area triggered parapatric isolation between maternal lineages of tree peonies. Subsequent climatic fluctuations drove migration and range recontact of these populations along the valleys. This detailed evolutionary history provides new insights into the phylogeographic pattern of species from mountain‐valley systems. Location of populations sampled (a); Geographic distribution of the chloroplast (cp) DNA haplotypes (population codes and chlorotype node refer to Table S1), the solid black lines represent three groups according to SAMOVA analysis, and the dotted lines display six groups (b); Maximum parsimony network based on chlorotypes (c). The size of the pie is a positive correlation with the frequency of each haplotype and black dots represent haplotypes that are missing, extinct, or not observed. Hong, and Paeonia rockii (S.G. Haw & Lauener) T. Hong & J.J. Li ex D.Y. Hong are three closely related tree peonies distributed in forest margins or thickets of adjacent valleys in the Qinling–Hengduan Mountains  and two chloroplast DNA markers  and ecological niche modeling (ENM). Our aims in this study are to (i) reveal the geographic patterns of population genetic variation of the species; (ii) elucidate the evolutionary factors that might be responsible for the patterns and levels of genetic variation observed; and (iii) describe the demographic patterns of three closely related tree peonies that evolved during the LGM.In this study, we present an analysis of the population genetic structure, phylogeography, and historical demography of 22.1P. decomposita, five populations of P. rotundiloba, and four populations of P. rockii were used for sampling from 2015 to 2016. Each sample was collected at least 20 m away from the other to magnify the allele frequency difference within each population. Fresh leaves of each individual were collected in the field and immediately dried with silica gel for DNA testing .A total of 228 individuals from eight natural populations of 2.2matK and ycf1, were amplified and sequenced using the primer pairs ITS‐1F (5′‐GTA GGT GAA CCT GCA GAA GGA TCA‐3′), 18S‐25S‐3′R , matK1248R , and ycf1R . A total of three DNA fragments, the ITS and two chloroplast genes 2.3www.ncbi.nlm.nih.gov) to detect contamination and confirm the targeted markers. Sequences were aligned using MAFFT v.7 and then adjusted manually in BioEdit v.7.0.0  and P. delavayi (U27679.1) as nrITS outgroups and P. lutea, P. delavayi , and P. ludlowii (KY817592.1) as cpDNA outgroups to reconstruct the phylogenetic tree. Maximum likelihood (ML) trees were reconstructed using PAUP* 4.0b10  and nucleotide diversity (π) were estimated according to Nei (hS and πS) and species (hT and πT) using DnaSP  with the MP criterion. A split phylogenetic tree based on the Neighbor‐Net algorithm  and ITS, indices of haplotype diversity (g to Nei  at the lK) that were geographically homogeneous and maximally differentiated from each other, with the number of groups ranging from 2 to 20. The analysis was reported five times for each K value with 1000 independent iterations, starting from 100 random initial conditions. The configuration with the highest and most significant FCT value was retained as the best grouping of populations.SAMOVA 1.0  and total genetic diversity (HT) within a population, as well as genetic differentiation between populations (GST and NST), were estimated using PERMUT v1.2.1 with the 1000 permutations test (http://www.pierroton.inra.fr/genetics/labo/Software/PermutCpSSR). The GST and NST were compared to determine the phylogeographic structure following Pons and Petit (Genetic diversity (nd Petit .FST) and geographical distances of all populations (Mantel test) were tested using the software Arlequin v.3.0  using 1000 parametric bootstrap replicates for each model. Where the sudden expansion model was not rejected, the formula T = τ/2u , where u = μkg; μ is the neutral mutation rate of the sequence in substitutions per site per year (s/s/y), k is the average sequence length  and g is the generation time in years . The analyses were run using an uncorrelated relaxed molecular clock under Bayesian skyline models for 108 iterations with burn‐in periods of 25%. The substitution models were set to GTR + I + G for nrITS and HKY + I for cpDNA. Genealogies and model parameters were sampled every 10,000 iterations. Chain convergence was inspected in Tracer v.1.5 software, and the results with an effective sample size (ESS) for each parameter >200 were accepted. The BSP was visualized in the program Tracer v.1.5, which summarizes the demographic history over time.To estimate the change in demographic growth over the history of the samples, we carried out two Bayesian skyline plot analyses (BSPs), implemented in BEAST v1.8.2 (7 generations with 25% burn‐in. The log file was then checked for convergence of the chains using Tracer 1.5. A maximum clade credibility (MCC) tree with the maximum sum of posterior probabilities on its internal nodes  and the literature , Bayesian, and maximum likelihood methods. Clade C contained haplotypes from P. decomposita and P. rotundiloba. P. rockii was polyphyletic and included haplotypes C7–C9  and C10–C13 (extracted from population CZ), corresponding to Clades B and D respectively    was higher than the average within‐population diversity . The NST was significantly higher than the GST values for both markers , suggesting a strong phylogeographic structure within these three species. For the spatial analysis of molecular variance (SAMOVA), the gradients of distribution of FCT values were both significantly decreased when K = 3 . Six groups can be concluded as a subdivision of the three groups' design , three of which were endemic . For nrITS, the West group contained 71 haplotypes  and contained two haplotypes (C1 and C5), only one of which was endemic for P. rotundiloba (C5). For nrITS, the Central group of nrITS included all five P. rotundiloba populations, and 11 haplotypes  clustered into the blue lineage, eight of which  were endemic. The East group of cpDNA contained one P. rotundiloba population (LG) and all four P. rockii populations, corresponding to eight haplotypes , all of which were endemic. In contrast, the East group of nrITS contained all four P. rockii populations and 33 haplotypes (H79–H111), all of which were endemic and clustered into three lineages . Each population contributed quite differently to total haplotype diversity. For details of the haplotype geographic distribution, see Figures When AMOVA revealed that the differences among populations  explained 91.7% of the total cpDNA variation. However, variation within populations accounted for most (83.68%) of the variation in nrITS Figures  and S3. 3.3D values . The current distributional predictions covered the species' extant distribution. However, there were also some predicted areas where the species are not found at present. In contrast, distributional predictions for the LGM  were different from the present, revealing a general southwards range shift. Furthermore, the simulated distribution areas of the three tree peonies at the LGM partially overlapped . Mountain barriers could shape the phylogeographic patterns and population structures of these tree species. The Min Mountains (4000 m a.s.l.) serve as a geographical barrier, as steep mountains and thick forest vegetation prevent seed and pollen dispersal from crossing, to realize gene transfer between tree peony recipients and potential donors. The role of landscape features in affecting genetic differentiation has been documented in the Paeonia subsect. Delavayanae ; data curation (lead); formal analysis (lead); methodology (lead); software (lead); writing – original draft (lead); writing – review and editing (lead). Ge Xue: Conceptualization (lead); data curation (lead); formal analysis (lead); funding acquisition (lead); investigation (lead); methodology (lead); project administration (lead); resources (lead); visualization (lead). Tingting Zhao: Data curation (supporting); formal analysis (supporting); software (supporting); visualization (supporting); writing – original draft (supporting); writing – review and editing (supporting). Yang Li: Data curation (supporting); investigation (supporting); writing – original draft (supporting); writing – review and editing (supporting). Liangliang Yue: Data curation (lead); formal analysis (lead); investigation (lead); methodology (lead); software (lead); validation (lead); visualization (lead); writing – original draft (lead); writing – review and editing (lead). Huixing Song: Conceptualization (supporting); methodology (supporting). Qinglin Liu: Conceptualization (supporting); methodology (supporting).None.The authors declare no conflicts of interest.Appendix S1:Click here for additional data file.