Old World camels are a valuable genetic resource for many countries around the world due to their adaptation to the desert environment. At present, Old World camels have encountered the challenge of unprecedented loss of genetic resources. Through our research, we would reveal the population structure and genetic variation in Old World camel populations, which provides a theoretical basis for understanding the germplasm resources and origin and evolution of different Old World camel populations.In the present study, we assessed mtDNA control region sequences of 182 individuals from Old World camels to unravel genetic diversity, phylogeography, and demographic dynamics.Fs test demonstrated a decrease in population size and/or balancing selection in the wild Bactrian camel population. In contrast, the negative values of Tajima’s D and Fu’s Fs test in East Asian Bactrian camel populations explained the demographic expansion and/or positive selection.Thirty-two haplotypes confirmed by 54 polymorphic sites were identified in the 156 sequences, which included 129 domestic and 27 wild Bactrian camels. Meanwhile, 14 haplotypes were defined by 47 polymorphic sites from 26 sequences in the dromedaries. The wild Bactrian camel population showed the lowest haplotype and nucleotide diversity, while the dromedaries investigated had the highest. The phylogenetic analysis suggests that there are several shared haplotypes in different Bactrian camel populations, and that there has been genetic introgression between domestic Bactrian camels and dromedaries. In addition, positive values of Tajima’s D and Fu’s In summary, we report novel information regarding the genetic diversity, population structure and demographic dynamics of Old World camels. The findings obtained from the present study reveal that abundant genetic diversity occurs in domestic Bactrian camel populations and dromedaries, while there are low levels of haplotype and nucleotide diversity in the wild Bactrian camel population. Camelus Bactrianus) and dromedary (Camelus dromedarius), and the only representative wild species remaining, wild Bactrian camel (Camelus ferus), following the extinction of the wild dromedary [The Old World camels are represented by the Tylopoda suborder which comprises domesticated Bactrian camel , as a molecular marker, is widely used in the identification of wild ancestors and maternal lines that have contributed to a breed or population –14. OverCamelus dromedarius) and Bactrian camel (Camelus bactrianus), and one wild species, wild Bactrian camel (Camelus Ferus), have been seriously affected; this is especially the case for the wild Bactrian camel species, which is on the verge of extinction [With the modernization of society and increasing desertification, the genomic resources from the two domesticated Old World camel species, dromedary (tinction . UnfortuThe present study was conducted on 182 sequences which were downloaded from GenBank. These included wild Bactrian camel from Mongolia (n = 27); domestic Bactrian camel from China (n = 57), Mongolia (n = 43), Russia (n = 10), Kazakhstan (n = 6), and Iran (n = 13); and dromedary (n = 26) from Africa . In accoDnaSP v5 was used to determine the level of genetic diversity, including polymorphic sites (S), number of haplotypes (H), haplotype diversity (Hd), nucleotide diversity (π), the average number of nucleotide differences (K) and the standard deviations (SD). These parameters were identified for each population and across all populations .In order to assess the possible genetic relationship between individuals and populations, a phylogenetic tree was constructed with the neighbor-joining (NJ) algorithm implemented in MEGA6 . The conFs [Fs test, which is more powerful than Tajima’s D [We calculated the demographic profiles for each geographic region from mismatch distribution patterns . At the Fs  and TajiFs  statistiFs . Tajima’Fs . Positivjima’s D .Thirty-two haplotypes confirmed by 54 polymorphic sites were identified in the 156 sequences, which included 129 domestic Bactrian camels and 27 wild Bactrian camels. There were 30 haplotypes determined in the domestic Bactrian camel population and two in the wild Bactrian camel population. Meanwhile, 14 haplotypes were defined by 47 polymorphic sites from 26 sequences in the dromedaries . In the At the country level, excepting the wild Bactrian camel populations, all other populations showed a high level of maternal genetic diversity, including dromedaries. In the domestic Bactrian camel populations, the highest level of Hd (0.876±0.033) was observed in Mongolia, while the lowest (0.600±0.0215) was found in Kazakhstan; the lowest level of nucleotide diversity (0.00188) was observed in China, while the highest (0.066) was observed in Iran’s domestic Bactrian camel population.Furthermore, we divided domestic Bactrian camel populations into two groups to investigate genetic diversity: East Asia (China and Mongolia’s domestic Bactrian camel populations) and Central Asia . The number of haplotypes from east Asia (H = 21) was higher than central Asia (H = 13); however, the genetic diversity for populations from Central Asia (Hd = 0.896±0.033 and π = 0.01043) was slightly higher than East Asia (Hd = 0.801±0.030 and π = 0.00238). Interestingly, the wild Bactrian camel population showed the lowest Hd (0.462±0.065) and nucleotide diversity (0.00115), while dromedaries revealed the highest Hd (0.908±0.041) in this study .In order to assess genetic relationships between Bactrian camels and dromedaries, the NJ tree was constructed for the 809 bp CR  and haplFurthermore, the phylogenetic relationships among domestic Bactrian camel population haplotypes, with H_2 and H_8 excluded, are shown in a MJ network . HaplotyFs values. These results suggest a complex demographic history for the different camel populations. While no significant differences were found for the Harpending raggedness index (r) and SSD in Old World camel populations, the results demonstrated that our total dataset showed relatively good fit to the population expansion model [We predicted mismatch distribution patterns for domestic Bactrian camel populations from different geographic regions, the wild Bactrian camel population and the dromedary population. To clarify the demographic dynamics of Old World camels, the mismatch distribution graphs revealed uni-, bi- and multi-modal patterns , which son model .In this study, we assessed the mtDNA genetic diversity of 182 Old World camels including domestic Bactrian camels from China, Mongolia, Russia, Iran and Kazakhstan, wild Bactrian camel from Mongolia; and dromedaries. The aim of our research would reveal Old World camel populations history and demographic dynamics using the most polymorphic CR in mtDNA. This highly polymorphic CR has been used in previous research to assess the genetic diversity and phylogeny of camels, especially in relation to the maternal origin of Old World Camels ,17,19, iWe observed higher haplotype and nucleotide diversity in the dromedary CRs compared to the domestic and wild Bactrian camel populations . This coIn the domestic Bactrian camel populations, there was no distinguishing geographic structuring in the NJ tree and median-joining network among populations from China, Mongolia, Russia, Kazakhstan, and Iran. This result indicated the populations’ single maternal lineage and that strong gene introgression existed in different domestic Bactrian camel populations, especially individuals MH109985 (H_2) and MH109974 (H_8) from Kazakhstan and Russia, which were clustered with the dromedaries; this finding has also been confirmed in whole genome sequencing research . The SilFs test in the wild Bactrian camel population, which demonstrates a decrease in population size and/or balancing selection. At the same time, positive values of Fu’s Fs test were found in the Central Asian  domestic Bactrian camels, which may also be related to a decreasing population size, especially considering that an Iranian population census indicated there were just several hundred individuals remaining. These results are in agreement with reduced genetic diversity and small effective population size in wild and domestic Iranian Bactrian camels. Meanwhile, negative values of Tajima’s D and Fu’s Fs test in East Asian populations  of domestic Bactrian camels can be explained by demographic expansion and/or positive selection.During the process of domestication, population growth and dispersion of animals across a wider geographic range can be determined from molecular signals of sudden expansion . In our In summary, we report novel information regarding genetic diversity, population structure and demographic dynamics of Old World camels. The findings obtained from the present study reveal that abundant genetic diversity occurs in domestic Bactrian camel populations and dromedaries, while low levels of haplotype and nucleotide diversity were found in the wild Bactrian camel population.


G. barbatus populations using a panel of 14 microsatellite loci.The bearded vulture is sparsely distributed across a wide geographic range that extends over three continents . Restriction to high-altitude mountainous habitats, low breeding rates, lack of food and a heightened level of persecution have left many local populations severely diminished or extinct. Understanding the genetic connectivity and population structure of this threatened vulture species is critical for accurately assessing their conservation status, and for appropriately managing local populations through captive breeding programmes or translocations. Previous genetic assessments of the species were mainly focused on the European and Asian populations and included limited representation of the geographically isolated southern African population. A single mitochondrial study, which focused on the African populations of the bearded vulture, detected limited genetic differentiation between populations in Ethiopia and southern Africa, with reduced haplotype diversity in the southern Africa population. In this study, we extend the previous genetic assessments of the species by examining the phylogeography and genetic connectivity of global Analyses revealed spatially correlated genetic differentiation between regional populations and low levels of gene flow between these population fragments. In contrast to the mitochondrial data, the microsatellite data support the management of genetically different populations as separate entities.G. barbatus and, to a lesser extent, the northern African populations highlights the need for conservation programmes to effectively manage populations of this species and maintain extant genetic diversity.Low genetic diversity and geographic isolation are known to adversely affect the evolutionary potential of a species in the long-term. The high inbreeding found in the southern African The online version contains supplementary material available at 10.1186/s12862-021-01760-6. Gypaetus barbatus, were considerably more abundant, albeit always sparsely distributed across a wide area ranging from the Palearctic, through Afrotropic and into Indomalay regions [Historically, bearded vultures,  regions . In the  regions –4. A pop regions , 2.In Europe, the population declined in the nineteenth century due to food shortage and direct persecution. This led to local extinction in the Alps by the early twentieth century . The PyrIn Africa, habitat loss, electrocution and collision with energy infrastructure, unintentional poisoning through veterinary drug-use, feeding on poison baits aimed at predator control and intentional poisoning for the use of vulture body parts in the illegal wildlife and the traditional medicine trade, are the primary culprits for the population decline in many vulture species –16. ThesMorocco is home to fewer than 20 individuals and the species is considered extinct in Tunisia . EthiopiDue to the reduced effective population size, small disjunct populations experience amplified genetic drift, inbreeding and a greater loss of genetic diversity –23. LossGypaetus barbatus barbatus is distributed across Europe and Asia, extending into north-west Africa , and Gypaetus barbatus meridionalis is found in north-east Africa, east Africa and extends into southern Africa. Studies based on maternally inherited mitochondrial data found evidence for two distinct lineages of bearded vultures which did not correspond geographically to the morphologically described subspecies. The first lineage described by Godoy et al. (2004) occurs predominantly in western Europe, and the other lineage extends over Africa, eastern Europe and central Asia. This study detected high levels of inter-population differentiation, with admixture between the two lineages occurring in Greece and the Alps [Two subspecies of bearded vulture have been recognized based on plumage characteristics and geography —Gypaetusthe Alps . Godoy ethe Alps . These cthe Alps . Most gethe Alps , 29, 30.The genetic results have implications for captive breeding programmes and open the possibility for the translocation of individuals into shrinking populations. Unfortunately, previous studies have focussed their analyses almost entirely on the European population (with limited representation from southern Africa). The single study that included good representation of the isolated southern African population was based on mitochondrial DNA . In thisST values , suggesting that null alleles have a very limited effect on the genetic structuring analyses in these samples of bearded vultures. In addition, many of the analyses we conducted are not strongly influenced by the presence of null alleles [A total of 236 individuals were genotyped with the 14 microsatellite markers. All loci were polymorphic with the number of alleles per individual ranging from 6 (Gf11A4) to 17 . A summary of locus-by-locus measures of genetic diversity are provided in Additional file  alleles . LinkageSignificant departures (p < 0.05) from HWE were obtained for all loci in the southern African population. Loci 1, 3 and 4 were in HWE for the European, northern African and Eastern population complexes, respectively. The remaining loci did not conform to HWE predictions. This was not unexpected as these small isolated populations naturally deviate from the assumptions of HWE.IS > 1, Table O < HE; Table The average number of alleles and effective alleles ranged from 5.93–7.00 and 2.81–3.23 respectively , followed by the southern African population Q = 0.92) and the Asian populations (Q = 0.88). The highest admixture was detected in the northern African populations .In all analyses, the isolated southern African bearded vulture population is genetically distinct from all other bearded vulture populations. Genotypes collected from this region appear to belong to unique genetic clusters and are characterized by unique allele frequencies. The genetic distinctiveness of the southern African population is also reflected in the number of unique alleles found in this population . The European population complex contains only 18 unique alleles and the Asian and northern African complexes have fewer than 10 unique alleles each. Only 31 alleles are shared by all populations. Results from the Mantel test indicate that there was no positive correlation between genetic and geographical distance  of variation was attributed to within individual differences, while differences among individuals and among populations explained 39% (p < 0.001) and 12% (p < 0.001) of the diversity respectively.The BayesAss 3.0 analysis indicates that the highest migration seems to have occurred from the European populations to the Asian populations . This supports the hypothesis that, before the extinction of bearded vultures in the Alps, there was an interconnected European population from Spain to the Alps, Balkans to Turkey and Asia.Minimal migration has occurred within Africa in the recent past. Less migration took place from northern Africa to southern Africa, than the reverse . There is debate over the splitting of the northern lineage into either one, Gypaetus barbatus barbatus [Gypaetus barbatus aureus , Gypaetus barbatus hemachalanus  and Gypaetus barbatus barbatus  [G. b. barbatus in Eurasia and northern Africa and G. b. meridionalis in eastern and southern Africa. The diversification of the northern and southern bearded vulture lineages is hypothesised to be linked to the expanding Sahara Desert which acted as a physical barrier during the last glacial maximum [The pattern of population differentiation found here provides clarification of the population structure and migration of bearded vultures. Although there is debate over the number of subspecies of bearded vultures –43, our barbatus , or 3 sus, 1758) , 42. Bas maximum . When thBased on this species’ philopatric dispersal behaviour, genetic differentiation between regional populations is expected to increase with geographic distance following an isolation-by-distance model , 47, espApart from past persecution, the southern African population of bearded vultures continues to suffer threats from several sources, adding to their continued decline , 48. PasThis study highlights the utility of integrating genetic data to inform conservation strategies as it elucidates information that is not readily evident in the field. Our results suggest that the southern African bearded vulture population, being distinct from other such populations, may represent a reservoir of genetic variation that should be given separate conservation status.A total of 236 bearded vulture specimens were analysed in this study. These include samples from across the global distribution of the species Fig. , and incThe NucleoSpin® Tissue kit (Macherey–Nagel) was used for all DNA extractions. The standard protocol for extracting genetic material from blood was followed for blood samples. The feather and archival tissue extractions were done using the standard protocol for muscle tissue, with the following modifications to increase DNA yield: incubation of the ~ 5 mm feather tip/skin snip and proteinase K for 48 h, lysate was then incubated in B3 (buffer) for 45 min (70 °C), the final volume of pre-warmed Buffer BE was decreased to 80 μl, incubation at 70 °C for 20 min followed by centrifuging and then reapplication of the solution onto the membrane, followed by incubation at 70 °C for an additional 5 min and a final centrifugation step. DNA concentrations were determined using the ThermoScientific NanoDrop 2000 spectrophotometer . All DNA extracts were stored at -20 °C.Gyps species [Fourteen microsatellite loci Table  were amp species . MicrosaST values [ST values were compared to FST values corrected using the excluding null alleles (ENA) method using a paired t-test. The presence of scoring errors, such as incorrect assigning of genotypes and fractions in genotypes, was assessed using GenAlEx v6.5 [A), allelic richness (AR), inbreeding co-efficient (FIS) and gene diversity. Effective alleles at each locus (NE), observed (HO) and expected (HE) heterozygosity were calculated in GenAlEx. FSTAT was used to determine allelic richness and gene diversity. Tests for deviation from Hardy–Weinberg equilibrium (HWE) and linkage disequilibrium were performed in Genepop v4.2 [IS) and population differentiation (FST) [IS and FST explain the deviations seen from HWE. Positive FIS values suggest higher inbreeding values (due to higher observed homozygosity) than would be expected under HWE, and vice versa. FST shows the genetic differentiation between two populations which no longer conform to the HWE assumptions.Null alleles in data can be problematic for calculations of genetic variability as they can decrease within-population variance and so inflate FT values . The preT values . UncorrelEx v6.5  and FSTAlEx v6.5 . These ppop v4.2  and FSTAon (FST) , 57 wereon (FST) . FIS andPopulation structure across the global distribution of the bearded vulture was assessed using a Bayesian clustering method implemented in the software program STRUCTURE version 2.3.4 , 60. TheAdmixture and No Admixture model parameters. If there is reason to consider each population as completely discrete, the No Admixture model is appropriate. In contrast, the Admixture model allows for a large proportion of sampled individuals to have ancestry from multiple lineages, which implies a shallower population structure. The historically wide geographic distribution of the bearded vulture favours the Admixture model, and previous molecular work suggests that the African, European and Asian populations are genetically closely linked [Analyses were run using both the y linked , 29. TheAll STRUCTURE analyses were performed with 100 000 Markov-Chain Monte Carlo (MCMC) replicates with a burnin of 10 000. The number of iterations for all assignments was 10 with K ranging from 1 to 10. Once all the simulations were completed, STRUCTURE Selector  was usedST) values were calculated in FreeNA using the ENA-corrected method. Population assignment analysis was conducted in GenAlEx. Pairwise FST values were calculated using two grouping schemes. Individuals were grouped by country of origin, and then because some countries have very low sample sizes, individuals were also grouped by region  was estimated using the Bayesian algorithm implemented in BayesAss 3.0 . The anaAdditional file 1. Supplementary data for Bearded Vulture analysis.


Paeonia subsect. Delavayanae composed of one widespread species (Paeonia delavayi) and the other geographically confined species (Paeonia ludlowii). We gathered genetic variation data at three chloroplast DNA fragments and one nuclear gene from 335 individuals of 34 populations sampled from HHM. We performed a combination of population genetic summary statistics, isolation-with-migration divergence models, isolation by environment, and demographic history analyses. We found evidence for the current taxonomic treatment that P. ludlowii and P. delavayi are two different species with significant genetic differentiation. The significant isolation by environment was revealed within all sampled populations but genetic distances only explained by geographical distances within P. delavayi populations. The results of population divergence models and demographic history analyses indicated a progenitor–derivative relationship and the Late Quaternary divergence without gene flow between them. The coalescence of all sampled cpDNA haplotypes could date to the Late Miocene, and P. delavayi populations probably underwent a severe bottleneck in population size during the last glacial period. Genetic variation in Paeonia subsect. Delavayanae is associated with geographical and environmental distances. These findings point to the importance of geological and climatic changes as causes of the speciation event and lineage diversification within Paeonia subsect. Delavayanae.Himalaya and Hengduan Mountains (HHM) is a biodiversity hotspot, and very rich in endemic species. Previous phylogeographical studies proposed different hypotheses (vicariance and climate-driven speciation) in explaining diversification and the observed pattern of extant biodiversity, but it is likely that taxa are forming in this area in species-specific ways. Here, we reexplored the phylogenetic relationship and tested the corresponding hypotheses within  Mountains are often hotspots of endemism, where the geological activities and climatic changes are historically frequent, driving lineage divergence, and speciation both in tropical and temperate regions , is a monotypic genus with a long evolutionary history and possesses germplasm resources with significant medicinal values . Moreover, great morphological diversity exists within P. delavayi, and this diversity was previously ascribed to several species , They exhibited continuous and overlapping variation in leaf and flower color characters without geographic patterns and then thus amalgamated into one species P. delavayi  D. Y. Hong, the other member of subsect. Delavayanae, is geographically confined to southeastern Tibet with a high average but narrow altitude range . P. ludlowii was firstly reported as one variety of P. lutea by Stern and Taylor (P. ludlowii)  Hong, .Delavayanae, but the genetic boundary between the two species is still controversial , Tibetan, and the rest populations of P. delavayi based on the SSR dataset , to test the hypothesis on geology- vs. climate-driven divergence within subsect. P. delavayi were collected from 31 locations covered the geographic distribution range  and three populations of P. ludlowii were sampled to represent the geographical spread in Mainling, Tibet (EH)  . Within trnL-trnF, rps16-trnK, trnH-psbA) and one presumably single-copy nuclear gene (ATP-dependent Lon protease) were amplified and sequenced using the published primers  coding method in Gapcoder to code all contiguous indel events involving more than one base pair as one mutation event  of cpDNA haplotypes was estimated in BEAST 1.8.2  were estimated using the coordinate information in GenAlex  at 2.5′ spatial resolution, after removing variables with Pearson's correlation values (|r|) >0.9 to reduce multicollinearity, according to Zhang J. M. et al.  analysis implemented in R Wang, . Pairwis. et al. . BrieflyP. delavayi and P. ludlowii species pairs: two effective population sizes for P. delavayi (θ1) and P. ludlowii (θ2), one ancestral effective population size (θA), two bidirectional migration rates (m1 and m2), and the splitting time between the two species (t). The HKY model was chosen for both cpDNA and nuclear loci. Initial pilot runs were used to select upper bounds on Bayesian priors. The MCMC analyses contained 20,000,000 steps after a burn-in period of 2,000,000 steps. All runs were repeated three times, and results were found to be consistent between runs with random starting seeds. All resultant ESS values were > 200. Parameter estimates were converted to demographic values using 3.18 × 10−10 as above. For the average substitution rates of plants which are generally about 4–5 times higher in nDNA than in cpDNA  statistical framework to all cpDNA and nuclear data, to compare four scenarios of divergence and population size changes. Scenarios were built considering the IMa and phylogenetic analyses, which point to a possible progenitor–derivative relationship between P. delavayi and P. ludlowii. The first scenario consisted of an older and simultaneous divergence of the two species due to the uplifts of the HDM and P. ludlowii experienced bottlenecks during the glacial period. The second scenario predicts that P. ludlowii is derived from P. delavayi during the last glaciation and established its current distribution through recent expansion. Because the distributions of organelle DNA haplotypes and EBSP analysis indicated that P. delavayi might have experienced a recent bottleneck, in scenarios 3 and 4, population size changes of P. delavayi were assumed and added on the basis of the first two scenarios. Simulations for each scenario and ABC analyses were conducted using DIYABC  was widely distributed and shared by lots of populations, and a high number of private haplotypes were also detected. Populations in EH were fixed by one haplotype (A1), and rare haplotypes  were found in populations in YP , whereas nuclear genes showed that the majority of variation (59.07%) separated P. delavayi and P. ludlowii, and 37.50% of variation was among populations within species   rather than between  species . On the delavayi . Our anadelavayi . The deludlowii) . The mea)  but not the environmental distance . However, among the three regions of P. delavayi , the majority of the bioclimatic variables were significantly distinct , though comparatively geographical distance still contributed more to the total genetic variation .The PCA results showed that the genetic distance of distinct . InteresP. ludlowii formed a monophyletic clade nested within P. delavayi haplotypes, giving limited support for monophyletic groups with subsect. Delavayanae . Most of major haplotype clades (formed by one or more haplotypes) depicted in the network were roughly concordant with the geographical distribution of populations , 2. The P. delavayi and P. ludlowii were represented graphically in P. delavayi (θ1 = 1.498) was at least an order of magnitude greater than that found in P. ludlowii (θ2 = 0.100) (A = 19.345)  (t was peaked at about 0.023 (HPDI = 0.006–0.061)  . Contemp 19.345) , suggest m2 = 0) . The pos6–0.061) , and aftte of Ne . In DIYAte of Ne . In addite of Ne . ScenariP. ludlowii and P. delavayi has been proved in the previous study , suggesting that P. delavayi has a long evolutionary history and both complex tectonic events  surrounded by high peaks (such as Nushan and Gaoligongshan) resulted from HHM uplift events which favored deep allopatric divergences, and perhaps lineage persistence during the ensuing Pleistocene climatic fluctuation in “refugia within refugia” of P. delavayi.Although the lines of evidence inferred from the demographic history analyses dismiss the possibility of speciation in P. delavayi were obtained and the precise divergence time for intraspecific lineages could not be estimated from the present genetic datasets, but the fixed private haplotypes in most populations and very low levels of admixture in the nuclear gene indicated that P. delavayi is on the way of speciation (incipient speciation)  Liu, . Particuon) Liu, , the popon) Liu, , which sP. delavayi must have taken place resulting in the loss of chloroplast haplotypes. This result is concordant with the coalescent analyses, in which the estimated population size was obviously smaller than that of the ancestral population , compared with those of congeneric species including P. jishanensis, P. qiui, and P. rockii or other shrubs distributed in HHM such as S. moorcroftiana  can be found in the article/Y-JZ and XG planned and designed the research. Y-JZ, G-SY, BT, and Y-ZP conducted the field work and drew the figures. Y-JZ and G-SY performed the experiments and analyzed the data. Y-JZ and XG wrote the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The Afrikaner population of South Africa is the descendants of European colonists who started to colonize the Cape of Good Hope in the 1600s. In the early days of the colony, mixed unions between European males and non-European females gave rise to admixed children who later became incorporated into either the Afrikaner or the Coloured populations of South Africa. Differences in ancestry, social class, culture, sex ratio and geographic structure led to distinct and characteristic admixture patterns in the Afrikaner and Coloured populations. The Afrikaner population has a predominant European composition, whereas the Coloured population has more diverse ancestries. Genealogical records previously estimated the contribution of non-Europeans into the Afrikaners to be between 5.5 and 7.2%.To investigate the genetic ancestry of the Afrikaner population today , we genotyped approximately five million genome-wide markers in 77 Afrikaner individuals and compared their genotypes to populations across the world to determine parental source populations and admixture proportions. We found that the majority of Afrikaner ancestry (average 95.3%) came from European populations , but that almost all Afrikaners had admixture from non-Europeans. The non-European admixture originated mostly from people who were brought to South Africa as slaves and, to a lesser extent, from local Khoe-San groups. Furthermore, despite a potentially small founding population, there is no sign of a recent bottleneck in the Afrikaner compared to other European populations. Admixture amongst diverse groups from Europe and elsewhere during early colonial times might have counterbalanced the effects of a small founding population.While Afrikaners have an ancestry predominantly from northwestern Europe, non-European admixture signals are ubiquitous in the Afrikaner population. Interesting patterns and similarities could be observed between genealogical predictions and our genetic inferences. Afrikaners today have comparable inbreeding levels to current-day European populations. The seventeenth-century European colonization of the southern tip of Africa resulted in the influx of two groups of people, European colonists and slaves. The subsequent admixture between these external groups and the local southern African Khoe-San populations resulted in two admixed populations—the Afrikaner population and the Coloured population of South Africa   resulted from informal as well as formal associations . The chuTo understand the characteristics of the genetic contributions that slaves made, it is necessary to know from where and when they came to Cape Town and see that in the light of European male partner choices. Shell  claimed The “trekboere” were European farmers who followed a nomadic lifestyle in harsh conditions along the frontier. Informal unions with Khoe-San women were more frequent amongst the “trekboere”, but it is unclear if children from these relationships were absorbed into the Coloured and/or Afrikaner community , 32. PooBy using church records, genealogists calculated the contribution of non-Europeans to be between 5.5 and 7.2%  and specifically Europeans (K = 3 to K = 9) before receiving their own cluster at K = 10. From K = 7 onwards, northern and southern Europeans cluster separately, with Finnish forming one cluster (light blue) and southern Europeans (Tuscans and Iberians) the other cluster (light yellow). British (GBR) and Utah residents of northwestern European descent (CEU) appear midway between the Finnish and southern European clusters. Afrikaners contain significantly more northern European (blue) ancestry component compared to CEU and GBR . The specific percentage of cluster assignments of Afrikaner individuals at K = 6 and K = 9, and the population averages assigned to each cluster, are given in Additional file In the population structure analysis Fig.  46], Af, Af46], K = 6), where the major geographical ancestries are discernible, i.e. aboriginal southern African (Khoe-San), West/East African, European, East Asian, South Asian and Native American, the level of admixture from these ancestries can be distinguished in the Afrikaners  of which 2.1% are African ancestry and 2.7% Asian and Native American ancestry. The individual with the most non-European admixture had 24.9% non-European admixture, and only a single Afrikaner individual (out of 77) had no evidence of non-European admixture  are generally correlated to each other , additional inferences can be made regarding Japanese vs. Chinese ancestry, East vs. West African ancestry and northern vs. southern European ancestry  had the following ancestry fractions: 30.1% Khoe-San, 24% European, 10.5% East Asian, 19.7% South Asian, 15.6% West/East African and 0.2% Native American  Fig. .Fig. 3PZ scores (low Z scores indicate significant admixture), and Z scores are visualized in a figure to aid interpretation  betweenAlleles that are shared privately between combinations of the Afrikaner population with one comparative population  decay method (“SPECC1 gene associated with the top peak has strong expression in the testis and shows high similarity to a human sperm antigen gene (OMIM entry 608793). The gene associated with the second highest LSBL peak (STK39) has a role in the cellular stress response pathway and shows ubiquitous expression, with the most abundant expression in the brain and pancreas. The ERF gene associated with peak 3 is thought to belong to an oncogene family and play a role in embryonic development and cell proliferation.We scanned Afrikaner genomes for patterns of allele frequency variations compared to comparative European source populations (CEU and GBR), by doing a locus-specific branch length (LSBL) analysis. Regions where allele frequencies were differentiated compared to the CEU and GBR population were plotted in a genome-wide Manhattan plot  , their predicted lactase persistence phenotypic status, based on homozygote and heterozygote counts combined, is not significantly different .We also analysed the Afrikaner data for genome-wide signals of selection by scanning for regions with extended haplotype homozygosity compared to other haplotypes within the same population (iHS scans) and compared to haplotypes in a comparative population (XP-EHH scans). For XP-EHH scans, Afrikaners were compared to the CEU population. Additional file Runs of homozygosity were calculated for each individual of the dataset. Depending on their length, runs of homozygosity are informative of historic population size or recent inbreeding in populations . While wGenealogical records suggest that Afrikaners have their main ancestry components from Europeans  and estimate the non-European contributions to the Afrikaner to be between 5.5 and 7.2%  . Elphick and Shell  noted thWest/East Africans contributed an average of 0.8% of the Afrikaner ancestry , the estimated time of 9.3 (SD = 0.99) generations  is related to 299 founders 1101 times [The 77 individuals included in this study form part of parallel studies on non-paternity , 56 and 01 times . We can 01 times . For ins01 times . Hence, www.genotyping.se), using the Human Omni 5M SNP array. Results were analysed using the software GenomeStudio 2011.1, and the data were exported to Plink format and aligned to hg19.Samples were collected with Oragene® DNA Saliva collection kits  and whole genome DNA was extracted according to the manufacturer’s instructions. Final concentrations were adjusted to 50 ng/μl. Genotyping was performed by the SNP&SEQ Technology Platform in Uppsala, Sweden  the POPRES dataset , 49 and K) were tested. A total of 100 iterations of ADMIXTURE were run for each value of K, and the iterations were analysed using CLUMPP [K to identify common modes amongst replicates. Pairs of replicates yielding a symmetric coefficient G’ ≥ 0.9 were considered to belong to common modes. The most frequent common modes were selected and visualized with DISTRUCT [K = 2 to K = 15 due to the higher number of populations in the dataset.Population genetic analysis was conducted for the main merged dataset, containing 1747 individuals from 33 populations and 2,182,606 SNPs. We inferred admixture fractions  in orderg CLUMPP  for eachDISTRUCT . For thePCA was performed with EIGENSOFT  with theFormal f3 and f4 tests of admixture were done using the ADMIXTOOLS package . We did The date estimations were done using Malder v.1.0, ADMIXTOOLS package v.5.0 . The HapTo estimate genetic diversity and evidence of bottleneck effects in the Afrikaner population, we estimate runs of homozygosity (RoH) across the genome. RoH were calculated using PLINK , applyinThe above analyses were also repeated on Afrikaner data where the non-European admixed fragments were masked out of Afrikaner genomes. To identify the non-European genomic fragments, we inferred genome local ancestry for the Afrikaner individuals using RFMix version 1.5.4 . The folWe scanned Afrikaner genomes for genome local patterns of allele frequency variation by doing a locus-specific branch length (LSBL) analysis. LSBL values were calculated for the AFR compared to two European populations (CEU and GBR). The first pairwise Fst were calculated between the three populations in Plink v1.90b4.9. To then arrive at the LSBL value, the Fst between CEU and GBR was added to the Fst between AFR and GBR and the Fst between AFR and CEU was subtracted. This sum is then divided by two.To scan for signals of genome-wide selection in the Afrikaner group, integrated haplotype scores (iHS) and the cross population extended haplotype homozygosity (XP-EHH) were analysed using the R package REHH . The ancAdditional file 1: Figure S1. Non-European admixture fractions (of K=6) sorted by ancestry fraction. Figure S2. Principal component analysis for PC1-PC10 and the variation explained by PCs. Figure S3. Results from f3-test. Populations are colored according to regional affiliation. Figure S4. Results from f3-test. The CEU (A) and Khomani (B) populations are fixed to show the best African and non-African sources to the Afrikaner population. Figure S5. Fraction of shared private alleles between the Afrikaner population and a comparative population. Figure S6. Shared private alleles between the Afrikaner populations and populations with West-African ancestry. Figure S7. A) Afrikaner individuals (black circles) projected on a PCA based on European genetic variation from the POPRES dataset. B) Population variation on PC 1 and 2 summarized as averages and standard deviations. Figure S8. Admixture analyses of the Asian extended dataset. Figure S9. Manhattan plot of Locus specific branch length (LSBL) results. Figure S10. Manhattan plots of selection scan results. Figure S11. Runs of of Homozygosity (RoH) for European populations and the Afrikaner population. Table S1. Admixture fractions of the Afrikaner individuals at K=6 (ADMIXTURE). Table S2. Admixture fractions of the Afrikaner individuals at K=9 (ADMIXTURE). Table S3. f4 test to test specific sources of ancestry in the Afrikaner population. Table S4. Admixture LD decay estimate of admixture times into the Afrikaner population done in Malder. Table S5. Top 5 peaks detected with Locus Specific Branch Length scans . Table S6. Top 5 selection scan peaks detected with iHS and XP-EHH scans. Supplementary Text. This supplementary note discusses the populations from which the Afrikaner population arose, it summarizes genealogical information of admixture and presents genetic information of admixture. Figure S12. The population size of adult Afrikaner men (solid heavy line) and women (solid lighter line) as a function of time. Figure S13. The origins of slaves arriving in the Cape. Table S7. Four estimates from three studies of the percentage composition of Afrikaners.


Brontispa longissima (Gestro), is a widely distributed pest in Southern China. Here, we used restriction site-associated DNA (RAD) genotyping to assess the invasion pathway by detecting and estimating the degree of genetic differentiation among 51 B. longissima accessions collected from Southern China. A total of 10,127 SNPs were obtained, the screened single nucleotide polymorphism (SNP) information was used to construct the phylogenetic tree, FST analysis, principal component analysis, and population structure analysis. Genetic structure analysis was used to infer the population structure; the result showed that all accessions were divided into Hainan population and non-Hainan population. The Hainan population remained stable, only the Sansha population differentiated, and the non-Hainan populations have gradually differentiated into smaller sub-populations. We concluded that there are two sources of invasion of B. longissima into mainland China: Taiwan and Hainan. With the increase of the invasion time, the Hainan population was relatively stable, and the Taiwan population was differentiated into three sub-populations. Based on the unrooted phylogenetic tree, we infer that Taiwan and Hainan are the two invasive base points. The Taiwan population invaded Fujian, Guangdong, and Guangxi, while the Hainan population invaded Yunnan and Sansha. Our results provide strong evidence for the utility of RAD sequencing (RAD-seq) in population genetics studies, and our generated SNP resource could provide a valuable tool for population genomics studies of B. longissima in the future.To determine population genomic structure through high-throughput sequencing techniques has revolutionized research on non-model organisms. The coconut leaf beetle,  Brontispa longissima (Gestro) (Coleoptera: Chrysomelidae), is a serious pest of the coconut palm Cocos nucifera (L.) and other palm trees [longissima was first described as Oxycephala longissima by Gestro(1885), collected from the Aru Islands, which are located in the Arafura Sea between New Guinea Island and Australia, and then was transferred to the genus Brontispa by Gestro (1907) [B. longissima represents two monophyletic clades, using mitochondrial DNA analysis and crosses between the two nominal species. One named Pacific clade is distributed in a relatively limited area , whereas the other named Asian clade covers a wide area, including Asia  and the French Polynesia, New Caledonia, and Vanuatu [B. longissima are found in young folded leaflets of palms, where they feed on the soft leaf tissues [B. longissima are mainly accomplished via chemical and biological control [B. longissima.The coconut leaf beetle, lm trees . The speby Gestro885, collo 1907) . The beeo (1907) . Shun-Ic Vanuatu . Since t Vanuatu ,4. In 19 Vanuatu . Larvae  . The be tissues ,7,8. At B. longissima, with few studies that focused on molecular genetics. To date, the use of gene markers to analyze genetic diversity and the genetic structure of B. longissima has not been reported. Population genetics research is based on a relatively wide range of distribution [B. longissima have been limited to mitochondrial DNA, restriction fragment length polymorphism (RFLP) [Related studies on population genetic structure and genetic diversity identified genetic evolution and gene connectivity between different populations of pest, which has important theoretical and practical significance for comprehensive management ,11,12. Pribution . The samribution . Thereforibution . To datem (RFLP) , and micm (RFLP) .B. longissima populations could be useful for the control of coleopterans in other regions of the world.The advent of next-generation sequencing (NGS) has facilitated the identification of novel population genetic markers on an unprecedented scale, even in non-model organisms . RestricB. longissima populations using RAD sequencing and SNP markers. The results of this study have important implications for understanding the genetic diversity of B. longissima populations and could be used to guide the integrated control of the beetle.In this study, we aimed to elucidate the genetic structure of B. longissima specimens were collected from May 2016 to August 2017. The sampling range was mainly in Southern China, including the Fujian (FJ), Guangdong (GD), Guangxi (GX), Yunnan (YN), Hainan (HN), Sansha (SS), and Taiwan (TW) regions, as shown in C. nucifera. Detailed descriptions with the original locations of specimen collection are provided in EcoRI (New England Biolabs) was used to digest the genome followed by heat inactivation of the enzyme. The EcoRI-cut site of each sample was ligated with barcoded P1 adapters (complementing the EcoRI-cut DNA gap). These adapters contained forward amplification and Illumina sequencing primer sites, as well as a nucleotide barcode 4- or 8-bp long for sample identification. The adapter-ligated fragments were subsequently pooled, randomly sheared, and size-selected. DNA was then ligated to a second adapter (P2), a Y adapter [RAD-seq libraries were constructed following a modified protocol . Genomic adapter  that hasRaw reads of RAD-seq Illumina sequencing were processed using the Stacks pipeline ,22. QualB. longissima was available.The final SNPs obtained underwent strict filtering and screening. We selected only SNPs matching the following criteria: (1) At least 20 accessions contained the locus in which the SNP was located, (2) the) was 0.01, (3) the minimum depth of the gene locus in which the SNP was located was 7, and (4) if all samples had a deletion rate of more than 10% at a site, the site was removed. The Stacks denovo_map.pl was implemented to identify candidate SNP markers for downstream analyses, as no reference genome for B. longissima using Structure 2.3.4 [http://taylor0.biology.ucla.edu/structureHarvester/). Based on the K value that we have selected, pairwise FST values were estimated in Arlequin v.3.5 [Based on the candidate SNPs, we inferred the population structure of re 2.3.4 ,25,26,27in v.3.5 ,29.PCA was performed by using PLINK ,31, withThe phylogenetic tree is a branch map or tree that describes the order of evolution between groups, indicating the evolutionary relationship between groups . The theA genome scan of the 61,182 SNPs retained using ARLEQUIN  revealedB. longissima  on a reduced-representation genome scale (STF = 0.141). Our result is similar to the genetic differentiation on population structure  showed that B. longissima represents two monophyletic clades, using mitochondrial DNA analysis, and crosses between the two nominal species. One named Pacific clade is distributed in a relatively limited area, whereas the other named Asian clade covers a wide area, including Asia and the French Polynesia, New Caledonia, and Vanuatu [B. longissima Asian clade appeared in New Caledonia and Vanuatu [o et al. 011 showe Vanuatu ,39. Howe Vanuatu , Tahiti  Vanuatu , Taiwan  Vanuatu , Japan [ Vanuatu , the Ind Vanuatu , and HaiB. longissima has high risk and great harm. The results showed that most effective measures for comprehensive treatment of B. longissima are to strengthen the quarantine work during the transport of B. longissima host seedlings to prevent their spread, and then use chemical agents [As an invading pest, l agents  or parasl agents  to kill B. longissima SNP genetic markers. In our strict filtering and screening, 10,127 SNPs out of 61,182 markers were identified. Based on these SNPs, phylogenetic tree analysis, principal component analysis (PCA), and population structure analysis were used to analyze the evolutionary relationship among different B. longissima populations. The results showed that the B. longissima in China can be divided into Hainan B. longissima population and non-Hainan B. longissima population. The Hainan B. longissima population was relatively stable. The non-Hainan B. longissima population was divided into several subgroups. Based on the unrooted phylogenetic tree, we inferred that Taiwan and Hainan B. longissima populations evolved as two invasion hubs. The Taiwan B. longissima population invaded Fujian, Guangdong, and Guangxi, while the Hainan B. longissima population invaded Yunnan and Sansha. However, due to the invasion in China, the time is short, less than 40 years, thus a genetic differentiation is not obvious enough.In this study, the RAD sequencing technology was used for the development of


Pinus armandii, a Chinese endemic coniferous tree species, that has been mass planted across its native range. Population genetic analyses showed that natural populations of P. armandii comprised three lineages that diverged around the late Miocene, during a period of massive uplifts of the Hengduan Mountains, and intensification of Asian Summer Monsoon. Only limited gene flow was detected between lineages, indicating that each largely maintained is genetic integrity. Moreover, most or all planted populations were found to have been sourced within the same region, minimizing disruption of large‐scale spatial genetic structure within P. armandii. This might be because each of the three lineages had a distinct climatic niche, according to ecological niche modeling and niche divergence tests. The current study provides empirical genetic and ecological evidence for the site‐species matching principle in forestry and will be useful to manage restoration efforts by identifying suitable areas and climates for introducing and planting new forests. Our results also highlight the urgent need to evaluate the genetic impacts of large‐scale afforestation in other native tree species.Many natural systems are subject to profound and persistent anthropogenic influence. Human‐induced gene movement through afforestation and the selective transportation of genotypes might enhance the potential for intraspecific hybridization, which could lead to outbreeding depression. However, the evolutionary legacy of afforestation on the spatial genetic structure of forest tree species has barely been investigated. To do this properly, the effects of anthropogenic and natural processes must be examined simultaneously. A multidisciplinary approach, integrating phylogeography, population genetics, species distribution modeling, and niche divergence would permit evaluation of potential anthropogenic impacts, such as mass planting near‐native material. Here, these approaches were applied to  The genetic variation and structure of ls Table . Forwardls Table , one chlii Table . Additioi et al. . Therefo2.2All DNA sequences were visually inspected, edited, and aligned using MEGA v6   between the three identified regional groups. To assess patterns of recent migration, we also estimated interpopulation migration rates (within 2–3 generations) using a Bayesian approach in BAYESASS v3.0  was performed in DIYABC v2.04  were obtained from our field observations, literature  and the National Specimen Information Infrastructure . In total, 284 georeferenced points were obtained  analyses were performed with MAXENT v3.3.3k   were retained for subsequent analysis (Table Nineteen bioclimatic variables were acquired at 2.5 arc‐minute resolutions from WorldClim (is Table .2.7P. armandii were compared in both geographic (G) and the environmental (E) spaces, because these two types of niche space have been shown to complement each other in niche comparison studies  space and using MAXENT with default settings. We limited our model extent to the distributional range of each regional lineage of P. armandii with a 200 km buffered zone, to eliminate the impact of background geographic area of the models on modeling results  space using R packages , South Hengduan Mountains (SH), and Qinling‐Daba Mountains (QD), respectively; hence, these three regions were clearly defined as distinct by chlorotype data  material only, unless stated otherwise.3.2nad5 intron 1 and nad7 intron 1 comprised 1412 bp, and from this, four mitotypes were distinguished. The geographic distribution of these was highly structured, with M1, M2, M3, and M4 unique to QD, EH, east SH, and west SH, respectively  (Table AGP6 and LFY) and microsatellite variation mainly occurred within populations . According to microsatellite data, FST values between all three pairs of regions were highly significant (p < .001), with although EH was less differentiated from SH (0.17) than either was from QD .The AMOVAs revealed that 88.90% of overall cpDNA variation was between regions  Table . Accordi0) Table . ConversAGP6 and LFY genes), ΔK indicated that the optimal value for K was 2  from SH (7‐20)  Figure . Additio3 Figure a, d. All3 Figure , S5, S6.3.4P. armandii populations was high (HT = 0.614), whereas the same measure within each region was lower   and nucleotide diversity (π) values for AGP6 and LFY among wild populations were higher than those for planted populations  Table . For plaly Table . Meanwhins Table .P. armandii (Table HE) and observed heterozygosity (HO) of the wild populations were 0.573 and 0.444, respectively. Interestingly, wild populations exhibited higher genetic diversity than the planted populations for each of four measures: effective allele number, expected heterozygosity, observed heterozygosity, and Shannon’s Information Index. The Kruskal–Wallis tests did not detect a significant difference in genetic variation between planted and wild populations  and from SH to QD (m = 0.021) (Table Nm) between all three regions, with the greatest Nm between QD and SH  Table . Additio3.65, 1.08 × 106, and 1.32 × 106, respectively, whereas NA was 9.78 × 104 .In the DIYABC analysis, the posterior probability for scenario 3 (with 95% CI) was 0.964 (95% CI: 0.955‐0.972), much higher than for scenarios 1 , 2 , or 4 . The median values of the effective population sizes of EH, SH, and QD were 3.60 × 105 generations or 4.83 Ma ago and then expanded 6.51 × 104 generations or 1.63 Ma ago. Both happened slightly earlier in SH, with contraction 2.14 × 105 generations or 5.35 Ma ago, then expansion 7.93 × 104 generations or 1.98 Ma ago. QD material best fitted a continuous expansion model, with probability 0.448 (95% CI: 0.398‐0.498)  and 0.447 (95% CI: 0.431–0.463), respectively. EH material contracted 1.93 × 10) Figure .3.7P. armandii and outgroup species . Within P. armandii, the three regional lineages EH, SH, and QD each formed strongly supported clades, and the first divergence was that of QD around the Tortonian period 9.0 Ma (95% HPD: 4.0–14.5), with divergence between EH and SH occurring later, 6.7 Ma (95% HPD: 2.8–12.0).A molecular phylogenetic tree was constructed using completed chloroplast genome sequences from the three lineages within s Figure . The div3.8P. armandii generated with MAXENT was fairly congruent with the current distribution of the species   Figure . HoweverD = 0.149), whereas niche overlap between EH and QD was the lowest (D = 0.086)  Figure . The pro) Figure .4Pinus armandii within its native range, in China, using large‐scale population genetics and phylogenomic analysis. We identified three intraspecific lineages, each occupying distinct ecological niches   Figure , which m) Figure .Taxus wallichiana . The fact that a moderately cold climate has prevailed on the QTP before the LIG will have provided opportunities for each of the three lineages to have continued its range expansion throughout the LIG, as previously proved in Picea likiangensis . Moreover, markers must be developed that detect within‐region geographic structure, through which introgression from elsewhere within the region, via material planted away from its source, can be detected.Lower levels of diversity in planted than wild accessions Tables , and S8 4.3P. armandii, earlier transplant experiments revealed strong local adaptation apparently driven by regional differences in mean annual temperature and extreme minimum temperature , giving rise to a site‐species matching principle. Within re Tang, , leadingre Tang, . The curre Tang,  and distre Tang, .D = 0.103, I = 0.286) and QD   being planted within the range of another (QB), leading to the dieback of trees in winter frost  Table  based on1) Table a. Despit1) Table . The connces Ma, , 1992, lrost Ma, . To avoi4.4P. armandii, is more likely to be failure of plantations due to maladaptation. Earlier work provides examples of this: Southern material could barely survive northern winters, whereas northern material grew very slowly in the south (Ma, P. armandii so far, shifts in potential distribution ranges due to future climate change in P. armandii (Zheng, Gao, & Zhang, To date, there has been little emphasis on assessing the genetic legacy of a widespread afforestation program, despite growing investment in large global afforestation projects (Payn et al., outh Ma, , 1992. AIntraspecific genetic variation is essential for species adaptation and survival and can have profound effects on ecological processes, across communities and even ecosystems (Hughes, Inouye, Johnson, Underwood, & Vellend, Z‐HL and JL conceived the study. YJ and JZ performed the experiments. Z‐HL, YJ, JZ, L‐MG, G‐FZ, and G‐FZ contributed materials and analysis tools. Z‐HL, JL, R‐IM, and YJ wrote the manuscript. Z‐HL, JL, R‐IM, and YJ revised the manuscript. All authors approved the final version of the manuscript.Supplementary MaterialClick here for additional data file.


Welwitschia mirabilis is one of the most extraordinary plant species on earth. With a fossil record of 112 My and phylogenetically isolated within the order Gnetales, the monotypic genus Welwitschia has survived only in the northern Namib Desert in Angola and Namibia. Despite its iconic role, the biogeography, ecological niche, and evolutionary history of the species remain poorly understood. Here we present the first comprehensive map of the strongly disjunct species range, and we explore the genetic relationships among all range fragments based on six SSR markers. We also assess the variation of the environmental niche and habitat preference. Our results confirm genetic divergence, which is consistent with the hypothetical existence of two subspecies within Welwitschia. We identify an efficient geographical barrier separating two gene pools at 18.7°S in northern Namibia. We also identify further diversification within each of the two subspecies, with several different gene pools in ten isolated range fragments. Given the presence of well-isolated populations with unique gene pools and the association with different bioclimatic variables, rock types, and habitats within arid river catchments, we can hypothesize that the present intraspecific diversity may have evolved at least in part within the present refuge of the northern Namib Desert. Welwitschia mirabilis make it one of the most extraordinary plant species on Earth. With a fossil record of 112 My and phylogenetically isolated within the order Gnetales, the genus Welwitschia is appropriately called a “living fossil.” Shortly after the discovery of Welwitschia by the Austrian botanist Friedrich Welwitsch, Hooker1 recognized similarities to conifers and proposed placing the new genus next to Gnetum L and Ephedra L. The most recent reviews based on matK and rbcL gene sequences validate Hooker’s proposal by revealing Gnetum as the closest relative of Welwitschia and Ephedra as sister to both2. The Gnetales are an extremely heterogeneous taxonomic group with an isolated phylogenetic position among seed plants. Relatives are known only from fossil records, mainly of Aptian age and scattered around the world 3. Numerous Welwitschiaceae with close similarities to the present-day Welwitschia morphology occurred in northeast Brazil during the Aptian–Albian3 and were still connected to Africa4. These Welwitschiaceae coexisted with a diverse flora with no explicit xerophytic character and even including aquatic species3. The fossil record does not indicate whether major adaptations evolved while Welwitschia was limited in distribution to the Namib region, probably during the cooling and aridification of the Tertiary and Quaternary6. The phylogenetic age and isolation, the diversity of extinct relatives, and the huge biogeographical space allow us to regard the extant Welwitschia as a living fossil.The phylogeny, morphology, and ecology of 7 recognized two subspecies of W. mirabilis ssp. namibiana from Namibia and the typical ssp. mirabilis from Angola. Leuenberger observed morphological differences in the male strobili  and allopatric distribution of greenhouse plants of the dioecious species cultivated under identical conditions. Jacobson et al.8 questioned the validity of the two subspecies but studied only populations belonging to the Namibian subspecies. Therefore, their results neither support nor reject Leuenberger’s proposal.Leuenberger9 used random amplified polymorphic DNA markers (RAPD) to explore smaller-scale genetic diversity among populations in the central Namib Desert in Namibia and in one population from near Khorixas. The evidently minimal gene flow between populations separated by as little as 18 km implies limited transport of the pollen and seeds. This view is supported by Wetschnig and Depisch10, who reported mainly insect pollination and almost no longer-distance transport by wind.Jacobson and LesterWelwitschia started almost simultaneously in Angola and Namibia. In Angola, Friedrich Welwitsch found the first plants on 3 September 1859 at the type locality on the coastal plateau near Cabo Negro , 15 km NE of Tombua1. On 5 May 1861, the artist Thomas Baines found Welwitschia in Namibia in a dry riverbed near Heigamkab . In Kew in 1863, Joseph Dalton Hooker inspected material from both collectors and published Welwitschia mirabilis, based on the type specimen from Angola1.Exploration of the geographical range of 11 visited sites in Namibia and published all records of that time. The southernmost record was reported from 23.6°S near Homeb. For Angola, Kers based the map records on Taborda de Morais12, who mentioned a population 8 km NE of the Rio de Sao Nicolau (= Rio Bentiaba), which is at 14.26°S. Jacobson et al.8 reported a N limit south of the Bentiaba River, while Henschel et al.13 reported 14.9°S, which is close to Moçâmedes (Namibé) at the latitude of Moscas Bay/Baba. Kers11 interpreted the biogeography as disjunct: “Most of the localities are so clearly separated from each other geographically that it is not even possible to imagine a gene exchange between them.” Giess14 published a few additional locations.Subsequently, many authors reported new locations. In 1967, KersWelwitschia is presently confined to the northern part of the Namib Desert, which had an arid to semiarid climate during the whole Quaternary and most of the Tertiary15. Jacobson and Lester9 proposed that Welwitschia may have established the present range more than 105 My ago.In summary, Welwitschia mirabilis has a long life expectancy17 and a highly unusual morphology. The stem diameter often surpasses 150 cm, but the stem height rarely surpasses 30 cm.1 and, more recently, Cooper-Driver18 have already described the root morphology. The stem shows a continuous transition into a broad taproot that rapidly gets thinner with depth within the first meter. Further away from the stem, one to four smaller roots of only 1–3 cm diameter typically spread horizontally but also exploit deeper soil layers. Kutschera et al.19 found roots with horizontal lengths of 15 m. After germination, young plants rapidly develop a taproot. Several authors20 have interpreted Welwitschia as a phreatophyte based on the preferred habitat adjacent to drainage lines and the pronounced taproot formation. However, Bornman21 reported that roots near the Brandberg do not extend deeper than 3 m.Hooker13 details the root architecture and water uptake of plants near the Swakop River. No roots deeper than 140 cm were observed, and the majority exploited rainwater within a gypsum crust and deeper petrocalcitic horizons. Only a small percentage showed upward growth, indicating uptake of a smaller amount of topsoil water. The same study presents evidence based on stable isotope analysis for a preferential water origin from continental water sources (= rare summer thunderstorms). Atlantic sources (= fog or winter rains) and water from gypsum crusts were much less relevant. Similarly, a study at Gobabeb22 did not show an influence of fog on leaf growth rate or germination.A recent studyWelwitschia. It is remarkable that beyond the foci of the aforementioned studies and around 300 other publications22, there has been no attempt to capture the environmental niche of Welwitschia within the whole range . Therefore, our objectives are to (1) investigate genetic differentiation among the sample records from all range fragments in Angola and Namibia to determine whether they support the existence of two subspecies; (2) examine environmental differences among the geographic fragments; and (3) discuss the results that most obviously characterize the ecological niche of Welwitschia.Based on current knowledge of the range and phylogenetic position, we seek to establish a new and complete biogeographical record. Additionally, we explore the genetic similarities among seventeen range-wide populations using the first developed SSR markers for Welwitschia . The broadest section in a W–E direction connects populations located just west of Khorixas at -20.35° latitude to populations east of Torra Bay, 149 km further west. With the newly found locations, the area of distribution of the genus almost doubles in Angola. New northernmost, southernmost, and easternmost records have been made as well as new populations closer to the Atlantic coast than previously recorded. We found a new northernmost record in Angola, north of Fael at -14.12° latitude. Similarly, the southernmost record could be extended slightly to -23.63° latitude.Our systematic mapping results allow for drawing a new map of the range of hia Fig. . A totalThe new northernmost record is nearest to the coast, 4.8 km inland from the beach at Fael. From N to S, the other large range fragments have the following minimum distances to the coast: 11.1 km , 12.6 km (Iona), 13.0 km , 8.5 km , 29.9 km (Khan–Swakop), 53.0 km (Kuiseb).Welwitschia population farthest from the Atlantic coast (149 km) is situated just W of Khorixas at -20.39 latitude. This is also the most humid site at just over 200 mm mean annual precipitation (MAP), compared to the majority of populations at less than 100 mm MAP.The Welwitschia is strongly fragmented into spatially isolated, disjunct partial ranges in a linear spatial arrangement from north to south along the hyperarid to arid Namib Desert. In this article, we distinguish 10 isolated (disjunct) “range fragments” using a 20-km distance threshold for assumed isolation, given the limited pollen transport of Diptera and Hymenoptera10 and the reported lack of gene flow9. The range fragments are presented in Fig. The biogeographical range of 2 we often counted more than 200 plants: for example, in plot 36,317  in the northern part of Iona NP we found 212 individuals, while in plot 31,555  in the Khan–Swakop range fragment we found only six individuals.In both countries, we found aggregates of two large range fragments separated by gaps smaller than 30 km; the two in Angola (Tombua–Virei and Iona) are 309 km from the two in Namibia (Etendeka and Messum). In the space between them and in the extreme north and south of the whole range are additional small range fragments. The aggregate of the two Namibian range fragments, Etendeka and Messum, is larger in area, while the two Angolan range fragments, Tombua–Virei and Iona, contain the largest number of individual plants. The high number of individuals strongly correlates to the very high plant density in Tombua–Virei and Iona. In our standard plots of 1000 mWelwitschia are viable within an arid niche defined by a MAP of less than 200 mm; many fragments in parts receive less than 100 mm, and the more southern range fragments less than 50 mm : Zygophyllum stapffii, Zygophyllum simplex, Arthraerua leubnitziae, Calicorema capitata, Petalidium variabile, Adenolobus pechuellii, and Commiphora wildii25. In contrast, Welwitschia mirabilis is obviously outcompeted by Acacia reficiens, Acacia mellifera, Acacia tortilis, Colophospermum mopane, and sometimes Salvadora persica, as can be deduced from the immediate disappearance of Welwitschia at the margin of stands of these woody species—for example, when approaching Virei or Khorixas from the west. In contrast, among the more frequently disturbed vegetation of larger dry riverbeds, these species and Welwitschia mirabilis sometimes coexist, with old individuals growing next to each other, as in the case of the famous “giant Welwitschia” individuals in Angola at Flamingo River and Giant Welwitschia South.Concerning neighboring vegetation, p < 0.001) confirms the visually observed separation of the fragments with particular overlap between the two groups. Finally, we conducted a Kruskal–Wallis test and Nemenyi post hoc test to analyze the differences among the range fragments in each environmental parameter  of 16 scaled bioclimatic variables from the WorldClim dataset and a set of 16 lithological units extracted from digitized geological maps of Angola and Namibia. The first two axes of the PCA already explain approximately 81.8% of the variation within the data set Fig. . The obser Table . The oveWelwitschia with six SSR markers.We used samples from 17 populations  among most of the populations. Only populations 10 and 12 (p < 0.33) were not significantly different (Supplementary Tables S1 and S2).At the largest spatial scale Fig. b, PCoAs Welwitschia into two clearly separated and almost pure gene pools  in a PERMANOVA comparison (Supplementary Tables S1 and S3).Most of the individuals of population 2 are assigned to the same gene pool Fig. c, yellowp < 0.05) in a pairwise comparison of the PERMANOVA test (Supplementary Tables S1 and S4). The structure analysis of the southern subgroup revealed a best K of four different gene pools. These are presented in Fig. The PCoA patterns of the southern taxon populations are shown in Fig. Welwitschia mirabilis has developed considerable genetic diversity within the refuge. Our results support the existence of two well-separated taxa within Welwitschia, located in both the northern and southern parts of the total range, as proposed by7. The gene-flow barrier is located in Namibia at 18.7°S between the Ougams and Ganias range fragments. The structure analysis  and south (Etendeka and Messum). It is possible that these major gene pools in the past were the only to survive and later expanded equally into the intermediate space. Further research is needed to explain this biogeographical boundary with regards to Welwitschia and other taxa.However, the location of the discontinuity coincides with an important biogeographical limitation, namely the southern boundary of the Kaokoveld desert ecoregionWelwitschia mirabilis, with ssp. namibiana occurring in Namibia south of 18.7° and the typical ssp. mirabilis found in Angola and the northwestern part of Namibia north of 18.7°.Although these data clearly show geographic isolation, at present there is no evidence of reproductive isolation. Therefore, the two taxa are correctly regarded as subspecies of We found further genetic diversity within each of the two subspecies. The structure analyses identified up to three gene pools for individuals from both subspecies in the large central range fragments Fig. c,d. In c3, the present range of Welwitschia mirabilis is limited to the northern part of the Namib Desert. The range is climatically defined by precipitation in the summer months, with a MAP of 20–200 mm. The highest aridity is found in the southernmost parts of the range. The western half of the range receives additional moisture in the form of fog, which increases in amount, frequency, and salinity toward the coast.Compared to the almost global distribution of Welwitschiaceae during the AptianWelwitschia is unable to compete with woody arid savanna plants, especially Acacia reficiens, Acacia mellifera, Acacia tortilis, Colophospermum mopane, and Salvadora persica. Mixed stands of these woody plants are only found in arid river environments, which offer a local mixture of more or less arid sites depending on the history of floods, sedimentation, and terrace erosion. Rarely, a smaller-scale mosaic of moister and drier habitats allows an interdigitation of Welwitschia mirabilis stands, woody acacias, and Colophospermum trees at the 10–100 m scale, as for example in the western part of Virei and Khorixas. In contrast, Welwitschia is able to share habitats with woody species of Commiphora, Calicorema capitata, Zygophyllum stapffii, Arthraerua leubnitziae, and perennial grasses.The absolute moisture limit is clearly associated with the presence of arid savanna vegetation. The aridity limit is less clearly defined and will depend on coastal factors such as fog, salinity, wind speed, sand blasting, and cooler temperatures. In several range fragments  the aridity limit toward the coast is defined by the extent of inland gravel sediments in the coastal area.Fields of sand dunes south of the Kuiseb River and near the coast between Torra Bay and Tombua also form an important limitation.Welwitschia encompassing a broad, uninterrupted band from the Kuiseb to central Angola.However, the general climatic niche of 20–200 mm MAP does not explain the disjunct range of The PCA of 19 scaled bioclimatic variables and geological units clearly separates the Angolan and Namibian range fragments. But in addition, the different Angolan range fragments are well separated from each other, while in Namibia the Khan–Swakop and Kuiseb subunits differ to some degree from the rest of the Namibian subunits. However, the rest of the Namibian range fragments are quite similar in their bioclimatic parameters.W. m. ssp. namibiana share a strong though not obligate affinity to Etendeka basalts . In contrast, other range fragments of Welwitschia are located on markedly different rock types, including granite, gneiss, mica schist, limestone, and sandstone. In some cases  the presence of Welwitschia fades out within a geological unit.In some range fragments, the lithology defines sharp boundaries. For example, the sharp boundary at the western edge of the Etendeka range fragment is clearly defined by the western boundary of Etendeka basalt. In fact, all the northern range fragments of Welwitschia range fragments. Such small drainage channels attract runoff water and increased infiltration of water during rare rainfall events and allow the soil to retain water within and under its calcrete (and sometimes gypcrete) horizons13 during periods without rainfall. After rainfall, small drainage channels especially seem to provide the level of soil moisture preferred by Welwitschia mirabilis in the vadose zone. Some of the smaller range fragments and their subunits  could reasonably be understood as interconnected catchment systems. Similarly, the western boundary toward the coast of many range fragments  is defined by the extent to which inland gravel sediments in catchments or sheetwash plains spread over the coastal area. In some places, especially in the north , rocky plains with shallow leptosols, often combined with calcrete, are the dominant habitat.The habitat preference of alluvial soils in or adjacent to small dry riverbeds and/or terraces bordering larger dry riverbeds seems to be a unifying factor for many, if not all, Welwitschia within the refuge could have evolved there through adaptation to different landscapes. An alternative hypothesis is that the present genetic diversity already existed when Welwitschia disappeared elsewhere and became limited to the northern Namib Desert.The data and observations presented here allow the following hypothesis: the observed diversity of 8. This relatively low level of diversification could support the hypothesis that only one common ancestor settled the refuge and has since diversified at a slow rate. We did not sample morphological data during our one-off field visits because the extremely variable environmental conditions  strongly determined the conditions of the relevant morphological features.The present diversity is minimal. Though the diversification of gene pools is clearly visible at the molecular level, it is hard to distinguish even the two subspecies morphologically in the field, whereas cultivation under identical conditions did allow us to distinguish the two subspeciesWelwitschia plants cannot compete with more modern woody arid-adapted savanna plants, in slightly moister habitats. However, throughout the range, Welwitschia plants are able to inhabit the above described niche near dry riverbeds and, especially, small drainage channels that form part of larger catchment systems. Perhaps their potentially very long lifespan is essential and enables Welwitschia plants to outcompete other species that establish themselves only during cycles of moist years.Welwitschia populations within the different arid catchments could have evolved adaptations to locally abundant rock types or other habitat conditions, including fog and water storage in gypcretes, for example. After the development of a major gene-flow barrier between the two subspecies, both were able to maintain large core areas, while satellite populations in suitable catchments north and south of the core area could survive and develop individual gene pools. In conclusion, our data and observations allow us to interpret Welwitschia mirabilis as a paleoendemic species surviving in an arid refuge where it further adapted to environmental conditions in disjunct range fragments.The preceding hypothesis, derived from investigating genetic divergence according to six SSR markers from all range fragments and niche divergence according to numerous environmental variables, should be tested by other research methods. Analyzing additional chloroplast or nuclear markers would be necessary to confirm our SSR results and should receive highest priority. Similarly, a somewhat higher spatial resolution would be required to better understand the genetic diversity within the largest range fragments. The integration of bioclimatic and geological variables presented here should be expanded to include potentially important variables related to fog, soil properties, small-scale habitat features such as gradients next to small riverbeds, and other species within the relevant plant communities. Utilizing these gradients to better quantify the ecological niche of the subspecies would be a necessity to further support the subspecies hypothesis.Welwitschia younger than 112 My will give us a more holistic understanding of how this important “living fossil” evolved.Perhaps the future discovery of fossil sites containing relatives of Welwitschia was or was not recorded. The field work was accompanied by targeted efforts to find potential Welwitschia populations using all available historical and recent information from collections, museums, literature27, and local people. Records with only broad geographical information were scrutinized during additional field visits. In addition, high-resolution aerial photographs were used to assess the presence of Welwitschia in inaccessible regions, especially in Angola28, and our own UAV pictures allowed inspection of inaccessible places. At each site, we also recorded all accompanying vegetation within 1000 m2, took soil samples, and noted additional environmental parameters.In the first author’s project, “Vegetation of the Namib Desert,” a systematic assessment from near Benguela (-12.5°S) to the southern margin of the Knersvlakte (-32°S) allowed us to distinguish among locations where 30 provided by Geological Services. We assembled the bioclimatic data from the WorldClim V2.124 data set with a resolution of 1 km2 per grid cell. These data describe 19 different bioclimatic variables, such as mean annual temperature (BIO1), temperature range (BIO7), and mean annual precipitation (BIO12). For a description of the variables, please refer to https://www.worldclim.org/data/bioclim.html. We extracted bioclimate data for all observations of Welwitschia in our database. The parameters BIO14, BIO17, and BIO19 indicate precipitation in the driest or coldest month or quarter. These were constantly zero or had zero variation and were removed in further analysis. For each parameter, we checked for differences between the medians of the ranked bioclimate values for the range fragments using a Kruskal–Wallis test. This nonparametric procedure was necessary because there were strong differences in the number of samples per fragment. We added a Nemenyi post hoc test to identify significant differences among the single-range fragments. To better understand the relationships among the range fragments and with regards to climate and lithology, we additionally conducted a PCA of the dataset. PCA is an eigenvalue-based data-dimension reduction technique that finds major orthogonal gradients in the data and reduces this pattern to so-called principal components or principal axes. The result is then visualized with a bi-plot in which the variables and samples are interpreted relative to their positions on the first two or three principal axes. The data were standardized and analyzed with a correlation instead of a variance–covariance matrix. Finally, we ran a nonparametric multivariate group test to check for the strength of separation between the clusters. We used the ANOSIM procedure, which analyzes differences among the ranks of group centroids for a multivariate data set and effectively measures the overlap among the different clusters. The analysis generates R-statistics and a p-value based on 999 permutations. Values below 0.5 indicate strong overlap among clusters, values below 0.75 indicate some overlap, and values above 0.75 indicate little to no overlap among the different multivariate groups. All analyses were run in R31, with the packages asbio32, PMCMR33, FactoMineR34, and vegan35.To better understand the ecology of the fragments, we analyzed their position along the large-scale climate gradient between arid Namibia and southwestern Angola, and we considered the importance of lithology, which might have large-scale consequences for the occurrence pattern. We compiled lithological units from the most recent digital geological maps of Angola and Namibia2 were taken from still-green leaf areas at the outer margin of the living leaf to avoid unnecessary damage. Samples were dried with silica gel in plastic bags. Tissues were taken from 331 individuals, which formed part of 31 sampling areas in 17 populations n, (AT)n, (AC)n, and (CG)n were chosen as SSR motives, and the minimum of n repeats was set to four. Out of 157 identified SSR motives, 16 ESTs were chosen to create SSR markers. Using Primer3 Version 1.1.4.38, primers were designed in front of and behind the microsatellite motif to create PCR products between 100 and 350 bp. Six out of 16 primer pairs produced distinct, reproducible, and polymorphic PCR products  according to the manufacturer’s instruction and finally adjusted to 20 ng/µL.All 6.214 W40 with modifications to the 3500 Genetic Analyzer . All forward primers were labeled either with 6-FAM or HEX . For dominant marker analyses, PCR products of the same SSR locus with the same sizes were considered as homologue alleles and coded as “1”; and no PCR products of the same size were coded as “0” in a 1/0 matrix. Questionable sites were treated as missing data and marked with a question mark. Peak shifts in sizes of less than 1 bp were adjusted to the respective allele size manually. For further analyses, all six SSR markers were combined in one 1/0 matrix. Based on first results, the data matrix with all 17 populations was split into two partial matrices: 1) all northern populations of Angola plus the northernmost Namibian populations (populations 1–5), and 2) the remaining Namibian populations (populations 6–17).42. The algorithm for this metric multidimensional scaling was based on Davis43. The PCoAs were estimated using the Sørensen–Dice44 coefficient and a transformation exponent of c = 2. Missing data were deleted pairwise and omitted from calculation41. The two dimensions with the highest value in an n-dimensional room were chosen to explain the distribution of the genetic characters in a two-dimensional scatterplot. Significant differences among populations of Welwitschia were identified by a one-way PERMANOVA45 with 9,999 permutations in PAST42. The Bonferroni-corrected p-values are shown in Supplementary Tables 1–4.PCoAs were run with the combined and two partial 1/0 matrices in PAST V 3.23Welwitschia, a codominant data matrix was created with allele sizes of each SSR locus coded in base pairs (bp). The complete data matrix was divided into two data matrices as described earlier. For all three SSR data matrices, Bayesian structure analyses were estimated with the program structure 2.3.448. To ensure an unbiased best-K estimate of the Welwitschia metapopulation, we analyzed all evolution model algorithms offered by the program structure with 30,000 MCMC replicates and a burn-in period of 10,000, a number of putative populations K between 1 and 18, and 30 replications per run. The output of all analyses was visualized by the online program Structure Harvester49, which estimates the changing rate in log probabilities between consecutive values of K according to the ad hoc statistic ∆K method50. A structure analysis was repeated with the best K, estimated by Structure Harvester with 100,000 MCMC replicates, a burn-in period of 30,000, and 50 replications.To identify the number of genetic populations (= best K) and the degree of admixture between and within each genetic population of Supplementary information.


Animal and plant species around the world are being challenged by the deleterious effects of inbreeding, loss of genetic diversity, and maladaptation due to widespread habitat destruction and rapid climate change. In many cases, interventions will likely be needed to safeguard populations and species and to maintain functioning ecosystems. Strategies aimed at initiating, reinstating, or enhancing patterns of gene flow via the deliberate movement of genotypes around the environment are generating growing interest with broad applications in conservation and environmental management. These diverse strategies go by various names ranging from genetic or evolutionary rescue to provenancing and genetic resurrection. Our aim here is to provide some clarification around terminology and to how these strategies are connected and linked to underlying genetic processes. We draw on case studies from the literature and outline mechanisms that underlie how the various strategies aim to increase species fitness and impact the wider community. We argue that understanding mechanisms leading to species decline and community impact is a key to successful implementation of these strategies. We emphasize the need to consider the nature of source and recipient populations, as well as associated risks and trade‐offs for the various strategies. This overview highlights where strategies are likely to have potential at population, species, and ecosystem scales, but also where they should probably not be attempted depending on the overall aims of the intervention. We advocate an approach where short‐ and long‐term strategies are integrated into a decision framework that also considers nongenetic aspects of management. We start by providing some examples of the different genetic mixing strategies in Table 2Genetic rescue is the term given to the most widely known strategy for the deliberate movement of genes across populations. Most applications of this concept have been responsive in nature and directed at reducing the genetic load of small populations suffering from inbreeding depression and fitness declines as a consequence of close relatives mating and random genetic drift  is the genetic burden of a population resulting from a steady flux of recessive deleterious mutations that remain at low frequency within populations. They are generated by mutation and natural selection acts to remove them, creating a low equilibrium frequency of deleterious alleles that reduces the overall fitness of the population . When a population becomes small, inbreeding can lead to the elevation in frequency and expression of these segregating deleterious alleles, resulting in inbreeding depression (and likely further reductions in population size). If the population remains small and isolated, then some of the segregating load will be lost from the population and a fraction will become fixed due to random genetic drift. These alleles will be expressed throughout the population, contributing to the drift load, leading to reductions in population fitness and size, which feeds back to enhance drift load, which could result in extinction  is likely to result in the masking of deleterious alleles and a resulting increase in the fitness of F1 individuals. However, the genetic load of the recipient population may also eventually increase as new deleterious alleles become fixed. Population growth and selection can act to reduce the overall genetic load. However, if population growth does not occur, there could be fitness consequences of an increased genetic load after the genetic rescue. For instance, in the Isle Royale gray wolf, an initial positive effect of genetic rescue was later followed by a population decline . This may apply to populations recently fragmented Bossuyt, , or smalBurramys parvus is one of Australia's most threatened marsupials and is restricted to alpine regions. The species persists in three main alpine regions, and these populations have been genetically isolated for at least 20,000 years  which in turn increases their adaptive capacity  with around 20× more genetic variation caused substantial increases in genomic variation, individual fitness, and population size. Fitzpatrick et al.  that occupy habitats heavily polluted with halogenated and polycyclic aromatic hydrocarbons. Genome scans of F. grandis populations spanning a pollution gradient found that loci with the strongest signatures of recent selection harbor genes regulating aryl hydrocarbon receptor (AHR) signaling, which in turn is negatively correlated with pollution level. Comparisons of whole‐genome sequences from F. grandis and its sister taxon, the Atlantic killifish (F. heteroclitus), which has also adapted to similar chemical exposure, suggested that resistance loci in F. grandis introgressed within the last 30 generations from F. heteroclitus. The recent adaptive introgression was likely mediated by human‐assisted transport allowing for hybridization, but sufficiently rare to preclude extensive accumulation of deleterious genotypes in F. grandis.Oziolor et al.  provide 4.2.2The process is akin to marker‐assisted selection seen in primary industries, which involves selecting for genetic variants linked to phenotypes of commercial interest. Primary industries have shifted their focus in the last decade to the use of marker‐based selection for enhancing both resilience and productivity of livestock, food crops, fisheries, and forestry under climate change. Genomic selection provides additional power in these analyses because a much higher density of genes is available for directing trait selection  that promote fast growth under warmer temperatures and could be used to counter current negative effects of climate warming on growth rates (Box Pseudotsuga menziesii var. menziesii), which are at risk of frost damage under climate change , populations with low frequencies of alleles associated with climate along gradients show the sharpest declines in population size , is maladapted to current temperature climates and growth rates are expected to slow as temperatures rise over the next century  is particularly important, given their response to environmental change will have major impacts on overall community structure and ecosystem function. Many species providing critical ecosystem services  are declining as a result of climate and other interacting stresses, leading to ecological cascade effects that compromise biodiversity and ecosystem function , and the history of the recipient population  in Table In terms of provenancing and genome selection, deliberate introductions of pre‐adapted genotypes can help overcome risks of maladaptation if the selection process can capture the challenges involved in defining the current and future fitness of the selected genotypes  strategies aimed at deliberate interventions in populations cover a continuum depending on genetic and evolutionary goals and the timeframes involved. When modifying populations to ensure some sort of rescue outcome, it is critical that strategies take into consideration the scenarios and endpoints of a rescue being considered Figure . The sceAppropriate scenarios for deciding on genetic mixing strategies also depend on the nature of source populations available for mixing. Where these are all small, resilience should be built up by sourcing from multiple small populations, acknowledging that population size needs to increase to avoid perverse outcomes of a higher genetic load. However, when masking inbreeding depression, sourcing from large populations produces additional issues because these populations have not been purged in the same way as persistently small populations. If only a single large source population is available and inbreeding continues in the recipient population, then this could lead to further inbreeding depression due to an inability to purge the genetic load, whereas a continuous influx from a large population would prevent this issue occurring.Applications of genetic mixing will also depend on the nature of the species being considered and particularly their generation time within the context of the rate of environmental change. While inbreeding depression masking may be most relevant to F1s, there are many situations where such a short time frame is critical such as in wildlife with long generation times. The different approaches carry different levels of risk. So evolutionary rescue through assisted gene flow is recommended for large populations with clear evidence of adaptation likely to benefit most from this process (Aitken & Whitlock, None declared.