Desmophyllum dianthus, dwelling in Chilean Patagonia, with the aim to illustrate its population genetic structure, demography and adaptation of the species along this coast. Microsatellite loci analysis included D. dianthus individuals from twelve sampling localities along bathymetric and oceanographic gradients from the latitude 40°S to 48°S. The results showed a lack of genetic structure with an asymmetric dispersion of individuals, and relevant heterozygosity deficiency in some populations. This study also analyses the natural and human impacts affecting the region , and stresses the importance of including genetic information in the process of management and conservation of marine resources. In particular, the relevance of using interdisciplinary approaches to fill the gaps in scientific knowledge especially in remote and pristine areas of western Patagonia. Therefore, information on genetic spatial distribution of marine fauna could become pivotal to develop a holistic ecosystem-based approach for marine spatial planning.The Chilean Patagonia is a complex puzzle of numerous fjords, channels, bays, estuaries, and islands. The largest part of it is very remote, hampering the generation of scientific knowledge and effective management planning that could balance conservation of the marine resources with the increasing development of aquaculture activities. The present study focuses on the deep-water emergent cold-water coral  The complex morphology of the Chilean coast is also reflected in the physical and chemical features of its waters , which present high seasonal and spatial variability 5, promoting peculiar biological and ecological traits . Chilean coastal waters represent unique marine ecosystems, and Patagonian marine ecosystems are highly diverse, showing hotspots richer in marine biodiversity than the coast north of Patagonia6. The decrease along the latitudinal gradient might be explained by a poleward reduction in diversity. The extension, complexity, remoteness and harsh climate of the region have also hampered the development of the scientific knowledge, leaving the Chilean Patagonia one of the least studied marine regions of the world1.Chilean Patagonia is one of the largest and most ragged fjord regions of the world. It is an articulate maze of channels, bays, estuaries, islands and fjords that extends over 240,000 km7. It is an economic-social relevant driver of the country, converting Chile in the second largest salmonid producing country with 25.4% share of the global salmon production8 and having a dampening effect of the unbalance and inequality in household income distribution9. Human well-being based on unsustainable blue economy does not come without conflicts, costs and risks. The Chilean salmon industry was accompanied by major sanitary crises , and environmental shortcomings , actively contributing to environmental and socio-economic degradation13. Therefore, the expansion of the salmonid industry into the Chilean southern regions  and Magallanes y de la Antártica Chilena (Region XII—latitude range 48°–56°S)14 rises concerns about the impact that salmon production may have on those marine ecosystems10 of the remaining more pristine areas of Patagonia. The uniqueness of these marine habitats let the recent implementation of two new national reserves: Katalalixar National Reserve in the Region XI and the newly created Kawésqar National Reserve in Region XII16. Besides anthropogenic activities, climate change is affecting the marine organisms and habitats of Chilean Patagonia17 within and outside marine protected areas (MPAs). Observed global climate trends have reduced precipitations in Chilean Patagonia, especially during summer18, and will alter freshwater discharge of large rivers present in the region . There will also be effects on local ocean circulation including the northward expansion of subantarctic water, driving potential changes on physical dynamics, biogeochemical and plankton properties3.Nevertheless, the coastal area of Chilean Patagonia is intensely used for salmonid farming19. However, management and conservation of the Chilean marine resources and ecosystem services require spatial planning, regulating the intensity and impacts of human activities, while balancing socio-economic development demands with the need for marine protection and governance (i.e. ecosystem-based approach)21. Genetic information like geospatial genetic diversity and connectivity has a great potential to support both policies, marine conservation and marine spatial planning at multiple scales23. In this context, only few studies have been conducted to define genetic diversity and structure of populations of marine organisms across Chilean Patagonia. Some examples are Alexandrium catenella (dinoflagellate24), Dissostichus eleginoides and Sprattus fuegensis (fish26), Cephalorhynchus eutropia (dolphin27), and Balaenoptera borealis  at fine-scale, or Desmophyllum dianthus  at fjord-depth scale.The extent of the damages affecting the oceans and their biodiversity, as well as the strategies most suited to protect them, is disconcertingly and disproportionately understudiedDesmophyllum dianthus individuals dwelling throughout Chilean Patagonia. Possible explanations of the observed genetic structure, patterns of gene flow, and potential recolonization are discussed evaluating the reproductive dynamics of the species, the particular oceanographic features of the Chilean Patagonia, and of climate change impacts and anthropic activities affecting this region.This study analyses the large-scale genetic diversity, population differentiation and potential subdivision of the deep-water emergent coral D. dianthus was sampled and preserved in absolute ethanol.Chilean Patagonia encompasses a vast area characterized by fjords, channels and numerous archipelagos. Samples were collected at twelve locations and different depths throughout North and Central Patagonia: eight sites in the Los Lagos Region (hereafter Region X): four locations from Comau Fjord , and four from Reñihue Fjord ; and four sites in the Aysén del General Carlos Ibáñez del Campo Region (hereafter Region XI): one location from Pitipalena Fjord (Isla Jaime), and three locations from the archipelago Guayaneco ; , with slight modifications, including the optional RNase treatment and an extended period of proteinase K lysis (overnight incubation at 55 °C). DNA concentration was quantified using the Qubit 2.0 Fluorometer, and diluted to a final concentration of 2 ng/µl. Thirty-one microsatellite loci developed for D. dianthus  were organized in 1 tetraplex, 7 triplex, and 3 duplex by Multiplex Manager 1.033 and analysed in each sample. Multiplex PCRs were performed using 1X Qiagen Multiplex PCR Master Mix , and following the PCR conditions described in Addamo et al.31. Fluorescently labelled PCR products were run on an ABI PRISM 3730 DNA Sequencer (Applied Biosystems), scored using the GeneScan-500 (LIZ) size standard, and analysed with the GeneMapper software (Applied Biosystems).Following the procedure described in Addamo et al.34 using Micro-Checker35 and FreeNa36. Due to possible asexual reproduction of corals (e.g. via budding), individuals with identical multilocus genotype (i.e. clones) were identified using the index of probability of identity  and the probability estimates for putative clonal genotypes calculated using GenAlEx 6.537. Departures from Hardy–Weinberg Equilibrium (HWE) and genotypic linkage disequilibrium (LD) were tested using Genepop on the web version 4.738 and GenAlEx 6.537. Sequential Holm-Bonferroni correction39 was applied to the multiple tests. Basic information on genetic variability and diversity within and among sampling localities was estimated as allele frequency and richness, heterozygosity  and fixation index (FST). Computations were made using GenAlEx 6.5, Genepop on the web version 4.7, and Arlequin version 3.540.Estimates of null allele frequency, error scoring, and large allele dropout were calculated with the Brookfield-1 method41. Bayesian analyses of genetic admixture model, including the information of sampling localities (LOCPRIOR) were run with settings including 50,000 MCMC interactions after a burn-in of 10,000 iterations. Ten independent chains were run to test each value of K from 1 to 15. The results from Structure were then processed in Structure Harvester42, Structure Selector43 and CLUMPAK44 to detect the best-fit number of genetic clusters representing the genetic discontinuity of the data. The highest mean lnPr(X|K)45, the ∆K46, and MedMeaK, MaxMeaK, MedMedK, MaxMedK47 were all considered to identify and evaluate the optimum value of K. Each cluster identified in the initial Structure run was analysed separately using the same procedures to identify potential within-cluster structure46. Individual/population assignment and genetic differentiation among clusters suggested by Structure, were calculated using analyses of molecular variance (AMOVA) implemented in GeneClass248, Arlequin 3.5 and GenAlEx 6.5, respectively. Samples were subjected to spatial genetic analysis using principal coordinate analysis (PCoA).To investigate population structure, the number of genetic clusters (K) from multilocus genotype data was inferred with a Bayesian model-based approach implemented in Structure v2.3.449 to test a recent reduction in effective population size from allele data frequencies. Detection of first-generation migrants was determined using GeneClass248, setting the frequency-based method with Monte-Carlo resampling, minimum number of 10,000 simulated individuals, and 0.01 and 0.05 for Type I error  values.Population demography analysis was computed using Bottleneckhttp://www.sernapesca.cl) of Ministry of Economy, Development, and Tourism in Chile. Descriptive analyses on abundance and distribution of salmon farms were conducted using R packages tidyverse50, dplyr51, and ggplot252.Finally, information about salmon farming in the Chilean Patagonia was retrieved from the National Fisheries and Aquaculture Service  resulted in absence of putative clones based on repeated multilocus genotypes. However, the detection and elimination of null alleles and loci/sample with 10% of missing data reduced the final genotype dataset to 28 microsatellites and 223 individuals. Analyses with Micro-Checker and FreeNa detected null alleles, while GenePop and GenAlEx confirmed the presence of few loci that were not in accordance with the HW equilibrium and the absence of linkage disequilibrium between loci in the reduced dataset. The potential inclusion of informative missing data, the presence of null alleles and loci that do not match the expectations of HW equilibrium, and their potential effects on population genetic inferences for an apparent excess of homozygosity in the locus, led us to parallel run analyses with five different datasets  and Isla Jaime (IJC)), while the observed heterozygosity (Ho) was lowest in Punta Gruesa  0.52 ± 0.05) and highest in CFC (0.64 ± 0.05) . Whereas, for the four studied areas, the AMOVA indicated no significant difference with very low level of variation among groups . For complete information on the FST estimates between populations and their statistical significance, see Supplementary Tables While the genetic dissimilarities explored through the analysis of principal coordinates (PCoA) showed two potential clusters directed by PC1, explaining 44.64% of dissimilarity Fig. B, is no 45, ∆K46, and MedMeaK, MaxMeaK, MedMedK, MaxMedK47 , with all individuals contributing equally to both clusters  exchanging volume of individuals among localities in Chilean Patagonia ers Fig. . The assDemographically, all populations presented normal L-shape distribution of alleles frequency, having no trace of any bottleneck event (i.e. severe reduction in population size) in recent times. Exceptions for Isla Lilihuapi (ILC) and Isla Jaime (IJC), whose sign tests under the TPM indicated: 24 loci with significant heterozygosity deficiency and only 4 with heterozygosity excess (expected number of loci with heterozygosity excess: 16.46) for ILC; and 23 loci with significant heterozygosity deficiency and only 5 with heterozygosity excess (expected number of loci with heterozygosity excess: 16.23) for IJC.1, but also an area where the optimal ecological conditions lead salmon farming becoming one of the most important economic sectors in Chile54. Based on the most recent data on salmon farms of the National Fisheries and Aquaculture Service in Chile14, over the last 38 years (1981–2019) a total of 1357 concessions of salmon farms have been granted in the Region X (501), Region XI (723) and Region XII (133) , a high density of coral individuals was documented 58. Whereas smaller and only scattered individuals were found in the fjords of the southern part of North Patagonia and in the channels of Central Patagonia, and other smaller accumulations of mid-sized corals are in the islands and channels where the Penas Gulf connects to the channels of Central Patagonia6. If limited or even non-genetic heterogeneity is synonym of non-adaptive plasticity to environmental changes60, the panmictic structure of these coral populations along Chilean Patagonia may suffer a lack of capability to cope with environmental crisis and changes. The unique and fragile ecosystems of Patagonia, however, are subjected to the effects of climate change and increasing anthropic activities, e.g. high-impact salmonid farming54.A previous study demonstrated that the spatial–temporal homogeneity of the physical structure in Comau Fjord might promote gene flow among coral individuals, maintaining a panmictic population spread across different locations and depths within the fjord−1) and strong main currents: the northward Humboldt Current (HC) and southward Cape Horn Current (CHC)62. Even though the CHC is not well studied yet, this southward current along the southern coast of Chile is crossing different channels, banks, islands and characterizing both Region XI and Region XII, with seasonal variability of the area in wind, circulation sea surface temperature, chlorophyll and primary production64. Such a current splitting would be expected to influence the biogeography of marine organisms, as it could potentially fragment the D. dianthus populations resulting in a clear genetic differentiation between northern and southern localities. The seasonal variability of the CHC5, and temporal variability in the phyto/zooplankton primary production66, as well as the seasonal reproduction of D. dianthus67 support the absence of a genetic structure. The panmictic populations could enable long-term resilience to environmental and anthropogenic stress, and heavily-impacted populations could effectively be re-seeded by less-impacted populations. However, the asymmetrical allelic richness of polymorphic loci among locations and the environmental impacts along the whole Chilean marine waters drives the future re-settlement of damaged coral populations. Contradictorily, the populations that died in Comau Fjord in 201268 have not been repopulated until today and other organisms have taken over the substrate. Thus, the Chilean Patagonian region and its strong abiotic gradient forms one of the most ragged shorelines with a labyrinth of fjords, channels, and islands habiting by numerous habitats that are further diversified by temporal dynamics 1. Given the geographic complexity in the study region, some populations might be naturally more unaffected by anthropogenic activities and climate change due to their remoteness and/or environmental stability. However, economic activities, mainly salmon farms, are extending southward and jeopardizing the geographic role as potential climate change refugium (CCR)69. The higher percentage of private alleles in Comau Fjord, however, raises the question whether Comau Fjord acts as source or sink of genetic biodiversity for the coral populations30. The results also suggest the presence of some retention of the private alleles in some localities  that are not found in others. Finally, although no sign of bottlenecks has been found, there may be a certain genetic drift that causes the loss of those alleles further south, where the populations are smaller. The high densities of D. dianthus individuals, besides being unique in Patagonian coastal waters, highlights the importance of Comau Fjord as a relevant hotspot. The high beta diversity within Comau Fjord stresses the need of ad-hoc management and protection of that particular marine habitat. On the other hand, the absence of genetic structure along Patagonia might ensure—if ecosystems conditions would be suitable—a repopulation of northern fjords in case of possible mass mortality event that would kill the remaining corals  refugium for northern coral populations, the low abundance of coral individuals south of the fjords of Region X  could represent a limiting factor and drawbacks, especially in determining low levels of genetic heterogeneity. For example, the significant heterozygosity deficiency among individuals from Pitipalena Fjord found in the bottleneck analysis under the TPM, and the low abundance described for both Region XI  and Region XII would unlikely repopulate the genetic diversity of represent by individuals inhabiting Region X (Comau Fjord). Moreover, the natural dispersion found, estimated in number of migrants, clearly indicated that a migration exists, but the southern populations contribute less to such individuals' interchange. Thus, it would be possible that some  currents were responsible for a greater dispersion from north to south, or that the southern populations simply represent the limit of the species in that area.South of approximately 40°S, ocean circulation is characterized by the bifurcation of the eastward South Pacific Current (SPC) in two very fast  found in previous studies were considered to likely represent the outcomes of asexual reproduction of D. dianthus32. Any clonal structure of Chilean population have been not detected in this study, however it is reasonable to assume the possibility of both reproduction strategies for Chilean individuals. Hence, the slower metabolism and the potential collapse of environmental tolerance of the species would therefore lead to abet the asexual reproduction, exacerbating heterozygosity deficiency among individuals82. Different regions of Patagonia are subjected to different stressors83. A potential silent genetic differentiation coupled with multiple environmental stressors might shape the distribution and different abundances of coral population reaching the ecological limit. Then, the means of connectivity (e.g. currents) would further reduce the possibility of potential differentiation. Characterizing the sites where the corals were sampled might help to reveal the existence of ecological gradients versus genetic metapopulations.While the general patterns in abundance and distribution of species and populations should approximate a normal probability density distributionD. dianthus populations have been collected from deeper depth of northern Chile from the Humboldt Current ecosystem84. The bifurcation of the South Pacific Current in two currents with opposite directions might represent an important physical barrier between Northern and Southern Chile. Climate change also affects precipitation and oceanic currents85 and thus might have effects in future connectivity patterns and thus the genetic structure of the coral populations. Further studies are needed to explore if the Peruvian Province and the Intermediate Area have the same genetic profile as the populations of Chilean Patagonian, and how climate change would affect the D. dianthus distribution. Such contest would lead to consider ad-hoc conservation needs based on the different Chilean metapopulations and regional biodiversity.Some individuals of 86, as well as provides nearly ideal conditions for salmon farming54. Therefore, in addition to the effects of climate change  and ocean acidification , for example, is one of the four poorest Chilean region with 23.2% of multidimensional poverty more than the average of the country (20.9%)88. Salmon farms promote seawater eutrophication and oxygen depletion11, which most likely will pose a major threat to D. dianthus in the naturally acidic waters of some Patagonian fjords where the coral lives since the species is not able to cope with the synergistic effects of both stressors81. As aquaculture is projected to become the main global seafood producer, there will be enormous demand for increasing production while there is little empirical research on its impacts, epically long-term ones54. This notable gap drives a vast reorganization of marine tenure governing the multiple use of coastal waters for other spatially fixed activities such as energy infrastructure89. The numerous salmon aquaculture concessions allocated over the last 38 years and the southward movement of the new salmon farming activities evidenced in this study will increase the impacts on Central and South Patagonian ecosystems91. Unsustainable and space-demanding aquaculture activities would enhance ecosystem degradation and could further lead to other sanitary crises. Indeed, the planned anthropic activities could affect Katalalixar National Reserve (Region XI) and the newly created Kawésqar National Reserve (Region XII). Both national reserves are characterized by diverse pristine marine habitats, with a wide range of biophysical conditions, still rare/low human impacts, and yet largely unknown marine ecosystems16. Finally, the frequent harmful algal blooms occurring in Chilean waters93, causing phycotoxin contamination and mass mortalities of marine organisms94, and might also lead to an unbalanced primary production affecting the livelihood of coral populations.The remote area of Chilean Patagonia harbours the highest diversity of shallow-water anthozoansD. dianthus inhabiting the Chilean Patagonian coast represent a panmictic population. However, in relation to other areas, they constitute a unique genetic profile in the Southern hemisphere, genetically distant from the neighbouring populations of New Zealand and Argentina29 Accordingly, the Chilean Patagonian population for its genetic richness and ecological peculiarity needs specific conservation actions. Similar panmictic populations and gene flow patterns have been observed in other species, like Alexandrium catenella (dinoflagellate24), Dissostichus eleginoides and Sprattus fuegensis (fish26). Nevertheless, further studies with a multidisciplinary approaches should consider either D. dianthus individuals inhabiting Northern Chile as well as other marine species to better understand the ecological and biophysical features driving the uniqueness of marine ecosystems in Patagonia. An efficient management plan should be applied including an integrative approach20, balancing ecological, genetic, social and economic aspects of the marine ecosystems and their services. An ecosystem-based approach of marine spatial planning that includes the creation of new marine protected areas (MPAs) leading to healthy marine ecosystems could promote sustainable activities and help to avoid conflicts among environmental and economic interests.The individuals of Supplementary Information.


Commercial routes are reported as the main cause of biological invasions. Particularly, naval trade may accidentally bring several species to new areas where they are not native. This is particularly evident for coastal areas, where most biological invasions occur. In our work, we reported, for the first time, the presence of the ocellated skink, native to the largest Italian islands . We collected several individuals of this alien population and we sampled them for molecular analyses, comparing them with those naturally occurring in Sardinia, Sicily and the Mediterranean basin, including individuals accidentally introduced to peninsular Southern Italy. Differently from what previously suggested, the nucleus in Portici  may have originated from Sardinia. The intense cork trade and touristic traffic between Sardinia and Southern Tuscany may have been responsible for the introduction of this lizard also to Central Italy.Chalcides ocellatus) is a widespread lizard, naturally distributed between the Maghreb and coastal Pakistan, with few insular populations in the Mediterranean coastal area. Some populations of this species have also been recorded in peninsular Italy, Campania and Southern Tuscany due to accidental introductions via touristic and commercial routes. In this work, we conducted genetic analyses on mitochondrial DNA COXI, cytb and 16S mtDNA genes on a sample of Italian insular and peninsular populations. Differently from what previously suggested, the nucleus in Portici  may have originated from Sardinia. The intense trade and touristic traffic between Sardinia and Southern Tuscany may have been responsible for the introduction of this lizard also to Central Italy.The ocellated skink ( Hemidactylus turcicus, Mediodactylus kotschyi, and Tarentola mauritanica) [Chamaeleo chamaeleon) occur in Southern Italy, due to multiple introduction events [Indotyphlops braminus is a semi-fossorial snake native to the Indo-Malayan region, able to survive also inside pots [Maritime transport supports 80% of the current global trade, a quarter of which crosses the Mediterranean ,2,3. Theitanica) ,12,13,14n events ,16. Simiide pots . This adide pots ,18.Chalcides ocellatus) is a widespread lizard species naturally occurring throughout Northern Africa, Western Asia, and South-Eastern Europe [C. o. tiligugu is distributed throughout Italy, i.e., in Sicily and Sardinia [C. o. linosae) and Lampedusa islands (C. o. zavattarii) are not genetically supported [The ocellated skink  were employed as outgroups (Samples of utgroups . All samhttp://www.technelysium.com.au (accessed on 9 June 2022)). The sequences were manually corrected and then aligned using CLUSTALX 1.81 [The PCR profiles were the same reported by Kornilios et al.  for 12S ALX 1.81 . In ordeALX 1.81 ,33) or mFor both datasets, we carried out a phylogenetic reconstruction by Neighbor-Joining (NJ), Bayesian (BI) and a Maximum Likelihood (ML) phylogenetic analysis. Analyses were carried out using genetic models selected by jModelTest , with thN = 4 males, 3 females) were sampled and immediately released.In our work, we confirmed, for the first time, the presence of a population of ocellated skink on the Tuscan coast, between the ports of Piombino and Torre Mozza. The population was confirmed to be reproductive, as two juveniles were also observed. In this area, seven adult individuals of ocellated skink , except for Tunisia, which resulted as the sister clade of all the other C. ocellatus groups. The second clade was constituted by the group of Tunisian and Italian populations. However, the last group looked quite close to Sardinian populations but not to the Sicilian or other peninsular populations, even though the tree is largely not solved at the interspecies level. The Linosa sample was included in the Sicilian clade, even if the relationships among Sicilian populations were not highly supported. However, the phylogenetic relationships within different Italian populations were not well resolved. The Dataset 1 tree showed two sister groups: populations from Tuscany  in one group and Sicilian, Sardinian and Portici populations in the other group. Sicilian samples are grouped together and they have the Pantelleria sample as a sister group. The Portici sample looked quite close to Sardinia, whereas Linosa confirmed its position inside the Sicilian group even if the support values at nodes of this group were not high.The different phylogenetic reconstructions applied to both datasets gave similar results . Within Sardinian populations were very close to one of the Tunisian sequences, and appeared as the only one with such high genetic affinity, as enlightened also by genetic distances .Testudo graeca [Chalcides chalcides [Natrix maura [Hemorrhois hippocrepis [C. ocellatus clade can be assigned to a single species, although they exhibit intraspecific genetic divergence with 6–8% values in cytb + 12S. Consequently, a split in different taxa must be evaluated.The ocellated skink is a widespread lizard species, with populations throughout the Mediterranean basin, up to the Middle East. The species may have evolved in Northern Africa and, afterward, expanded its range until coastal Pakistan . In our o graeca , Chalcidhalcides , Natrix ix maura  and Hemopocrepis . Particupocrepis . Carranzpocrepis  sustaineWe are aware of the limitation due to our small sample size, as our analysis was based on few mitochondrial DNA-only loci from a limited number of individual samples. However, we provided the first COXI barcoding sequences for this species and the first available information on the origins of the only two populations occurring in peninsular Italy; the one in Piombino is still unreported in the scientific literature.C. o. tiligugu were detected  and the other populations . Siciliaorted by , the secail root ) were deail root . This hyFibla maclachlani), recorded since 2005 also in the coastal part of Southern Tuscany, where it is currently expanding [Quercus suber L. [C. ocellatus on the Italian mainland would not represent a threat to native biodiversity, given the low population densities [Other Sardinian species followed the same colonization pattern, e.g., the Mediterranean snakefly , which  linosae . However linosae  were notDespite the wide distribution range of the ocellated skink, its scattered presence in Europe makes this species a conservation concern . Thus, aPort areas constitute a typically perturbed anthropogenic ecosystem, widespread and highly globally interconnected. Therefore, they have considerable potential to be hubs for the diffusion of aquatic and terrestrial alien species ,8. The s


Plectropomus leopardus [Lacépède 1802]), across two adjoining regions  spanning approximately 14 degrees of latitude and 9 degrees of longitude. We analysed 4548 single nucleotide polymorphism (SNP) markers across 11 sites and show that genetic connectivity between regions is low, despite their relative proximity (~100 km) and an absence of any obvious geographic barrier. Inferred demographic histories using 10,479 markers suggest that the Coral Sea population was founded by a small number of GBR individuals and that divergence occurred ~190 kya under a model of isolation with asymmetric migration. We detected population expansions in both regions, but estimates of contemporary effective population sizes were approximately 50% smaller in Coral Sea sites, which also had lower genetic diversity. Our results suggest that P. leopardus in the Coral Sea have experienced a long period of isolation that precedes the recent glacial period (~10–120 kya) and may be vulnerable to localized disturbances due to their relative reliance on local larval replenishment. While it is difficult to determine the underlying events that led to the divergence of the Coral Sea and GBR lineages, we show that even geographically proximate populations of a widely dispersed coral reef fish can have vastly different evolutionary histories.Many coral reef fishes display remarkable genetic and phenotypic variation across their geographic ranges. Understanding how historical and contemporary processes have shaped these patterns remains a focal question in evolutionary biology since they reveal how diversity is generated and how it may respond to future environmental change. Here, we compare the population genomics and demographic histories of a commercially and ecologically important coral reef fish, the common coral grouper ( Digested gDNA was cleaned with Dynabeads™ M‐270 Streptavidin (Life Technologies), quantified using the Qubit HS dsDNA assay kit (Life Technologies) and a Qubit 2.0 fluorometer, and standardized to 60 ng gDNA. Universal P2 adapters were then ligated onto fragment ends, and sets of 16 individuals were barcoded with unique P1 adapters. Individuals were pooled into groups of 16 and bead cleaned before selecting the 450–500 bp fragment size using the Pippin Prep (Sage Science). Unique Illumina indices were added to their respective pools, and gDNA was amplified with 10 PCR cycles using the high‐fidelity Platinum™ Taq DNA Polymerase (Thermo Fischer Scientific). The molarity of the pools was quantified using the High Sensitivity Qubit Kit and the 2100 Bioanalyzer (Agilent Technologies). For each library, we combined pools into a single standardized sample, and 150 bp paired‐end reads were sequenced on a single lane of an Illumina HiSeq 4000. Sequencing was conducted by the King Abdullah University of Science and Technology Bioscience Core Laboratory, Saudi Arabia.Tissue was subsampled and DNA extracted using the NucleoSpin Tissue Kit (Macherey‐Nagel). Eight genomic libraries were prepared following the double digest RADseq protocol , n , and m . For each dataset, we used the populations function to retain loci with a minimum coverage of 10×, loci in every individual (–r = 1), and loci in both populations .Hybrid fishes can be difficult to identify based on color alone so we ran a series of tests to screen for admixed individuals in our collections. Data were assembled de novo using Stacks version 2.3.5 , was set to two. Three replicate runs were conducted for each K, and admixture proportions were averaged across replicates. We used a conservative approach and excluded any P. leopardus individuals with an admixture proportion greater than 1%.We then used the program STRUCTURE version 2.3.4  when implementing the cstacks function, as most informative loci are likely to be captured within the first 10 individuals of a population . To test for potential contamination, we then screened for individuals with unusually low (<0.08) or high (>0.12) heterozygosity relative to other individuals in the sample, and for individuals that had more than 30% missing data. Lastly, we excluded loci with heterozygosity >0.5 and markers that were in Hardy–Weinberg disequilibrium in two or more populations using a mid‐p value threshold of 0.05.The resulting dataset was then imported into the R package PCAdapt  to compute test statistics and p values for each locus based on correlations between SNPs and principal components. We set K at 2 as this was identified as the most likely number of clusters in our data  or loci in Hardy–Weinberg disequilibrium, as these are likely to be influenced by demographic processes and are informative for inferring the demographic histories of populations.2.5strataG  were estimated using the divBasic function in the R package diveRsity version 1.9.90 .Observed and expected heterozygosity and allelic richness were calculated in the R package ekutieli . We usedJombart,  to visuaLEA  from 1 to 11. The most parsimonious number of populations (K) was determined by selecting the run with the lowest cross‐entropy criterion .To explore differences in ancestral genetic diversity, we used sparse non‐negative matrix factorization (SNMF) in the R package n Figure . We cond2.6P. leopardus in the Coral Sea and the GBR, we inferred the demographic histories of populations using a modified diffusion approximation of the Wright‐Fischer population model implemented in the program GADMA . We chose to compare Britomart (GBR) vs. Flinders  due to their geographic proximity and Princess Charlotte Bay (GBR) vs. East Lihou  to determine whether results were consistent at a broader spatial scale.https://github.com/isaacovercast/easySFS). We used one SNP per locus, and thus loci were assumed to be unlinked and 1,060,096 bp as the effective sequence length. An empirical mutation rate is not known for our study species, so we chose to use the mutation rate of 1.0E−08, which is most commonly reported for fishes  of 8.25 years based on the formula by Pianka (t2 = (a + w)/2, where a = mean age (years) at 50% maturity and w = longevity (years). We set a at 2.5 years and w at 14 years based on the known life history of P. leopardus in the GBR  files using the easy SFS python script . This allowed us to test for consistency across models, while acknowledging that these results should be interpreted with caution because inferring complex scenarios using a relatively small number of loci  of unknown evolutionary history may result in over‐fitting of the data. Together, the complex and simple models captured many possible demographic scenarios, including the four most common that are often inferred from genomic data: strict isolation (SI), ancient migration (AM), isolation with migration (IM), and secondary contact (SC). The list of models and parameter space of the 20 best models for each dataset are shown in Tables 33.1A total of 31 individuals were excluded due to having evidence of mixed ancestry >1%, all admixed individuals were sampled on reefs where they co‐occur with congeneric species Table , highligP. leopardus samples passed further quality filtering steps, and no individuals were excluded while screening for duplicate samples, individual heterozygosity, and individual missing data. We retained 4548 neutral markers for analyses of population genomic structure, 230 outlier markers (of which 42 were detected by both methods), and 10,479 markers for inference of demographic histories. Parameter settings and the corresponding number of filtered loci are shown in Table The remaining 200 3.2FIS) suggesting recent expansions or mixing; however, FIS estimates were closer to zero in the Coral Sea (Table He) and allelic richness . Pairwise FST comparisons revealed a significant genetic break between all sites in the Coral Sea versus all sites in the GBR  in our data was two  identified significant genetic structure among R Figure . SimilarR Figure  and 22% R Figure , and theo Figure .P. leopardus sites was between Torres Strait (the northern‐most site sampled in the GBR) and Lihou East . The two most genetically similar sampling locations between regions were Marion Reef in the Coral Sea and Princess Charlotte Bay in the GBR .The greatest genetic distance between Coral Sea and GBR FST in the Coral Sea was between Flinders Reef and Lihou West  while the smallest pairwise FST in the Coral Sea was between Lihou West and Lihou East .In the GBR, we found no evidence of genetic structure Figures  and 4, iFST estimate of 0.23 (p < 0.001). Within the GBR, there was evidence of structure between some sites according to pairwise FST comparisons ; Flinders  vs. Britomart (GBR), and East Lihou  vs. Princess Charlotte Bay (GBR). For both simple model replicates, the best‐ranked model identified population divergence via isolation with asymmetric migration  across 14 degrees of latitude and 9 degrees of longitude in the west Pacific region of Australia. We find limited genetic connectivity between P. leopardus in the GBR and the Coral Sea despite the proximity of these two regions (~100 km). Inferred demographic histories for two replicate comparisons suggest that divergence occurred under a model of isolation with migration and was initiated at approximately 206 and 177 kya, with one model comparison identifying an ancestral population in the Coral Sea that was two orders of magnitude smaller than the GBR, in terms of effective population size (Ne). Expansions were evident in both regions despite concurrent changes in sea level, but genetic diversity and contemporary effective population sizes (Ne) were smaller in the isolated atolls of the Coral Sea. We found high levels of gene flow along the majority of the GBR and significant genetic structure within the Coral Sea. Our results indicate a unique evolutionary history of P. leopardus in each region.We assess the population genomic structure of a commercially and ecologically important species of coral reef fish  on the demography of coral reef fishes is well documented in the literature  at the recruit, juvenile and adult life history stages  and are rare or absent in surrounding coral reef habitat . It is possible that changing environmental conditions in the Coral Sea  facilitated expansion into the region and that these conditions remained favorable enough to support populations during the ~190 ky period that followed. Indeed, P. leopardus, we provide evidence of a potentially complex evolutionary history influenced by factors in addition to changes in sea level.Alternatively, the abrupt decline in sea level approximately 190 kya may have reduced available habitat in the Coral Sea, resulting in a population bottleneck that triggered faster relative genetic drift from the ancestral population. This may have been re‐enforced by geographic isolation if the ancestral population was restricted to the southern GBR, as suggested for some coral reef species during periods of low sea level Benzie, . While iNe at East Lihou despite this population diverging some 29 kya earlier than the Flinders Reef population. The geographic isolation of Lihou Reef appears to impose some limit on larval connectivity, and this may explain the limited increase in Ne relative to Flinders Reef, which is closer to the GBR. Despite evidence of genetic isolation, expansions were exponential at both Coral Sea reefs and may be a consequence of similar events, potentially initiated by global processes such as changes in sea level  the New Caledonia Jet and the north Vanuatu Jet flow east to west through the Coral Sea and directly intersect the GBR  regP. leopardus, it is possible that the genetic signal of any migrants arriving from the Coral Sea is quickly diluted into the local gene pool . Plectropomus leopardus also form relatively small aggregations  at multiple sites  that aggregate in large numbers  and spawn in reef passages adjacent to the open ocean, during high current flow periods. There is also evidence that reef fish populations in habitat‐limited areas  spawn over narrower time period to maximize local retention of larvae  may serve to limit introgression between populations through the evolution of pre‐ or postzygotic reproductive barriers. Though this seems unlikely given that P. leopardus across the majority of the 2200 km length of the GBR due to the proximity of individual reefs and the ubiquitous distribution this species. Similarly, sites at East Lihou and West Lihou were genetically homogenous due to the continuous habitat that connects the ~100 km long coral atoll. These findings are consistent with (Pinsky et al., P. leopardus larvae (~250 km, Williamson et al., Within regions, measures of genetic connectivity were generally consistent with the geographic configuration of reefs and the relative continuity of habitat. Similar to previous studies that analyse microsatellite markers (Ma et al., 4.3P. leopardus in the GBR experience relatively high levels of genetic connectivity but exist as an independent stock to the Coral Sea. Considering that the GBR fishery is split into 12 stock units that align with habitat types (Campbell et al., Our results add to an increasing body of literature that identifies cross‐shelf patterns of population genetic structure in fishery species with implications for management (e.g., Atlantic cod, Barth et al., P. leopardus populations have declined throughout the majority of their range (Sadovy de Mitcheson et al., High levels of observed genetic connectivity in the GBR are also likely to benefit the relative resilience of this population because they allow the replenishment of individual reefs from upstream locations. The large effective population size and higher relative genetic diversity may also assist with adaptation to changing environmental conditions. These results, however, should not be interpreted as a panacea, as P. leopardus in the Coral Sea escape many coastal impacts due to its distance from mainland Australia such as habitat loss due to coastal runoff (Ceccarelli et al., Plectropomus leopardus are also particularly dependent on live coral cover for habitat (Emslie et al., We show that while 5Climate‐driven changes in sea level, their impact on the demography of GBR fauna, and links with the Coral Sea region are often discussed in the literature Benzie,  but are The authors declare no conflict of interest.Appendix S1Click here for additional data file.


Mimulus guttatus for nine generations in greenhouses with or without pollinating bees and studied DNA polymorphism in descendants. Populations without bees adapted to produce more selfed seed yet exhibited striking reductions in DNA polymorphism despite large population sizes. Importantly, the genome‐wide pattern of variation cannot be explained by a simple reduction in effective population size, but instead reflects the complicated interaction between selection, linkage, and inbreeding. Simulations demonstrate that the spread of favored alleles at few loci depresses neutral variation genome wide in large populations containing fully selfing lineages. It also generates greater heterogeneity among chromosomes than expected with neutral evolution in small populations. Genome‐wide deviations from neutrality were documented in populations with bees, suggesting widespread influences of background selection. After applying outlier tests to detect loci under selection, two genome regions were found in populations with bees, yet no adaptive loci were otherwise mapped. Large amounts of stochastic change in selfing populations compromise evolutionary potential and undermine outlier tests for selection. This occurs because genetic draft in highly selfing populations makes even the largest changes in allele frequency unremarkable.Although selfing populations harbor little genetic variation limiting evolutionary potential, the causes are unclear. We experimentally evolved large, replicate populations of  With few exceptions, flowering plants do not move as adults, yet reproduction typically involves finding and mating with another individual , neutral theory predicts that effective population size (Ne) in partially selfing populations at equilibrium will be reduced relative to an idealized Wright Fisher population with N individuals (Ne=N/(1+F); Pollak Ne because it fundamentally reduces the number of individuals necessary to make offspring in a population  and intercrossed. The resulting (outbred) F3 seed collection was the ancestor for all four experimental populations analyzed in this study  population of s Willis . This pos Willis  and quans Willis . Founders Willis ; Fig. 1as Willis . From th3 seed source was split into two treatments, hereafter referred to as “No Bee” and “Bee,” with two replicate populations in each treatment  with default settings in BWA . These libraries were sequenced using Illumina NovaSeq (S4 option) at the University of Kansas Medical center, generating 150‐bp paired‐end reads. Raw reads were trimmed to remove low‐quality bases in TrimGalore version 0.6.6 Krueger . Reads wWe obtained over 200 million read pairs from each pool  and a variant call file was made using VarScan version 2.4.2  within each population. The procedure obtains a robust estimate for the variance of observed divergence, unaffected by outlier loci under selection. We then subtract off the variance owing to finite sequencing depths. The null variance within a population represents the aggregate of allele frequency dispersion, which includes genetic drift and draft plus the additional round of sampling with the bulking of DNA molecules in each sequencing pool.In this experiment, evolutionary change within populations reflects the combined action of genetic drift and natural selection, both at polymorphisms affecting fitness and linked SNPs. If most SNPs were neutral with respect to fitness over the course of the experiment, we can use the overall distribution of allele frequency changes to estimate the magnitude of change at neutral SNPs. Here, the angular (arcsin square root) transformation was applied to frequencies: y et al.  to estimvA1,vA2, vB1,andvB2 are estimated from the divergence between populations . We used generalized least squares to distill the six distinct pairwise contrasts between populations into the four null variances. The model is y=Xβ^ + error, where y is the vector of population pair divergences, β^ is the vector of null variances, and X is a matrix of indicator variables relating populations to the pairwise comparisons. The variance‐covariance matrix of null divergences (V) was generated by splitting the whole‐genome dataset into windows of 500 SNPs, bootstrapping the SNP dataset 1000 times, and estimating the six null divergences in each replicate. The vector of null variance parameters was then estimated as β^=(XTV−1X)−1XV−1y , null variances , and SNP‐specific read depth variances  were used to calculate the likelihood of competing models  and the null likelihood (LL0) were computed from 2(LL1 – LL0). LRT statistics are approximately χ2 distributed with degrees of freedom equal to the k1 – k0. To account for multiple comparisons, the threshold of significance was determined using Sidak's correction with a false discovery rate (FDR) of 0.05  of the difference between the best fitting model's log likelihood . Lineage specific null variances were 0.0138 for B1, 0.0235 for B2, 0.2554 for A1, and 0.8545 for A2. The higher values for A1 and A2 indicate greatly elevated allele frequency change in the No Bee treatment . This average change is even larger for A2 (Δp≈0.40), but much smaller in B1 (Δp≈0.06) and B2 (Δp≈0.08).No Bee populations exhibited greatly elevated genetic differentiation compared to Bee populations Fig. . FST vaThe much greater divergence of the No Bee populations cannot be explained by differences in adult population sizes. Hundreds of individuals were grown each generation and mean population sizes were only slightly lower in the No Bee populations  relative to Bee populations  and as high as A2  through the first five generations, there was clear evidence of adaptive evolution of quantitative traits and of mean fitness in No Bee populations (Bodbyl‐Roels and Kelly  through s = 0.8) was chosen because its spread emulates the rapid increase in self seed production in No Bee populations followed by little change after five generations of evolution (Table s = 0.8) causes substantially higher null variance, as expected with additional linked selection in the genome. In large outcrossing populations (N = 500), selection on one locus produces outcomes in between those in smaller populations  without natural selection. Strong selection on two loci causes higher null variance, consistent with selection causing stochastic change at linked loci  in the No Bee populations produce AFDs that generally resemble empirical distributions . The simplest nonneutral models received similar levels of support at this broad level . More complex models of adaptation received little support in the neutral simulations , also mirroring the real data.In considering SNPs in the evolved populations, random genetic drift was the most supported model when considering the minimum AIC criterion . The simplest nonneutral models received similar levels of support at this broad level . More complex models of adaptation received little support across SNPs . These patterns (fraction of SNPs favoring each model) are generally reiterated by simulations with purely neutral evolution, at least if we use Slight differences in the log‐likelihood of different models are sufficient for AIC to suggest selection, but large differences are required for an LRT to reject drift in favor of a particular selection model at genome‐wide significance levels. No SNPs were close to this threshold for adaptation in the No Bee treatments Fig . In contP‐values are low enough to pass the threshold , and the coefficient of variation in individual seed number was 65% higher in caged plants . Bodbyl‐Roels and Kelly (h2 = 0.20–0.40), consistent with a role for selection on the genetic component to generate correlated allele frequency changes across generations, which will greatly amplify the cumulative change . Selection on one or two loci with inbreeding elevates the variance among chromosomes, although not to the level observed in population A1 .Sequence data are accessible from the NCBI SRA under PRJNA822425. Code is available on Dryad (Associate Editor: Y. BrandvainHandling Editor: T. ChapmanTable S1. Annotations for SNPs that reject the null model of genetic drift. Best model represents the implicated model of adaptation (Table 2). For non‐coding sites, the nearest gene was identified in M. guttatus. Orthologous genes in A. thaliana are based on highest sequence similarity to the M. guttatus gene. ‘NA’ denotes ‘not available,’ while ‘–’ denotes identity with annotations in the row immediately above.Figure S1. The distributions of nucleotide diversity (pi) in No Bee  and Bee populations  along each chromosome. The number of pairwise differences per site was calculated within 50 kb windows on each chromosome.Figure S2. The null variance produced in neutral simulations with full selfing. At a given population size, the number of individuals (N) was held constant across 9 generations of evolution. Outlines denote distributions and filled circles denote the mean over 1000 independent replicates.Figure S3. The outcomes of SNP outlier tests. P‐value distributions were generated from likelihood ratio tests of adaptation in a single population . Red lines depict threshold P‐values for significant outliers with genome‐wide FDR = 0.05. Tests of adaptation in No Bee populations  fail to produce P‐values that approach the threshold significance level. Filled circles denote means.Click here for additional data file.


Populus angustifolia from SI have diverged from MC, and converged across SI, in reproductive and productivity traits, (2) these traits  are significantly correlated, suggesting a genetic linkage between them, and (3) the trait variation is driven by both natural selection and genetic drift. These shifts represent potentially beneficial phenotypes for population persistence in a changing world. These results suggest that the SI–MC comparison is a natural laboratory, as well as a predictive framework, for studying long-term responses to climate change across the globe.Climate-induced evolution will determine population persistence in a changing world. However, finding natural systems in which to study these responses has been a barrier to estimating the impact of global change on a broad scale. We propose that isolated sky islands (SI) and adjacent mountain chains (MC) are natural laboratories for studying long-term and contemporary climatic pressures on natural populations. We used greenhouse common garden trees to test whether populations on SI exposed to hot and dry climates since the end of the Pleistocene have phenotypically diverged from populations on MC, and if SI populations have converged in these traits. We show: (1) populations of  This includes alterations to soil nutrient pools and bud break phenology driven by mean annual temperature and precipitation, elevation, and genetically-based soil conditioning4, as well as genetic divergence at the provenance level in atmosphere-plant-ecosystem feedback3. While these studies show that long-lived species evolve along contemporary landscape-scale abiotic environmental gradients to affect ecosystem function, they do not directly address how climate change has driven evolutionary dynamics, or which traits have been important for population persistence and ecosystem functioning. Evolution can occur on rapid timescales and is critical to understand in a time of rapid environmental change8. While multiple empirical approaches have been used to understand how species have and continue to respond to global climate variation11, approaches that address how species have evolved in direct response to climate change are still underdeveloped.Identifying how dominant terrestrial species have adapted in response to climate change is fundamental to understanding which traits are most important for population persistence and subsequent ecosystem functioning under contemporary climate change. Recent studies have shown that atmospheric climate gradients shape the linkage and feedback between genetically-based phenotypic variation and ecosystem functions at sub-continental scales13  are vast mountainous regions whereby multiple large populations may exist, interact, and migrate between contiguous habitat corridors25. Owing to more habitat on MC, populations experience higher levels of gene flow and genetic diversity, as well as more climatically buffered habitat suitable for migration and range shifts. Overall, populations across SI and MC have experienced long-term differences in climates that have continued to diverge under Anthropogenic climate change.Sky islands (SI) are globally distributed isolated mountain habitats surrounded by lowlands or habitats outside of the range of species’ thermal tolerance, serving as a barrier to species dispersal and migration15. Previous work has shown that isolation of SI by environment and by distance has resulted in genetic divergence, shifts in species interactions, reduction in genetic variation, and rapid speciation on SI33. These studies show the important roles of reduced gene flow, high environmental pressures, genetic drift, and historical population demographics that have shaped populations isolated atop SI since the Pleistocene35. However, their use as a tool for examining hypotheses specifically related to past or contemporary climate change is minimal. Most research has examined only single SI or clusters of SI within a circumscribed geographic region, and very few incorporate climatic differences into statistical models. Comparative studies of SI relative to adjacent, continuous MC  can directly examine trait evolution and evolutionary mechanisms important for population persistence and ecosystem function in response to past and current climate change.Sky islands have been used extensively as laboratories for studying evolutionary ecology—specifically, patterns of diversity and allopatric speciation—in response to geographic isolation and post-Pleistocene demographic shiftsPopulus angustifolia36. We tested the hypothesis that P. angustifolia populations on hotter, drier SI have phenotypically diverged from populations on MC. Specifically, based on previous research that reports adaptive phenotypic traits driven by landscape-level climatic variation1, we hypothesized that with increased climatic pressures on SI , P. angustifolia populations grown in a common garden will have greater rates of cloning and aboveground biomass than populations on MC, and that these two traits are correlated across the entire study region (Hypothesis 1). Lastly, we tested the hypothesis that any phenotypic variation is driven by climate-induced natural selection (Hypothesis 2).We use the SI-MC comparison to determine if a long-lived tree species has adapted in response to climate change and isolation. Using clonal replicates of trees collected from SI and adjacent MC in riparian areas in the western U.S., we examined intra-specific, population-level divergence to test how vegetative reproductive and productivity traits have responded to long-term climate change and isolation. Under common garden conditions, we examined how long-term climatic variation in temperature and precipitation has altered cloning  and aboveground biomass production  in contemporary populations of the dominant foundation species 2 = 0.022, p-value = 0.05016*) between cloning and aboveground biomass, suggesting a possible genetic linkage between the gene complexes responsible for the two traits  on the z-scores of the microsatellite associated with individual genotypes and incorporated the first two principal component axes (PC1 and PC2) into the phenotypic models. Incorporating genetic markers in the trait models to detect any remaining significance attributed to mountain class  allows us to interpret any observed quantitative trait differences as a consequence of natural selection or genetic drift induced by mountain class. When microsatellite data were included in the phenotypic models  in higher-stress populations of P. angustifolia on SI may indicate that phenotypic trade-offs between reproduction and growth common in high-stress environments45 are not as essential to the survival of this species46. An alternative hypothesis for this pattern is that natural selection is acting on the fitness trait of aboveground biomass. Because cloning and aboveground biomass are positively correlated, high-aboveground biomass trees also produce more clones. Regardless, increases in both of these traits in warmer and drier populations on SI is representative of increased carbon sequestration that influences overall ecosystem productivity49. Taken together, the altered reproductive and productivity traits that we document indicate that convergent evolution among SI could lead to predictable ecosystem-level consequences driven by climatic variation relative to MC, irrespective of the evolutionary mechanism at play. Further, across the SI-MC comparison, cloning and aboveground biomass were significantly correlated, suggesting genetic linkage between the two traits that may be influenced by environmental variation. Due to its value as a bioenergy crop, much research has gone into identifying genetic controls on aboveground biomass in the genus Populus54. However, no research to our knowledge has attempted to tackle the genetic underpinnings of cloning as a reproductive strategy in Populus. Thus, further research is needed to elucidate the genetic and functional significance underlying the correlation between cloning and aboveground biomass.Overall, we show phenotypic trait divergence across the natural range of a long-lived tree species driven by ongoing population demographic and climatic differences since the end of the Pleistocene across the SI-MC comparison. Asexual, vegetative reproduction via cloning allows a genet to spatially “scavenge” for resources across the landscape and persist in environments post-perturbation or under stress56. Numerous studies suggest that plant species will likely respond to the stress caused by climate change by implementing shifts in their geographic ranges61. However, relying on bioclimatic envelopes to predict and model future species’ distributions in response to climate change has largely underestimated the adaptive capacities of long-lived species through phenotypic plasticity or rapid evolution63. One phenotypically adaptive mechanism by which populations may persist under rapid climate change is through evolutionary shifts in cloning  and overall biomass production . Evidence of trait convergence in long-lived tree species demonstrates the empirical utility of the SI-MC comparison as a natural laboratory and predictive framework for studying evolution in response to climate change in natural populations.Contemporary climate change is projected to increase temperatures and the prevalence of severe drought on a global scale, especially in the western U.S.64. The global breadth of the SI-MC comparison is ripe for studies that examine the genetic basis by which populations persist or perish across a fragmented and vulnerable contemporary landscape. For example, SI and MC can be found across the entire natural range of P. angustifolia from northern Mexico to Alberta, Canada, and are present in all three genetic provenances identified for the species36. Moreover, SI and MC are found on almost every continent and similar comparisons are possible across many species of plants, animals and microorganisms, providing comparable opportunities to examine evolution in response to climate and isolation around the globe.The SI-MC comparison should allow for a greater understanding of the genetic basis to phenotypes that promote population-level persistence in stressful environments and determine the ecological and evolutionary mechanisms  that drive ecosystems to persist globally67. We suggest that the study of SI may be made more robust by studying geographically adjacent MC comparatively to address evolution in direct response to climate change, as opposed to other approaches that infer evolution in response to climate variation. The climatic histories and demographic structure  commonly found on SI, relative to MC, make SI-MC comparisons ideal for future climate change studies across the globe and will allow for direct tests of the role of climate change. Using the SI-MC comparison across a large geographic scale to understand population- and community-level responses to climate change will allow for a better understanding and more robust predictions of climate-driven evolution, and subsequent ecosystem-level responses, across the globe.Previous work detailing the evolutionary responses of species isolated atop individual or adjacent SI has shown the dramatic impact that isolation and climatic exposure on SI can have on a wide variety of taxaPopulus angustifolia James  is a native high-elevation, foundation tree species dominant in riparian areas (900–3500 m) across the intermountain western U.S.68. Throughout its natural range, P. angustifolia forms distinct genetic populations, largely driven by reduced gene flow resulting from variation in the intermountain landscape69. The fragmented contemporary range of P. angustifolia reflects historical bottlenecks driven by Pleistocene glacial cycles, as well as contemporary climate change69. Populus angustifolia extends northwards from northern Mexico into southern Alberta, Canada; a geographic region also characterized by the presence of SI69. Sky islands are isolated mountain habitats surrounded by desert lowlands or habitats outside of the range of species’ thermal tolerance, serving as a barrier to species dispersal and migration13. Conversely, populations of trees from the continuous MC throughout the natural range of P. angustifolia are not dispersal-limited, as the riparian habitat between the high-elevation zones on MC is climatically suitable for within-population windborne seed dispersal and migration. Populus angustifolia exhibits both asexual and sexual reproductive strategies, mostly by cloning and pollen/seed dispersal by wind and water71. Due to the obligate riparian nature of P. angustifolia, populations on SI used in this study constitute distinct populations, devoid of the potential for any significant gene flow36. Isolated SI across the landscape, paired with multiple adjacent MC, serve as natural replication for our study72. In May and June of 2012, 8 watershed populations  of P. angustifolia were surveyed  were georeferenced and sampled and 10 terminal branch cuttings (~ 20 cm long) were collected from each tree. The cuttings were initially established in general potting soil  for 4 months1. Surviving cuttings were replanted in 6.4 × 36 cm plastic pots and grown under identical ambient common garden conditions at the University of Tennessee Knoxville greenhouse.P. angustifolia populations on SI have diverged in stress-adaptive functional traits (Hypothesis 1), cuttings were grown in the University of Tennessee Knoxville greenhouse. All plants in the common garden experienced similar environmental conditions: they were watered every 2–3 days under near-ambient seasonal temperature conditions. This setup allowed for the isolation of the genetic basis to trait variation. In 2012, aboveground biomass (g) was measured from the main stem of each replicated tree genotype using the following allometric equation: Aboveground biomass (g) = (stem volume (mm3) × 0.41899) – 2.40137, whereby stem volume (mm3) = π 2 × plant height (mm)74. In 2016, cloning was quantified from all surviving greenhouse trees by counting the number of ramets present within each pot. Cloning was measured in 2016 as this was the year that cuttings began to produce ramets.To understand how 76. PCR amplification and electrophoresis were executed using previously published techniques1. To control for clonal genotypes, we used the “multilocus matching” function in GenAlEx v.6.478 to identify samples with 100% microsatellite loci similarity.We used microsatellite data to resolve the observed evolutionary patterns in quantitative traits, identify individual genotypes of each tree, and determine population genetic divergence in the study areas. In the field, leaves were collected from each genotype and were dried in a 70 °C oven for 48 h, finely ground using a SPEX SamplePrep 8000D Dual Mixer ; genomic DNA (gDNA) was extracted using a Qiagen DNeasy Plant Mini Kit  following manufacturer’s protocols. To reduce PCR inhibition, the gDNA samples were diluted at 1:10 . We used nine microsatellite markers to determine multi-locus genotypes for each tree79). To address the contribution of elevation to any observed population-level variation and to eliminate the alternative hypothesis that ranges have already shifted, we conducted a linear mixed-effects model with elevation as the response variable, mountain class (SI or MC) as the fixed effect, and watershed as a random effect. Subsequent ANOVAs were conducted for all models.To confirm previously reported climatic differences across the SI-MC comparison, we employed linear mixed-effects models for mean annual temperature (MAT) and mean annual precipitation (MAP) response variables, separately, with mountain class (SI or MC) as the fixed effect and watershed population as a random effect , we used a generalized linear mixed-effects model with a Poisson log link function for the cloning response variable, with mountain class (SI or MC) as a fixed effect, watershed/genotype as a nested random effect. This model was selected to account for the right-skewed cloning count data with a Poisson distribution. For the aboveground biomass response variable, we used a linear mixed-effects model with mountain class (SI or MC) as a fixed effect and watershed/genotype as a nested random effect. Aboveground biomass was log-transformed for normality. For both models in Hypothesis 1, a nested random effect of watershed/genotype was chosen to account for variation at each level . This procedure allowed for a more accurate assessment of any observed SI-MC effect and is a commonly used practice in classical studies in evolutionary ecology with nested design37. To reduce dimensionality and account for loci collinearity, we first performed a principal component analysis (PCA) ordination on the z-scores of the microsatellite data. We then extracted the main principal components that explained the majority of the microsatellite variance (PC1 and PC2). The principal component axes were then added to the quantitative trait mixed-effects models described for Hypothesis 1. To test model fit for each trait, models employed in Hypothesis 1 without microsatellite PC axes were used as null models and were run in parallel with the alternate models that included microsatellite PC axes. Akaike Information Criterion (AIC) estimates were compared between each. For each trait, models containing PC1 and PC2 performed better than the null models without the PC axes, suggesting that genetic drift is present within both populations. For Hypothesis 2, if the observed variation in cloning and aboveground biomass across the SI-MC comparison seen in Hypothesis 1 remained significant after adding the microsatellite PC axes to the models, the evolutionary process driving the trait variation is consistent with adaptive trait differentiation . Conversely, if the observed trait variation becomes insignificant after incorporating the microsatellite ordination axes, neutral and demographic processes  are more likely responsible for trait variation across the landscape81. For all hypotheses, statistical significance (p < 0.05) was determined by Anova Type II Wald chi-square tests for each model  driving trait divergence (Hypothesis 2), we used an ANCOVA approach that incorporated neutral microsatellite data into the mixed-effects models employed for Hypothesis 1Supplementary Information 1.Supplementary Information 2.Supplementary Information 3.Supplementary Information 4.Supplementary Information 5.


Rattus rattus) is a major threat to native biodiversity, effective suppression of pest numbers requires removal and limitation of reinvasion from outside the managed population. We contrasted population genetic structure in rat populations over a wide scale without known barriers, with structure over a fine scale with potential barriers to dispersal. MtDNA D-loop sequences and microsatellite genotypes resolved little genetic structure in southern North Island population samples of ship rat 100 km apart. In contrast, samples from major islands differed significantly for both mtDNA and nuclear markers. We also compared ship rats collected within a small peninsula reserve bounded by sea, suburbs and, more recently, a predator fence with rats in the surrounding forest. Here, mtDNA did not differ but genotypes from 14 nuclear loci were sufficient to distinguish the fenced population. This suggests that natural (sea) and artificial barriers  are effectively limiting gene flow among ship rat populations over the short distance (~ 500 m) between the peninsula reserve and surrounding forest. The effectiveness of the fence alone is not clear given it is a recent feature and no historical samples exist; resampling population genetic diversity over time will improve understanding. Nonetheless, the current genetic isolation of the fenced rat population suggests that rat eradication is a sensible management option given that reinvasion appears to be limited and could probably be managed with a biosecurity programme.Clear delimitation of management units is essential for effective management of invasive species. Analysis of population genetic structure of target species can improve identification and interpretation of natural and artificial barriers to dispersal. In Aotearoa New Zealand where the introduced ship rat (The online version contains supplementary material available at 10.1007/s10530-023-03004-8. Rattus rattus, R. norvegicus, R. exulans) are troublesome pests in Aotearoa New Zealand (Tompkins R. norvegicus) and ship rat (R. rattus) were introduced from Europe and Asia in the eighteenth and nineteenth centuries  is at the entrance to Picton Harbour, adjacent to the port where timber for export is stored. It is on a small peninsular but the adjacent shore is < 500 m away Fig. , which iMost shipping between North Island and South Island comes through the port in Picton Harbour. Therefore if rats were moving between islands, we would expect to detect gene flow from North Island rats among the Picton population samples. Across Cook Strait, in southern North Island, rat populations were sampled from four forested locations within 105 km of one another during 2016 and 2017 Sran : Akatara® chemistry (Perkin Elmer) following the manufacturer’s protocol .DNA was extracted from rodent tails using the Extracta™ DNA Prep for PCR—Tissue (Quanta BIOSCIENCES) following the manufacturers protocol. A tenfold dilution of the resulting DNA solution was used for subsequent polymerase chain reaction (PCR) amplification. Amplification of partial D-loop (585 bp) from the mitochondrial genome used the primers: EGL4L 5′-CCACCATCAACACCCAAAG-3′ and RJ3R 5′- CATGCCTTGACGGCTATGTTG-3′ . Aligned DNA sequences were trimmed, and a dataset was generated comprising one example of each haplotype using DnaSP 6.12.03  with the Markov chain parameters  set to 10,000 iterations. During this exploratory process, five loci were removed from the dataset due to high frequencies of missing data and/or lack of allelic variation.Microsatellite genotypes from ship rat specimens were scored using the Microsat plugin in Geneious. Genetic parameters for each population and each locus were calculated with Fstat 2.9.4 Goudet  and the ST values among population samples were estimated to assess population subdivision, using Arlequin 3.5.2.2 with 99,999 permutations and p values calculated with a significance level of 0.05 and a Bonferroni correction for multiple tests (28 tests: 0.05/28 = 0.00178). For populations at equilibrium statistically significant departures of pairwise FST values from zero indicate restricted gene flow between them. Average numbers of pairwise differences between populations (πXY) and within populations (πX) were estimated using Arlequin 3.5.2.2 with the same settings as FST estimation. A principal component analysis (PCA) was implemented in R 4.0 with the adegenet package 2.1.4  and excluded from further analysis. None of the samples were Norway rats. Similarly, 48 rat samples from North Island were confirmed to be ship rats and no Norway rats were sampled.Partial D-loop DNA sequences were used to confirm the identity of 243 samples. Among the 195 rodents studied from Picton, 193 were confirmed to be ship rats, and two tails were found to have come from house mice (Hd) for these six haplotypes was 0.033 and nucleotide diversity per site (π) was 0.00015.A total of 240 ship rat specimens resolved six haplotypes in a 585 bp segment of D-loop. These six haplotypes were differentiated by four (4/585) nucleotides Fig.  dominateMicrosatellite genotypes were obtained for 133 ship rat specimens whose identity was first confirmed by mtDNA D-loop sequencing. These comprised 85 individuals from Picton (South Island) and 48 from North Island. For each population sample and each of 15 microsatellite loci Table . Linkages = 0.642; Table X (Table IS) provided no evidence of inbreeding within our sampled populations  for all pairwise population sample comparisons were significantly greater than zero, with the highest estimate of FST between North and South Island population samples (Table ST estimates > 0.05) while rats from Wedge Forest were not significantly different from those caught at Victoria Domain and Essons Valley  according to ΔK, but examination of assignment probabilities showed no evidence of two clusters among this set of individuals  from rats in the North Island  is readily apparent from naïve Bayesian clustering and principal component analysis of their genotypes Figs. , 5. Assi km is reGiven that a few rats sampled outside of Kaipupu are genetically similar to the population within the sanctuary, it is conceivable that individual rats are moving out from Kaipupu, however, it is equally likely that these genotypes detected in Victoria Domain and Essons Valley are related to rats that formed the founding population within Kaipupu. There is potential for rats to move in or out of Kaipupu on boats or by swimming the < 500 m water gap King , but ourST values were greater than zero, pairwise genetic difference was similar to within sample variation  would be useful in order to test for changes in allele frequency, but this is rarely achieved. Traditionally, wildlife population genetic analyses are used to infer population sizes and gene flow Frankham  without At Kaipupu, which is a relatively small area (40 ha), an eradication attempt using rodenticides Below is the link to the electronic supplementary material.


Aforementioned results suggested that the 30 autosomal InDels are highly polymorphic and informative, which are suitable for human identification and population genetics.With the characteristics of low mutation rate, length variation and short amplicon size, insertion/deletion polymorphisms (InDels) have the advantages of both short tandem repeats (STRs) and single nucleotide polymorphisms (SNPs). Herein, people of two ethnicities from Hainan Island were genotyped for the first time using the Investigator DIPplex kit. We investigated the forensic parameters of the 30 InDels and the phylogenetic relationships among different populations. The accumulated powers of discrimination and powers of exclusion were 0.999 999 999 9646 and 0.9897 in the Hainan Han population and 0.999 999 999 9292 and 0.9861 in the Hainan Li population, respectively. Additionally, population comparisons among geographically, ethnically and linguistically diverse populations  Four hundred and forty-five Chinese individuals from two ethnicities (Hainan Han and Hainan Li) were firstly analyzed by 30 autosomal InDels included in the Investigator DIPplex panel.Forensic parameters of the 30 InDels in the two populations showed high polymorphism and universality for human identification purposes.The Investigator DIPplex panel had a certain capacity of differentiating intercontinental populations and different language populations. Insertion/deletion polymorphisms (InDels), also known as DIPs, are abundant in the human genome and usually appear biallelic feature, which have attracted the interests of forensic researchers and population geneticists recently . With thhttps://en.wikipedia.org/wiki/Hainan). Based on the 2010 National Population Census (http://www.stats.gov.cn/tjsj/pcsj/rkpc/6rp/indexch.htm), Han (84%) and Li (15%) are the dominant ethnicities of Hainan Island and account for 99% of the island’s population. At the time of the Song dynasty (A.D. 960–1279), large numbers of Han people from the Mainland arrived and settled on Hainan Island. However, according to the literature and archeological studies, scholars believe that the Li people are the original inhabitants of Hainan Island and represent descendants of the ancient Yue tribe, who settled on the island between 7 000–27 000 years ago [Hainan Island, the second largest island in China, is located at the southernmost tip of China, facing the Mainland to the north across the Qiongzhou Strait  and Li % are theSupplementary Table S1.In the present study, we firstly genotyped Han and Li ethnicities from Hainan Island using the Investigator DIPplex kit and evaluated the forensic efficiency of this panel in the aforementioned two populations. Then, we performed population comparisons and genetic structure analysis between the two investigated groups and other previously studied populations based on 30 autosomal InDels. The details of the relevant populations are displayed in A total of 445 blood samples were collected from unrelated individuals (238 Han and 207 Li people) living on Hainan Island with written informed consent. The collection of blood samples was approved by the Ethics Committee of Sichuan University. All participants declared that their ancestors have lived on this island for at least three generations. Genomic DNA was isolated utilizing the PureLink Genomic DNA Mini Kit  and quantified using the Nanodrop-2000C (Thermo Fisher Scientific) following the manufacturer’s recommendations. Then, DNA samples were normalized to 1.0 ng/uL and stored at −20 °C until amplification.2O were used as positive and negative controls for each batch of genotyping. Our laboratory has been accredited by the China National Accreditation Service (CNAS) for Conformity Assessment and ISO 17025. The experimental methods and procedures of this study were conducted according to the approved guidelines of Institute of Forensic Medicine, Sichuan University.The 30 InDels and amelogenin included in the Investigator DIPplex kit were coamplified on a ProFlex 96-well PCR System (Thermo Fisher Scientific) according to the manufacturer’s protocol. Subsequently, PCR products were separated and detected using the Applied Biosystems 3130 Genetic Analyzer (Thermo Fisher Scientific). Allele allocation was carried out using GeneMapper ID-X v1.5 software. Control DNA 9948 (Qiagen) and ddHo), expected heterozygosity (He), matching probability (PM), power of discrimination (PD), probability of exclusion (PE) and typical paternity index (TPI), as well as the Hardy-Weinberg equilibrium (HWE) and linkage disequilibrium (LD) tests were assessed using the online tool of STRAF [Rst) were produced with an online tool Morpheus (https://software.broadinstitute.org/morpheus/). Rst was calculated based on allele frequencies using the PHYLIP 3.695 package. The Rst matrix was then used to implement a multidimensional scaling (MDS) plot via the SPSS software  and construct the neighbour-joining (NJ) tree via the MEGA v7.0 software [K values spanned from 2 to 7 [K value, CLUMPP v1.1.2  and Distruct v.1.1 (Rosenberg Lab) were employed to visualize the population genetic structures.Allele frequencies and forensic parameters, including observed heterozygosity (Hof STRAF . Subsequsoftware . Allele software . PopulatSupplementary Table S2 presents the genotype data of the 30 InDels in the Hainan Han and Hainan Li populations. No significant deviation from HWE was observed in either population after applying the Bonferroni correction (P < 0.0017) (Supplementary Table S3). LD test were performed using a shuffling test for all of the locus by locus pairwise combinations. No significant LD was found in either group, with the exception of HLD93–HLD97 in Hainan Han people after applying the Bonferroni correction (P < 0.0001) (Supplementary Tables S4–S5). The observed significance may represent substructure association, which may be caused by the sample size or genetic admixture [Supplementary Table S3 and o ranged from 0.1092 to 0.5756 in Hainan Han people and from 0.0725 to 0.5942 in Hainan Li people. In both populations, HLD88 possessed the largest PD and the values were 0.6361 (Hainan Han) and 0.6423 (Hainan Li), HLD93 had the highest PE, and the values were 0.2627 (Hainan Han) and 0.2840 (Hainan Li). The combined powers of discrimination and exclusion were 0.999 999 999 9646 and 0.9897 in Hainan Han people and 0.999 999 999 9292 and 0.9861 in Hainan Li people. These results suggested that this panel was effective for personal identification but not sufficiently powerful to perform a paternity test in the two groups.dmixture . The allSupplementary Figure S1), the HLD101, HLD114, HLD39, HLD48 and HLD111 loci showed high deletion frequencies in most East Asian populations, while the HLD118, HLD99, HLD64 and HLD81 loci showed low deletion frequencies in these groups. Moreover, three African populations  displayed high deletion frequencies at the HLD06, HLD124, HLD77, HLD125, HLD58, HLD40 and HLD45 loci and low deletion frequencies at the HLD101, HLD114, HLD128, HLD131, HLD39 and HLD70 loci. In brief, there were significant differences in allele frequency distribution between populations from different continents .To gain an overview of the genetic similarities and differences between our studied populations and 56 global populations , while the Hainan Li population had the smallest Rst with the Vietnam group (Rst = 0.0040). Both showed the highest Rst with the African Nigeria population, and the values were 0.1878 (Hainan Han) and 0.2059 (Hainan Li), respectively. As demonstrated in Supplementary Figure S3(A), our studied populations and most East Asian populations were located at the right part of the y-axis, West Asian and European populations were distributed in the second quadrant, and most American and African populations were scattered in the third quadrant. A PCA plot ) showed that the population distribution pattern was similar to the MDS, and the top two components could explain 74.01% of the total variance (PC1: 55.85% and PC2: 18.16%). Our studied populations and the East Asian populations were separated from other continental populations and had the greatest genetic differences from the three African populations . Furthermore, the six Xinjiang minorities were situated between the other East Asian and European populations, in accordance with our previous study [Supplementary Figure S3(C)), three main branches were observed. The lower branch included Brazil and four African populations, the middle one contained six American groups, and the upper one was split into two subclades. Our studied populations and the East Asian populations clustered in the upper subclade, while the lower subclade consisted of the West Asian, European, Afrikaner and Southern Brazil populations. To sum up, the results of MDS, PCA and phylogenetic tree were consistent with each other.As shown in us study . As showSupplementary Figure S4 presents the cluster heatmap of deletion allele frequencies among the 30 populations, and three primary clusters  were easily distinguished. Cluster I was divided into two subclusters (IA and IB); the IA subcluster included five Tibetan groups, and the IB subcluster consisted of the Han, Bai, Tujia, Hui, Xibe, Dongxiang, She, Salar and Liangshan Yi populations. Cluster II contained the Hainan Li, Gaoshan, Zhuang, Miao, Dong and Yunnan Yi populations. In cluster III, there were six Xinjiang minorities. The Hainan Han population had a similar frequency pattern to the other Han, Hui and Tujia populations, while the Hainan Li population had a similar frequency pattern to the Gaoshan, Zhuang and Miao populations.For the purpose of obtaining a clearer insight into Chinese population relationships, we performed various analyses among our studied populations and 28 Chinese populations ,22,24–33Supplementary Table S6 and Supplementary Figure S5, the Hainan Han population had relatively small Rst with the other Han, Hui and Tujia populations, while the Hainan Li population had genetic affinities with the Zhuang, Dong and Gaoshan populations. Both had distant genetic relationships with the six Xinjiang groups. In x-axis. The Hainan Han population clustered with the Tujia, Bai, She (Hmong-Mien-speaking population) and Sinitic-speaking populations, while the Hainan Li population had close genetic relationships with the Zhuang (Tai-Kadai-speaking population) and Miao (Hmong-Mien-speaking population) groups. In our PCA plot  and the Miao group. In the NJ tree  and could also distinguish different language populations to a certain extent . For our investigated populations, the Hainan Han population had close relationships to the other Han, She and Tujia populations, and the Hainan Li population had genetic affinities with the Zhuang and Miao minorities.Click here for additional data file.