Agrilus mali Matsumura is a wood-boring beetle that aggressively attacks species of the genus Malus, that has recently caused serious damage to the wild apple tree M. sieversii (Lebed.) in the western Tianshan Mountains in Xinjiang. It was first detected there in the early 1990s and spread rapidly, being thus considered a regional invasive pest. To explore the possible outbreak mechanism of the local population and characterize the genetic differentiation of A. mali across different regions of China, we used three mitochondrial genes  to investigate the genetic diversity and genetic structure of 17 A. mali populations containing 205 individuals collected from five Chinese provinces. Among them, nine populations were from the western Tianshan Mountains. Ultimately, of the 136 pairwise Fst comparisons, 99 showed high genetic differentiation among overall populations, and Tianshan populations exhibited significant differentiation with most of the non-Tianshan populations. Furthermore, A. mali populations represented relatively abundant haplotypes (54 haplotypes). Nine populations from the Tianshan Mountains showed 32 haplotypes (26 of which were unique), displaying relatively high genetic diversity. Additionally, the Mantel test revealed population genetic differentiation among either overall populations or the Tianshan Mountains populations, likely caused by geographical isolation. Phylogenic relationships showed that all populations clustered into three clades, and Tianshan Mountains populations, including CY, occupied one of the three clades. These results suggest that A. mali in the western Tianshan region has possibly been present in the area for a long period, and may not have been introduced recently. Highly frequent gene flows within Tianshan populations are possibly caused by human activities and may enhance the adaptability of A. mali along the western Tianshan Mountains, leading to periodic outbreaks. These findings enhance our understanding of jewel beetle population genetics and provide valuable information for pest management. Agrilus mali Matsumura (Coleoptera: Buprestidae) is a serious wood-boring beetle and considered to originate in Northeast Asia, including North Korea, the Russian Far East, and Eastern China , in the wild fruit forests of the Tianshan Mountains, Xinjiang, Western China  of this beetle were investigated genetically based on seven simple sequence repeat (SSR) markers, with the Tianshan populations revealing high genetic similarity and showing significant differentiation when compared with the Liaoning population . Owing tCOI), cytochrome oxidase subunit II (COII), and cytochrome b (CytB) are ideal molecular markers for evolutionary analysis. In the present study, the geographical pattern of genetic variation for this species was assessed using the above three mtDNA genes  from 17 populations across China. The main purposes were to (i) analyze the genetic structure of A. mali, (ii) infer the demographic history of A. mali, and (iii) discuss the genetic status of populations in the western Tianshan Mountains. By comparing the genetic structure of populations from different habitats, we attempted to understand the relationships between populations and evaluate factors that may affect genetic variation. Information on the genetic diversity of A. mali populations may increase our knowledge of these beetle populations and enhance their effective control.mtDNA plays an important role as a basic tool in insect ecology and genetic studies . Accordiin vitro at room temperature. Once adult beetles emerged, they were placed into the centrifugal tubes and stored at −80°C prior to DNA extraction. Genomic DNA was extracted from an individual without the abdomen and elytra using a TIANamp Genomic DNA Kit  according to the manufacturer’s instructions. Voucher specimens were deposited at the insect museum of the Chinese Academy of Forestry, Beijing, China. Hundreds of A. mali adult individuals were obtained from 17 locations in China  were utilized as molecular markers in the present study. Based on the published mitochondrial genome sequence of A. mali , and extension at 72°C for 30 s; and a final elongation at 72°C for 1 min. The PCR products were visualized on 1.0% agarose gels under UV light. The sequencing reaction was carried out using an ABI BigDye Terminator version 3.1 cycle sequencing kit on an ABI 3730XL  for Sanger sequencing in both directions.Polymerase Chain Reaction (PCR) amplification was conducted in a total volume of 25 μl containing 1.5 μl genomic DNA, 1 μl each of forward and reverse primers (10 μmol/L), 12.5 μl 2× Flash PCR MasterMix , and 9 μl ddHhttps://www.geneious.com)  were inferred from the amino acid alignment. The sequence of each PCG (excluding stop codons) was then aligned individually as per codon-based multiple alignments using the MAFFT algorithm, which was implemented in the TranslatorX online platform  database of National Center for Biotechnology Information (NCBI) using BLASTN. Three mitochondrial gene sequences were analyzed and edited using Geneious R11.1.5 (ous.com)  and MEGAous.com) . Deletioplatform . Subsequplatform . The nucGenetic diversity was estimated by the number of polymorphic sites (S), the number of haplotypes (h), haplotype diversity (Hd), average number of nucleotide differences (K), and nucleotide diversity (π) for concatenated genes, using DnaSP version 5.0  or ArleqCOI, and OM212329–OM212346 for COII. All CytB sequences were also deposited in GenBank under the accession numbers OM264916–OM265120, and haplotype sequences are available in the Zenodo database with a DOI of https://doi.org/10.5281/zenodo.6107571.The haplotype sequences for each gene were exported by DnaSP version 5.0. The haplotype sequences were deposited in GenBank under the accession numbers OM177028–OM177057 for Fst) and gene flow indices (Nm) were estimated using the DnaSP version 5.0  was performed using 10,000 permutations to estimate the hierarchical genetic structure using Arlequin version 3.5  based on sion 3.5 . Two hieTo test isolation by distance (IBD), the pairwise genetic distance and geographical distance (km) matrices between all 17 sampled populations were compared using the Mantel test with 9,999 permutations . PairwisAgrilus planipennis were used as an outgroup. For Bayesian analyses, we analyzed the combined genes based on the GTR + I + G model, which was selected using jModelTest version 2.1.7  using MrBayes version 3.2.5 . The conon 2.1.7 . Then, ton 2.1.7 .To explore the demographic history of different lineages, neutral tests using Tajima’s D  and Fu’sAdditionally, the distribution of pairwise differences (mismatch distributions) between each pair of sequences was analyzed using DnaSP version 5.0  with defCOI:1,395 bp, COII:582 bp, CytB:936 bp). No insertions or deletions were detected in these fragments. To ensure the credibility of the data, we deleted a 186 bp sequence containing the poly-T base in the CytB gene. The nucleotide compositions of the 17 geographical populations were consistent. The obtained combined sequences showed base compositions similar to those reported previously in mitochondrial sequences for other insects, with a heavy bias towards A/T (68.7%), which was in accordance with the mitochondrial nucleotide composition .Every mitochondrial gene displayed several haplotypes, with a total of 30 for π = 0.00398) from the natural forests, while the lowest  was found in the YLN population from plantations. Overall, the genetic diversity of natural forest populations is slightly higher than that of plantation populations  exhibited significant genetic differentiation from other populations. The SY population showed higher genetic differences with other populations, whereas there was a certain gene flow between the BY population and the JZ, YLB, YLK, and YLZS populations, respectively. Additionally, no genetic differentiation was observed between the JZ population and the YL group. The Nm values indicated that frequent genetic flow occurred between the YL group and the JZ population (The pairwise pulation .p = 0.0001) (p = 0.952) , and genetic variation within populations was slightly lower . The Man 0.0001)  while no= 0.952)  between Based on the combined genes, the BI phylogenetic trees displayed three parallel clades: Clade 1 containing YL, JZ, SY, BY (these four populations formed the biggest subdivision), and CY populations (another subdivision); Clade 2 containing CF; Clade 3 containing CF, FX, HM, and PL . Within A. mali across overall populations , most Tajima’s D and Fu’s Fs values  high Hd and low π, iii) low Hd and high π, and iv) high Hd and high π. Most A. mali populations fitted the second category, excluding BY, CF, and CY. According to A. mali. based on our distributions of pairwise differences and neutral test data, which supported that the YL population did not experience recent population expansion. The inference was also not seemly obtained in another previous study (π), which was considered as secondary contacts between previously differentiated allopatric lineages, or attributable to a long evolutionary history in a large stable population .Hd and π are important indicators of genetic diversity. Here, overall populations had high haplotype diversity (from 0.590 to 0.963); however, most of them displayed moderate or low nucleotide diversity (<0.005). us study , and manus study . Yet, foπ = 0.00398), followed by another natural forest site population, YLZ . Those two sites represented a typically dense growth region of the wild apple tree (For the western Tianshan populations, genetic diversity in plantations was slightly reduced compared to that in natural forests. Natural forest populations showed more haplotypes than those seen in plantation populations, even with a similar sampling size , 3. Consple tree , indicatFst values (Phylogeny relationships revealed that the YL and CY populations occupied one of three clear clades, in which three subdivisions could identified, corresponding to three star-liking clusters caused by three ancestral haplotypes, suggesting that YL likely has a long population history. Additionally, although the SY population was included in this clade, we could identify, through haplotype networks, the presence of many mutation steps between the haplotypes of the SY population and the ancestral haplotypes H1 and H19 of the YL group. These occurred a certain degree of genetic differentiation, which was supported by t values .A. mali indicated that the geographic isolation of insects is one of the important factors for genetic differentiation in different populations (A. mali were also reported in a study by The high level of genetic differentiation among all populations of ulations , which wulations , while tulations . Moreoveulations . NotablyA. mali is generally regarded as a sedentary species with a certain natural diffusion ability of up to 35 m (A. mali can reduce gene flow among populations.The population genetic differentiation of a species is not only affected by distance and geographic isolation but also its own biological characteristics and environmental conditions, such as human factors, flight capacity, population size, and habitat specialization . Species to 35 m . The weaA. mali, anthropic movement of infected wood or wood products provides routes for the hitchhiking of live adults and larvae, which may increase gene exchange between populations. The findings of this study also suggest that frequent gene flow between natural forests and plantation populations, which may be caused by human activities, possibly enhanced the adaptability of A. mali along the western Tianshan Mountains and resulted in frequent outbreaks (A. mali in the western Tianshan Mountains.For sedentary insects such as utbreaks . TherefoA. mali is a secondary pest and attacks the weak host tree. In the last few decades, the wild fruit forest in the western Tianshan Mountains gradually declined, probably caused by climatic and environmental factors, which provided a chance for the beetle outbreak. Subsequently, low plant diversity in the undergrowth made the natural enemies of the beetle lose their substitute host, leading to a reduction in population size. For the feeding of livestock, local people had to mow the grass growing in the wild fruit forest. Finally, poor orchard management also facilitated the rapid growth of the beetle population.Considering the outbreaks of the beetle, present in both natural forests and in plantations the Tianshan Mountains, we think that the decline in host forests was the main factor causing the rapid growth in beetle population size, because


Chelonia mydas) in the Cayman Islands as a possible outcome of a reintroduction program started 50 years ago. We show that both populations are highly related to the captive population but rapidly diverged due to genetic drift. Individuals from the reintroduced populations showed high levels of nest fidelity, within and across nesting seasons, indicating that philopatry may help reinforce the success of new populations. Additionally, we show that reintroduction from captive populations has not undermined the reproductive fitness of first generation individuals. Sea turtle reintroduction programs can, therefore, establish new populations but require scientific evaluation of costs and benefits and should be monitored over time to ensure viability in the long-term.Due to changing environmental conditions, many species will have to migrate or occupy new suitable areas to avoid potential extinction in the current biodiversity crisis. Long-lived animals are especially vulnerable and ex-situ conservation actions can provide solutions through assisted colonisations. However, there is little empirical evidence on the process of founding new populations for such species or the feasibility of assisted colonisations as a viable conservation measure. Here, we combined genetics with reproductive data to study the rise of two wild populations of green turtles ( Empirical evidence on the process of founding new populations for assisted colonisations is limited. This work examined two wild populations of green turtles in the Cayman Islands following a reintroduction program started 50 years ago. They show both populations are highly related to the captive population and that philopatry may reinforce the success of new populations. Anthropogenic impacts such as global warming, habitat alteration, and human-mediated dispersal of alien invasive species are some of the main causes of the biodiversity crisis at a global scale2. Ecosystems are being dramatically altered to the point that they are no longer suitable for some organisms3. Consequently, species must either rapidly adapt or move to new suitable habitats to avoid extinction and for this reason, some species are changing their distributions by founding new populations4. However, species with limited potential to adjust their distributions to the new climatic conditions are potentially more vulnerable and thus more prone to extinction6. While adaptation is difficult to predict, range expansions can be detected and even facilitated through reintroductions from ex-situ conservation programs8. Unfortunately, reintroductions from captive breeding programs are rarely evaluated to assess their longer-term success11. This evaluation is crucial, as reintroduced individuals can display reduced reproductive success and newly founded populations can suffer reductions of genetic variability due to the founder effect. The foundation process of new populations was theoretically described in the last century12, however, few studies have provided empirical data and most of them have focused on short-lived organisms13.The rate of biodiversity loss has accelerated during the last decade14. As reptiles, sea turtles are strongly influenced by temperature16, and have Temperature-dependent Sex Determination (TSD) with rising temperatures causing the feminization of nesting populations16. Modelling studies have predicted a potential collapse of some existing nesting populations due to environmental change, and at the same time new areas would become potentially suitable for nesting19. While sea turtles are highly migratory species20, their potential to colonise new nesting areas is thought to be limited due to their philopatric behaviour22. To date, few cases of natural changes in the distribution of sea turtle nesting areas have been detected19 and for this reason, assisted colonisation has been proposed as a conservation tool to conserve populations threatened by anthropogenic activities or to reinforce natural expansion processes23.The study of founding processes in long-lived vertebrates is challenging, but essential in the current era of global biodiversity decline, as these species are potentially highly vulnerable to habitat alterations, may have slow responses to environmental change and are potential targets for assisted colonisation programsChelonia mydas) reintroduction program offers a unique opportunity to study the process and consequences of assisted colonisations in sea turtles. The local green turtle nesting population was considered nearly extinct24 but the number of nesting females has increased exponentially in Grand Cayman over the past 20 years25, partially as a result of the reintroduction program initiated in 1983 from the Cayman Turtle Farm (CTF) (now the Cayman Turtle Conservation and Education Centre Ltd.)27. This reintroduction was based on releasing captive-bred green turtles from the island of Grand Cayman where the CTF is based , the foundation and differentiation process of these populations, including the role of philopatry, and any potential effect of the reintroduction on individual fitness.The Cayman Islands green turtle  and to infer potential unsampled mothers for the remaining unassigned clutches (n = 171) . These results confirm that the nesting populations of these two islands are mainly the result of an assisted colonisation through individuals from the captive breeding program.Here we present genetic and ecological data from three to four generations of green turtles collected across three different stages of the assisted colonisation process  Fig. . By iden71) Fig. , with no29 and were present in the CTF captive population at different frequencies. The degree of differentiation found between these three populations in only a very few generations suggests that genetic drift during the founder process has been a strong evolutionary force on our populations, able to drive genetic differentiation over small temporal and spatial scales. Selection is unlikely to have played a major role in this differentiation process, as the two islands are separated by only 108 km and have similar environmental conditions. Only strong and opposite selection coefficients could explain such differentiation in a few generations. Previous studies have suggested that philopatry is one of the main drivers of the deep genetic structuring found in sea turtles, as this behaviour reduces gene flow significantly among populations. Therefore, mutation, selection and genetic drift across many generations would generate differentiation among isolated sea turtle populations over extended evolutionary scales30. Here, we demonstrate that genetic drift during founding processes can have also an important role in generating significant genetic structuring in sea turtles in only one generation after the foundation of new populations. After this initial potential differentiation by genetic drift during the founder process, philopatry is expected to increase this differentiation in the future by maintaining the isolation of populations across generations.Although maternity and sibship analysis allow us to reconstruct the family pedigree, the measure of genetic difference between nesting groups reflects the evolutionary differentiation process of the new populations. The observation of this process in its very first phases is crucial, not only to set the baseline for future assisted colonisation projects, but also because its detection in long-lived, migratory vertebrates is rare. In the case of the Cayman Islands, despite the high degree of relatedness of both nesting populations to the CTF, significant genetic differences were found among the three groups, especially with biparentally inherited markers  on both islands to assess the degree of nest-site fidelity by combining parentage analyses and nesting information. This analysis aimed to understand the role of nest-site fidelity in the differentiation of philopatric species within the wider context of an assisted colonisation. To do so we used nest geographic coordinates to calculate the distances between nests laid by the same female in the same and different nesting seasons (see Methods).Philopatry limits the colonising potential of specific organisms but ensures reutilisation of suitable habitats, reinforcing population growthWild females concentrated their nesting activity in certain areas Fig.  and the 34. Furthermore, we did not find any significant impact of female heterozygosity  or CTF relatedness  on within-season mean distance, or on maximum distance . These results suggest that the reintroduction program might not influence nesting distance and that long-distance nesting events are more likely the result of stochastic processes.Females nesting on the two islands could reflect an actual failure in finding the natal beach or be a consequence of external disturbance during nesting. Nonetheless, long-distance nesting (either on the same or different islands) could also be an evolutionary strategy that maintains gene flow and avoids collapse due to extreme philopatry. Recent research on within-season nest-site fidelity using genetic and satellite tracking highlights that long-distance nesting appears to be more common than previously described36. Sea turtles, as with many other reptile species, exhibit Temperature-dependent Sex Determination with a greater proportion of female offspring produced at temperatures above the pivotal temperature (~29 °C)38 and a greater proportion of males produced at temperatures below this. In the Cayman Islands wild breeding adults, we did not detect female skewed sex ratios. The minimum genetically estimated breeding population size was of 121 females and 114 males . Similar sex ratios were obtained by analysing each island independently  we ran Linear Mixed-Effects Models with particular focus towards individual heterozygosity, and relatedness to the CTF. As described in previous studies26  individuals of external contribution (i.e. migrations from other populations); ii) individuals of the original wild population still nesting in the Cayman Islands; or iii) adult captive turtles escaped after Hurricane Michelle damaged the CTF facility in 2001. Unfortunately, these different hypotheses will remain untested, since genetic data from the original population and the initial CTF founder stock are not available.When we compared heterozygosity values of hatchlings related and unrelated to the CTF, with the adult wild population and the subgroups of the CTF  and F1(1995))26 Fig. , related43, translocations and assisted colonisations seem a viable option for species facing challenging dispersal barriers5. Our results show that assisted colonisations as a conservation measure could possibly be used in sea turtles and might be adapted to other long-lived, migratory and philopatric species. Where habitat degradation undermines species survival14, assisted colonisations might become an important future strategy to prevent extinctions for some species5. However, decision-making must include factors such as risk of decline or extinction under climate change, the technical possibility of the translocation and establishment of the species, and assessment of whether the translocation benefit outweighs biological and socioeconomic constraints14. In this study, we show that assisted colonisation can establish sea turtle nesting populations and we also provide insight on factors related to feasibility and long-term viability. For sea turtles, important considerations for captive breeding include animal husbandry and welfare concerns, the potential for disease transfer through the release of animals from an intensive-rearing facility into the wild, high costs, and apparently low rates of recruitment of captive-bred individuals into wild nesting populations25. In this study, we showed the results from more than 25,000 yearling and hatchling turtles released in the 1980s27. This assists in elucidating the timescale and costs of establishing viable wild turtle nesting populations through assisted colonisation.As extinction risk projections predict an increasing number of species committed to extinction due to global warming5. In the case of the Cayman Islands, this aspect was not considered and individuals from distant populations were incorporated to the breeding stock.For all species, potential implications for the welfare of both captive and wild animals, dictate that thorough scientific assessments must underpin each step of assisted colonisation projects. For this reason, the study of the foundation of new populations using a multidisciplinary approach is crucial to improve assisted colonisations and to tailor conservation action plans to the target species. In fact, a careful study of the species and the colonisation area prior to the reintroduction is necessary to ensure the survival of translocated individuals but also to determine the potential impacts that the colonisation may have on the host ecosystemThe scientific study and ongoing monitoring of conservation actions is just as important as their initial implementation and, in the case of the Cayman Islands, the impact of the captive breeding program on other Caribbean populations should be assessed in the future. The CTF reintroduction program raised concerns about its effectiveness, its suitability to recover the population and its economic costs. Despite controversies surrounding the Cayman Turtle Farm outcome, detailed analyses have shown how this attempt started almost 50 years ago was successful in contributing captive-raised individuals to the wild and that the first wild generations are fit to survive in their natural habitat. We show how the study of the foundation of new populations in vertebrates with complex life histories, such as marine turtles, can also provide relevant information on the generations required to establish a genetically differentiated new population or potential alterations of fitness. Assisted colonisation has shown potential in protecting a complex and highly migratory species in response to a critical population decline. However, ex-situ strategies should not replace, but aid in-situ conservation, and the latter should be considered as a conservation management priority before resorting to complicated, costly and controversial ex-situ conservation strategies.25, these hatchlings can be considered to be the first generation after the foundation of the new wild population. For nests assigned to a sampled wild female (see results) we gathered information regarding nesting date and GPS location from the DOE database as well as the total number of hatched and unhatched eggs, following standard procedures39, and the presence of an embryo in the unhatched eggs, as checked visually. Using these parameters, for each clutch we estimated the fertilization success, expressed as the proportion of the eggs that hatched or developed an embryo and the viability, expressed as the proportion of eggs hatched from those that hatched or developed an embryo (Supplementary Data n = 25) were used as a control for genetic parentage identification. Samples were taken from the hatchling’s margin of the carapace and up to three hatchlings per nest were sampled. Samples were obtained with a scalpel blade and stored in 100% ethanol.This research complies with all relevant ethical regulations, including research and environmental regulations from the Cayman Islands Department of Environment and Cayman Islands Government. Sampling and data collection are regularly performed by the DOE to monitor nesting beaches of marine turtles on the islands of Little Cayman and Grand Cayman, in the Caribbean. Samples for this study were collected from 320 nests laid in Grand Cayman and Little Cayman Fig.  during 244 using the same protocols used in the previous studies26. In summary, microsatellite loci were amplified with two multiplex PCR sets with fluorescent dye labelled primers . Each multiplex was amplified in a final volume of 5 μl, with 2.5 μl of Multiplex PCR Master Mix (Qiagen), 1.5 μl of primer mix and 1 μl of DNA. After amplification, 15 μl of ultrapure H2O Ecolab was added in each reaction tube and amplification success was assessed in an agarose gel. Microsatellite allele sizes were estimated in 2 μl of diluted amplified DNA, 0.5 μl of GeneScan 500 Liz Size standard (Applied Biosystems) and 12.5 μl of deionized formamide on an ABI 3730 DNA Analyzer (Applied Biosystems) at the Serveis Científico‐Tècnics of the Universitat de Barcelona, and alleles were assigned using Genemapper v3.7. We sequenced 81 individuals for 800 bp of the D-Loop mitochondrial DNA using published protocols26. To summarize, the fragment was amplified in a reaction volume of 15 μl containing 5.08 μl of deionized water, 3 μl of PCR buffer 5× (GoTaq Promega), 1.8 μl of dNTPs (1 mm), 0.6 μl of MgCl2 (25 mm), 1.8 μl of bovine serum albumin, 0.3 μl of forward primer (10 μm), 0.3 μl of reverse primer (10 μm), 0.12 μl of GoTaq G2 Flexi DNA Polymerase , and 2 μl of DNA. The amplified DNA was purified with Exo‐SAP (2 μl containing 0.4 U of EXO and 0.4 U of TSAP) using a single cycle of 37 °C for 15 min and 80 °C for 15 min. Then, 1 μl (5 μm) of the forward primer was added to the purified product (LCM15382) and dried at 80 °C for 30 min in order to be sequenced on an ABI 3730 automated DNA analyser (Applied Biosystems) at the Serveis Científico‐Tècnics from Universitat de Barcelona. Haplotypes were assessed (Supplementary Data 45 by comparison to the haplotype database maintained by the Archie Carr Center for Sea Turtle research (https://accstr.ufl.edu/).The DNA of one hatchling sample per nest was extracted using the QIAamp Blood and Tissue Kit (Qiagen®) or using E.Z.N.A.® Tissue DNA kit (OMEGA Bio-tek), following the manufacturer’s protocol. All samples were genotyped at 13 microsatellite loci . The CTF breeding stock dataset included original founders of the captive population (n = 25), a first-generation cohort of breeders born in 1995 corresponding to a single cohort breeders replacement strategy (F1(1995), n = 189, previously mentioned in the literature as C199526) and a multicohort group of first-generation breeders corresponding to a continuous replacement strategy (F1(mixed), n = 43, previously mentioned in the literature as MCF126)  Fig. . Thus, c47, which performs parentage assignment and reconstructs genotypes for unsampled parents, allowing the identification of family groups with sampled and unsampled females and males. We set the parameters to long run, high precision and error rate = 0.0001. All hatchlings were included in the analysis as offspring and the genotypes of 57 wild adult females from a previous study26 were included as mothers. We used D-loop mtDNA information to build two exclusion files. The first one contained female-offspring pairs with different mtDNA haplotypes, as a hatchling cannot be the offspring of a female with a different haplotype. The second exclusion file contained sib-sib pairs with different mtDNA haplotypes, as two hatchlings cannot be mother siblings if they have different mtDNA haplotypes. These two exclusion files were included in the input of the program to refine the assignment. We checked the accuracy of COLONY by comparing the output with 25 female-offspring known pairs recorded during field observations  were included in these analyses as a control to assess the reliability of the programs. A total of 131 hatchlings were assigned a wild mother previously found to be related to the CTF. Of these, 120 hatchlings were confirmed as related to the CTF by the two relatedness programs, and 11 hatchlings were only confirmed by ML-Relate as half siblings of CTF individuals. We calculated the proportion of hatchlings related to the CTF for Little Cayman and Grand Cayman and tested for significant differences between islands with a Chi-squared test with Yates’ continuity correction with R52.In order to understand the impact of the CTF reintroduction program on the two populations we computed Queller and Goodnight relatedness estimatorST and statistical significance through 999 permutations using GENALEX46. A previous study26 found deviations of Hardy-Weinberg Equilibrium within the farm that are the result of the CTF breeding program . However, these deviations did not come from null alleles and thus are not expected to overestimate FST values. In order to have additional support for genetic differentiation, we performed a Discriminant Analysis of Principal Components with the R package adegenet v2.1.553 using microsatellite markers, retaining 128 PCAs. The mitochondrial haplotype frequencies extracted from 74 independent nests  were also used to calculate pairwise FST values between groups of samples, and significance  was assessed through an exact test using Arlequin v5.254. A previous study using the same set of markers55 showed that our mitochondrial marker has the statistical power to reliably detect differentiation on FST values above 0.01 and our set of microsatellites can reliably detect differentiation on FST values above 0.0025.To identify early signs of genetic structuring, we tested the level of genetic differentiation between the hatchlings sampled in Grand Cayman and Little Cayman and the CTF adult females using both nuclear and mitochondrial markers. As several nests were found to be laid by the same female (see Results), we used only one random nest per female laid during the same nesting season to avoid pseudoreplication. Using microsatellites, we calculated pairwise Fn = 27) using geographic coordinates of their nests within the same season. Distances between nests were obtained by measuring the coastline between the geographic coordinates of consecutive nests using Daft Logic , an online tool to calculate distances with Google satellite maps. We used two different measures of NSF: the mean distance between consecutive nests and the maximum distance, that is the distance between the two most distant nests laid by the same female within a season. We also analysed interseasonal nest-site fidelity of 8 wild females found to lay nests in more than one nesting season. We used the same tool to calculate the geographic distance between nests laid by the same female in different seasons.With the results of the parentage analysis, we were able to link all the data collected in the field for each nest with an identified mother. We added to the dataset information on 16 female-offspring pairs recorded during night patrols but with no hatchling samples collected and genotyped  on mean and maximum distance.In order to assess any potential effect of females’ heterozygosity on NSF we performed a generalised linear model in R56 with R52 to evaluate the significant difference in the number of males and females that would indicate skewed sex ratios.The parentage analysis performed by COLONY also provided the number of males and females that produced the offspring sampled on both Cayman Islands during the different nesting seasons. These data allowed us to estimate the minimum breeding population size across seasons. We added to the count three of the eight females recorded nesting during night patrols, which were not included in the genetic census because they had no nest assigned with genetics , and viability of the clutch (i.e. proportion of eggs that hatched from fertilized eggs) (supplementary information: Table Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary InformationSupplementary Data 1Supplementary Data 2Reporting Summary


Migration of a population from its founder population is expected to cause a reduction of its genetic diversity and facilitates differentiation between the population and its founder population, as predicted by the theory of genetic isolation by distance. Consistent with that theory, a model of expansion from a single founder predicts that patterns of genetic diversity in populations can be explained well by their geographic expansion from their founders, which is correlated with genetic differentiation.To investigate this in chicken, we estimated the relationship between the genetic diversity of 160 domesticated chicken populations and their genetic distances to wild chicken populations.Our results show a strong inverse relationship, i.e. 88.6% of the variation in the overall genetic diversity of domesticated chicken populations was explained by their genetic distance to the wild populations. We also investigated whether the patterns of genetic diversity of different types of single nucleotide polymorphisms (SNPs) and genes are similar to that of the overall genome. Among the SNP classes, the non-synonymous SNPs deviated most from the overall genome. However, genetic distance to the wild chicken still explained more variation in domesticated chicken diversity across all SNP classes, which ranged from 83.0 to 89.3%.Genetic distance between domesticated chicken populations and their wild relatives can predict the genetic diversity of the domesticated populations. On the one hand, genes with little genetic variation across populations, regardless of the genetic distance to the wild population, are associated with major functions such as brain development. Changes in such genes may be detrimental to the species. On the other hand, genetic diversity seems to change at a faster rate within genes that are associated with e.g. protein transport and protein and lipid metabolic processes. In general, such genes may be flexible to changes according to the populations’ needs. These results contribute to the knowledge of the evolutionary patterns of different functional genomic regions in the chicken.The online version contains supplementary material available at 10.1186/s12711-021-00628-z. Gallus gallus domesticus) are one of the most widely distributed domestic animal species in the world. This is in part because of their portability and flexibility of transportation through human migration, stock trading, and expansion in the agricultural practices \document}FST) in ) between}FST) in  and 0.75}FST) in  for anci}FST) in .Fig. 1ReG. gallus) and the 2 value of 0.99. When using G. gallus) explained 88.5% of the variation in Since we had different sample sizes, with some populations having less than 15 sampled individuals, we checked whether this affected the estimates. We estimated entclass1pt{minimaentclass1pt{minimaentclass1pt{minima2 = 0.01). Second, we estimated the regression of 2 value of the linear regression was directly associated with the 2 values and vice versa. We found that although there was some association between the populations’ 2 values (Pearson’s correlation of 0.35), it was not very strong. R2 values for the regression of 2 values than the two wild populations, of which 25 of them are of Asian origin and only four (Albanian Crowers (ALxx), Hungarian Yellow (YH), Schweizer Huhn (SCw) and African Kuroiler (KUR)) are of non-Asian origin, based on our classification (3 European and 1 African). However, the four were all clustered with Asian populations [2 values (e.g. 0.74), none of them were higher than the regression based on geographic distance from Ethiopia (the possible founder origin) with an R2 = 0.76. However, other locations in Africa had R2 values higher than Ethiopia (e.g. R2 as high as 0.87) [Gallus gallus subspecies that we included in our study is that the samples were not from naturally existing populations in the wild. Instead, they were sampled from small populations that have been isolated for years, therefore they may have a reduced genetic diversity, which reduces their explanatory power of the genetic diversity  was weaker within the Asia_local group than within the rest of the other groups, see Additional file 2 values and regression coefficients. The South_America category was not included in this analysis since it consisted of only four populations. Genetic distances of the Asian local populations to the wild populations were generally shorter than those of the other groups, in particular the European breeds and Asian fancy breeds. Not only is intercrossing common among Asian local breeds, which promotes high genetic diversity, but there is also a high probability of gene flow between the wild populations (RJF) and local chickens in Asia, as reported in some studies e.g. [G. gallus is more rapid compared to their respective local populations . Although our results may not directly prove this, because of the lack of geographic sampling coordinates, given the whole dataset G.gallus) are much larger than those of their respective local breeds. However, when considering the sampling areas, the genetic diversity may correlate to the geographic distances to the G. gallus wild chicken within the Asian breed categories. Presumably, many of the fancy breeds originated from a small number of breeding birds that were imported from Asia to Europe, after which they were subjected to strong phenotypic selection, with small effective population sizes, population bottlenecks, and intensional inbreeding to keep the desired traits. These practices are likely responsible for most of the differences in the genetic diversity of the fancy Asian and European type breeds vs. their respective local types.Breeds of the same geographic origin are scattered across the genetic diversity spectrum, in particular, the European (green symbols) and Asian (red symbols) type breeds, as shown in Fig. (ii)The concept of isolation by distance assumes that individuals from nearby locations are likely related because mating between them is possible. This is often the case for traditional breeding systems but not for breeding and management practices for fancy breeds. In fancy breeds, gene flow between small stocks may occur based on personal contacts or personal relationships between breeders, but is not related to geographic distance forming a subpopulation structure within the breed. Actually, such gene flow between fancy breeds is also very limited. Furthermore, if geographic distance was a better predictor for the loss of genetic diversity and increased differentiation of domesticated breeds to the wild populations, then the African and South American breeds would be expected to have a much reduced genetic diversity due to their geographic distances and to show large genetic distances to the wild populations and to the rest of the Asian populations. However, we found that both these expectations were not fulfilled and that some of the African populations were clustered with the wild type populations .Based on our results, we can conclude that the variance in mentclass2pt{minimTherefore, the observed differences in genetic diversity between domesticated breeds may not be predicted by geographic expansion only, but rather by a combination with other aspects or subsequent events, such as effective population size, type of breeding practices, and possibly subsequent series of founder events following the geographic expansion, as previously suggested , 6. SuchGallus gallus obtained by using the whole set of SNPs to those obtained by using different SNP classes, as shown in Fig. o for the set of non-sysnonymous SNPs in Additional file We compared the patterns of the relationship between mentclass2pt{minimmentclass2pt{minim2 values ranging from 83.0 to 89.3%. The results indicated that 89.3% and 88.0% of the variation in G. gallus for the synonymous and non-synonymous SNPs, respectively, while this percentage was lowest (83.0%) for the class of 5′UTR SNPs. However, it is important to note that the 5′UTR class included only 118 SNPs, which could explain the differences. To test this, we sampled 118 random SNPs in 100 replicates from the overall set and estimated the relationship, as we have done for the non-synonymous SNPs. The R2 for the 100 replicates ranged from 76.0 to 86.6%, with a mean of 82.8%, which suggests that the result for the 5′UTR class is most likely an artifact due to the small number of SNPs.The intergenic and intronic classes had the highest proportion of SNPs among all SNP classes Table . In ordeentclass1pt{minimaFigure  humans) , 33. It  humans) . Such ex2) from the linear regression of the genetic distance from the wild ancestor on 2 of 0.47, and the regression coefficients (slopes) ranged from − 0.11 to − 1.19. However, the R2 values were correlated with the number of SNPs genotyped within the gene, with a correlation of 0.57. The regression coefficients were independent of the number of SNPs within genes, with a correlation of 0.03. The correlation between the regression coefficients and R2 values was − 0.52.We investigated the patterns of G. gallus wild chicken and those in the lowest 5% showed very slow changes in o across the breeds, regardless of the genetic distance to the G. gallus wild chicken , regulation of axon extension , and morphogenesis of salivary gland .We evaluated the regression coefficients of the relationship between mentclass2pt{minimplatform  to identmentclass2pt{minimplatform , functioG. gallus can be the result of several factors, as described in the following.(i)GRB2 gene, which had both the lowest slope, i.e. closest to zero (− 0.112) and the lowest R2 value (0.036), is highly conserved and under very strong evolutionary constraints in both chickens and in humans [On the one hand, some genes may be under evolutionary constraints such that the genetic make-up of these genes may be critical for normal development or functioning of the animal and changes within the genes may have detrimental effects. For example, the n humans .(ii)EGFR and STK17A across chicken populations, with reduced nucleotide diversity across populations but without significant genetic differentiation between the populations. Previously, a study of these two genes, along with NDUFA9 and NTF3, in different Mexican chickens suggested an influence of natural (adaptive) selection pressure rather than artificial selection [On the other hand, the genetic diversity of some genes is probably reduced from the founders i.e. selection and fixation of the preferred variants took place prior to domestication, such that there is either no or less possibility for further reductions in genetic diversity. For example, Qanbari et al.  reportedelection .(iii)If an adaptive selection event did not occur prior to domestication, a third explanation is that purifying selection may have continued post-domestication and removed the non-favorable alleles across populations, which led to rapid fixation of the other allele.The consistent lower genetic diversity , and the relationship between G. gallus (right). The regression lines of the relationships are drawn in red. The R2 is equal to 0.885 and 0.988, for the left and right figures, respectively. Different breed categories are denoted in different colors and/or shapes. Figure S3. Comparison of the relationship between the genetic distance to G. gallus and the observed heterozygosity estimated from the non-synonymous class vs. 100 random samples of the same number of SNPs as the non-synonymous class from the overall SNPs. The black dotted lines represent estimations with the overall SNPs, the red solid line represents the non-synonymous SNPs. The shaded areas represent the 95% confidence intervals of the regression lines. The mean R2 of the 100 samples is 0.880 and the mean slope is − 0.708. Figure S4. Comparison of the relationship between the genetic distances to G. gallus and the observed heterozygosity estimated from intronic SNPs vs. the overall set. The black dashed lines represent estimations with the 100 replicates of 1000 randomly samples SNPs from the intronic SNPs and the red solid line represents overall SNPs. The 95% confidence intervals are shaded in gray. The mean R2 and slope of the 100 samples are 0.880 and − 0.711, respectively. Figure S5. Comparison of the relationship between the genetic distance to G. gallus and the observed heterozygosity estimated from intergenic SNPs vs. the overall set. The black dashed lines represent estimations with the 100 replicates of 1000 randomly sampled SNPs from the intergenic SNPs and the red solid line represents overall SNPs. The 95% confidence intervals are shaded in gray. The mean R2 and slope of the 100 samples are 0.878 and − 0.701, respectively.Additional file 3: Table S3. Title: R2 and slope values of the relationship between observed heterozygosity and genetic distance to Gallus gallus ssp. estimated from the 6303 genes.Additional file 4. Relationships between observed heterozygosity and genetic distance to G. gallus for genes in the top 5% slope range.Additional file 5. Relationships between observed heterozygosity and genetic distance to G. gallus for genes in the lowest 5% slope range.


Scylla olivacea  in the Sulu Sea. Dispersal simulations reveal widespread but asymmetric larval dispersal influenced by persistent southward and westward surface circulation features in the Sulu Sea. Despite potential for widespread dispersal across the Sulu Sea, significant genetic differentiation was detected among eight populations based on 1,655 SNPs  and a subset of 1,643 putatively neutral SNP markers . Oceanography influences genetic structure, with redundancy analysis (RDA) indicating significant contribution of asymmetric ocean currents to neutral genetic variation . Genetic structure may also reflect demographic factors, with divergent populations characterized by low effective population sizes (Ne < 50). Pronounced latitudinal genetic structure was recovered for loci putatively under selection , significantly correlated with sea surface temperature variabilities during peak spawning months for S. olivacea , suggesting putative signatures of selection and local adaptation to thermal clines. While oceanography and dispersal ability likely shape patterns of gene flow and genetic structure of S. olivacea across the Sulu Sea, the impacts of genetic drift and natural selection influenced by sea surface temperature also appear as likely drivers of population genetic structure. This study contributes to the growing body of literature documenting population genetic structure and local adaptation for highly dispersive marine species, and provides information useful for spatial management of the fishery resource.Connectivity of marine populations is shaped by complex interactions between biological and physical processes across the seascape. The influence of environmental features on the genetic structure of populations has key implications for the dynamics and persistence of populations, and an understanding of spatial scales and patterns of connectivity is crucial for management and conservation. This study employed a seascape genomics approach combining larval dispersal modeling and population genomic analysis using single nucleotide polymorphisms (SNPs) obtained from RADseq to examine environmental factors influencing patterns of genetic structure and connectivity for a highly dispersive mud crab  Scylla olivacea in the Sulu Sea, Philippines. We report significant genetic differentiation found using mostly neutral markers despite potential for widespread connectivity as indicated by the model simulations. Our study also highlights the pattern of latitudinal genetic structure as revealed by the outlier loci, suggesting local adaptation to environmental clines such as sea surface temperature.This research presents a seascape genomics approach using combined biophysical modeling and RADseq data to examine the genetic structure of a highly dispersive mud crab  For marSeascape genomics studies have improved our understanding of the environmental conditions influencing population connectivity and the spatial distribution of genetic variation in the ocean. The ability to interrogate population diversity using thousands of SNPs, and to identify loci which may be under the influence of selection versus neutral loci  following the description of Keenan et al.  being the most abundant  in the Sulu Sea basin. Using a seascape genomics approach, we aimed to: (a) characterize genetic structure of S. olivacea across the Sulu Sea and examine spatial patterns of genetic connectivity using SNP markers generated by RADseq; (b) examine the influence of oceanographic circulation on genetic structure and connectivity of S. olivacea populations in the Sulu Sea; and (c) examine the SNP dataset for signatures of local adaptation, which may be correlated with other environmental factors. First, we developed a biophysical model of larval dispersal parameterized using the life history characteristics of S. olivacea, to generate realistic predictions of larval dispersal and connectivity in the Sulu Sea. We combined larval dispersal estimates with empirical genetic observations at neutral loci to determine the influence of asymmetric ocean currents on spatial patterns of connectivity. Second, we performed analyses to recover loci putatively under selection to examine signatures of local adaptation. We assessed the potential impact of environmental factors, specifically sea surface temperature and rainfall  on adaptive divergence of S. olivacea. The results of this study provide valuable insights into the spatial scales of dispersal, patterns of genetic structure, and the influence of environmental and evolutionary processes on population connectivity of S. olivacea in the Sulu Sea basin, to support the development of management and conservation strategies for the fishery resource.This study examined patterns of connectivity among populations of the orange mud crab  were collected from natural mangrove habitats from 8 sites in the Sulu Sea and 2 outlier locations between 2016 and 2017  using a NanoDrop™ spectrophotometer.Adult acea n = 46 were c17 Table . Tissue 17 Table , and sto17 Table . DNA was2.3MluCI and MspI and purified using AMPure XP (Beckman Coulter). Custom‐barcoded adapters P1 and P2  libraries were prepared according to Peterson et al. . DNA extn et al.  for sequ2.4process_radtags in STACKs v2.2  was set to 5 (default: 3), and the maximum distance (in nucleotides) allowed between stacks (−M) and the number of mismatches allowed between sample tags when generating the catalog (−n) were increased to 4 (default: 3) to increase the SNP calling confidence and to minimize missing data , and exclude loci that were not present in at least 50% of the individuals for each population (−r = 0.5).Sequence libraries were initially demultiplexed using the internal barcodes, while reads with low‐quality scores, uncalled bases, and sequences with intact adapters were removed using the module poppr v2.8.3  in at least 50% the populations (5 or more populations) were excluded. To limit the influence of nonindependent loci, linkage disequilibrium (LD) was tested between all SNP pairs using the package genetics v1.3.8.1.2  were removed  were also dropped from the dataset  outlier detection methods, which use different underlying models: BayeScan v2.1  limit were considered as putative outlier loci. OutFLANK uses a maximum‐likelihood approach to generate the STF distribution of neutral loci by trimming extreme values  all loci; (b) putatively neutral loci; and (c) putative outlier loci only, hereafter referred to as all, neutral, and outlier loci, respectively. For putative function annotation, consensus tags associated with candidate outlier loci were queried for sequence similarity against the NCBI nucleotide (nr/nt) collection using the BLAST algorithm BLASTN v2.6.1  and between populations (pairwise STF), calculated using the R packages hierfstat v0.04‐22  were used to examine genetic differentiation and infer connectivity among populations. We used Weir and Cockerham's FST  to estimadegenet v2.1.3 , maximum number of nuclei in the Poisson–Voronoi tessellation process fixed to 438 (N multiplied by 3), and individual samples from each location that were set to the same spatial coordinates. Postprocessing of MCMC outputs generated a final estimate of K, which was used as the maximum number of populations in succeeding runs performed with 10 independent replicates. Individual runs were ranked, and the run having the highest average posterior probability was used to calculate individual membership coefficients and maps of posterior probability of membership in each K cluster.Spatial patterns of genetic structure were examined using a discriminant analysis of principal components  to assess correlation between log(geographic distance) and linearized genetic distance (STF/(1 − STF)) matrices. Geographic distances were measured as the shortest distance over water between all pairs of sites in the Sulu Sea using the igraph package for R  of NeEstimator v2.01 . A randomly generated subset of 1,000 loci was used to calculate mutation‐scaled migration rates  and examine the probabilities of four different migration models: (a) a single genetic population (panmixia); (b) bidirectional gene flow between East and West allowing for asymmetric migration rates; (c) unidirectional gene flow from East to West; and (d) unidirectional gene flow from West to East. Analyses were performed on the CIPRES Portal  and the migration rate (M = 2000) exhibited acceptable posterior distributions and were used for subsequent analyses. Each model was run using Metropolis sampling and a static heating scheme with four chains, 1 × 106 generations with 10 replicate chains sampling every 100 steps, and a burn‐in of 100,000 steps. To determine the most likely migration model, log Bayes factors (LBFs) were calculated from the Bezier approximation score and compared for all four gene flow models , which calculates the relative levels of migration by assessing the genetic differentiation between two populations and a hypothetical pool of migrants . This pooling scheme is similar to the groupings used for the Migrate‐n analysis with one group of East sites  and one group of pooled West sites (ROX and BAT), with three additional populations: PPC, CRN, and TWI.The directionality and rates of contemporary migration were examined using the Web application of 2.8S. olivacea in the Sulu Sea basin, we used redundancy analysis (RDA), a direct gradient analysis technique, to test for significant relationships between response and explanatory variables  for the Sulu Sea domain  from 1987 to 2005 were generated from the NOAA/OAR/ESRL PSL website at https://psl.noaa.gov/  was evaluated through redundancy analysis using the outlier dataset. For SST, high‐resolution (0.25° × 0.25°) monthly variability data  was calculated. Partial RDA was performed, and the global analysis of variance was determined using the ANOVA function in stats v3.5.3 with 999 permutations. The significance of individual RDA axes was also assessed using ANOVA (permutations = 999), and selected environmental vectors were fitted into the ordination using envfit (permutations = 999).All explanatory variables  were individually tested using a backward selection procedure with 999 permutations using 33.1Scylla olivacea populations in the Sulu Sea basin  were aligned with PE contigs, with an effective per‐sample mean coverage of 20.8×. Following successive filtering steps  suggestive of diversifying selection  at the 99% confidence interval limit, which also included the 12 loci identified by BayeScan as putative outliers. OutFLANK flagged 12 loci as putative outliers (STF = 0.1124–0.3828); of these, 8 loci were concordant with BayeScan and Arlequin analyses. Consequently, a SNP panel consisting of 12 candidate outlier loci identified by at least two outlier tests was designated as the outlier loci dataset. Querying the contig sequences of putative outlier loci against public domain sequences using a BLAST showed no functional gene region matches for these 12 outlier loci  reads from 146 individual ci Table .3.3Scylla olivacea populations exhibited significant genetic differentiation based on global estimates of STF calculated using all loci  and putatively neutral loci . Excluding outgroup sites, Sulu Sea samples  still exhibited significant genetic differentiation for all loci  and neutral loci , PPC (STF range = 0.0014–0.0187), and one outgroup GSC (STF range = 0.0014–0.0219) , with significant STF between TWI‐ROX at all loci (Table 9) Table . The diver Table . Dendrogs Figure . Excludici Table , but no ci Table .ST pF‐values provide strong support for the separation of CRN and PPC, and to a lesser extent TWI, there is no evident support for ANT as a distinct population based on neutral loci. GENELAND recovered four genetic clusters for the neutral loci . An AMOVA testing a hypothesis of three genetic groups, (a) CRN, (b) PPC, and (c) the rest of the Sulu Sea populations, showed significant differentiation between groups .The DAPC using neutral loci shows separation of CRN, PPC, ANT, and TWI from the other Sulu Sea populations Figure . Based oi Figure . SpatialSTF = 0.2390, p = .001). A dendrogram based on pairwise STF estimates suggests four genetic clusters in the Sulu Sea: (a) CRN‐MSJ; (b) ROX‐PPC‐ANT; (c) BAT‐TWI; and (d) NEG , that is, for ROX‐PPC‐ANT and BAT‐TWI, while between‐cluster comparisons are significant (FDR p < .05)  accounting for 20.9% of the total observed variance. No further structure is detected among samples within groups . However, the discordance between pairwise STF versus groupings recovered by DAPC and GENELAND for the southern sites BAT, NEG, and TWI populations may be influenced by missing data (19% over the outlier dataset). Thus, the clustering for these three populations should be approached with caution.Outlier loci revealed pronounced genetic differentiation across the Sulu Sea  Table . The DAPn Figure . The firSTF and multivariate methods. To examine this further, we performed two separate analyses to handle missing data: (a) remove genotypes  with >25% missing data; and (b) impute missing data based on population frequencies as implemented in GenoDive v3.0  of individuals from East into West was slightly higher than immigration of individuals from West into East, at 950.1 (95% highest posterior density (HPD): 942, 980.7) and 800.3 (95% HPD: 606–922), respectively. The model of unidirectional gene flow from East to West had a greater probability than unidirectional gene flow from West to East, while the model of panmixia had the lowest probability.Coalescent simulations using Migrate‐n revealed that the model representing bidirectional gene flow between East and West populations had the strongest support Table . The immdivMigrate indicate high levels of relative bidirectional gene flow (m) between eastern (MSJ‐ANT‐NEG) and western (ROX‐BAT) populations . No statistically significant asymmetries in gene flow patterns were detected .Relative contemporary migration rates estimated from 3.5p > .05) . The first RDA axis (RDA1) constituted the highest proportion of genetic variation in the response data (60.9%), which is only significant at the 10% level (p = .065), whereas RDA2 accounted for 39.1% of the total genetic variation (p = .292). Although AEM6 and AEM7 vectors were both selected to construct the model, individual testing of explanatory variables revealed that only AEM6 was significant (p < .001). The AEM6 eigenvector modeled Puerto Princesa (PPC) and Tawi‐Tawi (TWI) as separate units  representing predicted patterns of spatial genetic connectivity in the Sulu Sea. Using redundancy analysis (RDA), backward selection of the AEM variables identified two significant predictors  Table . Togethes Figure .p > .05), suggesting neutral genetic structure is not influenced by geographic distances. This was supported by additional Mantel tests resulting in a nonsignificant correlation between geographic distance and genetic distance . Examining eastern and western boundary populations separately, an emergent pattern of genetic distance increasing with geographic distance is observed for the eastern boundary populations  although the relationship is not significant . Using the putatively neutral loci dataset, genetically divergent populations CRN, PPC, and GSC were estimated to have small effective population size  compared with other localities where Ne values range from 139.2 to very large (infinite) at 95% CI , with each analysis having four independent vectors identified consisting of months mostly during the wet season . RDA1 explained the highest fraction of genetic variation comprising 87.9%–88.4%, whereas RDA2 accounted for 9.8%–10.3%. Only SSTmean (p = .048) and SSTmin (p = .049) showed statistically significant RDA1 axes, while SSTmax is significant at 10% level (p = .056). Rainfall data explained a lower proportion of the variation (Radj2 = 0.656) despite having a similar number of significant variables contributing to genetic variation. The RDA model constructed using the rainfall vectors did not reveal significant correlation with genetic data (p = .089), which suggests that SST  is a stronger predictor of the observed latitudinal genetic variation than rainfall.Environmental data on SST and rainfall exhibited different levels of contribution to genetic differentiation and potential latitudinal adaptation of 4Scylla olivacea populations in the Sulu Sea. Analysis of neutral markers revealed weak yet significant genetic differentiation. Moreover, genetic structure estimated from SNP markers is significantly correlated with genetic structure predicted from particle dispersal simulations, indicating the influence of ocean currents on gene flow. Geographic distance was not a significant predictor of genetic structure. Outlier loci revealed a pattern of latitudinal genetic structure suggesting local adaptation to latitudinal environmental gradients, with SST as a stronger predictor of adaptive divergence than rainfall. These results reveal basin‐scale genetic differentiation of S. olivacea populations in the Sulu Sea and insights on potential environmental drivers, information that is expected to be useful to support spatially explicit management and conservation interventions.This study employed a seascape genomics approach to examine environmental factors influencing genetic structure of 4.1S. olivacea based on life history features such as offshore spawning migration and a pelagic larval duration of 20–30 days  , the hypothetical pool of migrants is expected to exhibit the same degree of genetic similarity to either West or East populations, and the accuracy of divMigrate estimates of directionality is likely to be low. Allele frequency‐based methods, particularly in moderate to high gene flow systems, fare poorly at distinguishing demographically significant connections and asymmetries , the accuracy of directionality estimates does not exceed 50% , but did not appear to indicate restricted dispersal between eastern and western boundary populations , with AMOVA indicating significant differentiation among groups: (a) CRN‐MSJ, (b) ROX‐PPC‐ANT, (c) BAT‐NEG, and (d) TWI. SST variabilities can potentially explain the observed latitudinal genetic structure of S. olivacea in the Sulu Sea. The most significant variables (months) included in the RDA model cover the wet season (June–November) where the latitudinal thermal cline was the steepest. This significant association between latitudinal genetic structure and environmental variation during the wet season coincides with the reported peak spawning season of Scylla species in the Philippines  , in which some of the genes involved in the genetic structure were associated with heat stress tolerance , which is linked to local adaptation relating to seasonal variability in temperature between two regions separated by 1–2°C thermal difference between sites , these were consistently identified by two outlier loci detection methods. However, as these SNPs do not map to known functional genome regions, there is no basis to generate hypotheses regarding specific genes or gene regions potentially under adaptive selection. Further studies utilizing a larger number of SNP loci than what we were able to generate for this study  should be able to recover a proportionally greater number of putative outlier loci. Moreover, while the redundancy analysis indicates a significant association between SST and genetic variation based on outlier loci, analysis of an expanded set of environmental variables and genetic data in a more explicit genotype–environment association analysis is recommended for further studies. These are expected to contribute to greater insight into local adaptation and underlying factors influencing genetic differentiation, which is essential to understand the dynamics of populations particularly in the context of environmental variability.This study reports a pattern of latitudinal adaptive divergence associated with SST for populations of 4.3S. olivacea, basin‐scale genetic differentiation was detected at both the putatively neutral and outlier loci, reflecting the influence of evolutionary  and environmental processes  on genotypic composition of populations in the Sulu Sea. The assessment of genetic diversity and connectivity of marine populations inferred from both neutral and outlier loci provides more holistic genetic information for fisheries management of populations  likely influenced by some restrictions to gene flow, but also genetic drift as a consequence of small effective population sizes. Populations with low Ne are particularly vulnerable to continued loss of genetic diversity and may need to be prioritized in restoration and conservation plans such as stock enhancement programs aimed at increasing yields beyond levels supported by natural recruitment  264s 2020; ; data curation (lead); formal analysis (lead); investigation (lead); methodology ; visualization (lead); writing–original draft . Rachel Ravago‐Gotanco: Conceptualization ; formal analysis (supporting); funding acquisition (lead); methodology ; project administration (lead); supervision (lead); writing–original draft .Scylla olivacea is a commercially harvested species and was not identified as a regulated species at the time of sampling. For Palawan, collection and local transport were covered under Palawan Council for Sustainable Development (PCSD) local transport permits and Wildlife Gratuitous Permit (GP) no. 2016‐23. Export of material for DNA sequencing was covered under the Bureau of Fisheries and Aquatic Resources GP no. 2018‐0005.https://doi.org/10.5061/dryad.3xsj3txdz.This article has been awarded <Open Materials, Open Data>Badges. All materials and data are publicly accessible via the Open Science Framework at Supplementary MaterialClick here for additional data file.


Bassiana duperreyi, to assess genetic population structure in the form of diagnosable lineages and their distribution across the landscape, with particular reference to the recent catastrophic bushfires of eastern Australia. Five well‐supported diagnosable operational taxonomic units (OTUs) existed within B. duperreyi. Low levels of divergence of B. duperreyi between mainland Australia and Tasmania  support the notion of episodic exchange of alleles across Bass Strait  during periods of low sea level during the Upper Pleistocene rather than the much longer period of isolation (1.7 My) indicated by earlier studies using mitochondrial sequence variation. Our study provides foundational work for the detailed taxonomic re‐evaluation of this species complex and the need for biodiversity assessment to include an examination of cryptic species and/or cryptic diversity below the level of species. Such information on lineage diversity within species and its distribution in the context of disturbance at a regional scale can be factored into conservation planning regardless of whether a decision is made to formally diagnose new species taxonomically and nomenclaturally.Much attention is paid in conservation planning to the concept of a species, to ensure comparability across studies and regions when classifying taxa against criteria of endangerment and setting priorities for action. However, various jurisdictions now allow taxonomic ranks below the level of species and nontaxonomic intraspecific divisions to be factored into conservation planning—subspecies, key populations, evolutionarily significant units, or designatable units. Understanding patterns of genetic diversity and its distribution across the landscape is a key component in the identification of species boundaries and determination of substantial geographic structure within species. A total of 12,532 reliable polymorphic SNP loci were generated from 63 populations  covering the distribution of the Australian eastern three‐lined skink,  Information on lineage diversity within species and its distribution in the context of disturbance at a regional scale is important for conservation planning regardless of whether a decision is made to formally diagnose those lineages as new species. Lizards were released at their point of capture. All collection protocols were conducted with the permission of Animal Ethics Committees at the University of Canberra and the CSIRO. Description of samples of B. duperreyi from each locality and their assigned population labels are provided in the Supporting Information Table We sampled 286 individuals of d Figure . Up to 1Bassiana platynota (n = 2), Bassiana trilineatus (n = 2), Pseudemoia pagenstecheri (n = 1), and Niveoscincus coventryi (n = 1). Nomenclature for bioregions follows that of Australia's bioregions (IBRA) and the description of the recognized biogeographic barriers in eastern Australia, according to Chapple, Hoskin, et al.  coupled with NucleoMag SEP (Ref. 744900) to allow automated separation of high‐quality DNA on a Freedom Evo robotic liquid handler . Four combinations of restriction enzymes were evaluated for B. duperreyi  and the restriction enzyme combination of PstI (recognition sequence 5’‐CTGCA|G‐3’) and SphI (5’‐GCATG|C‐3’) was selected for the complexity reduction by double digestion.Tissue samples were sent to Diversity Array Technology Pty Ltd. (DArT), Canberra, Australia, for SNP genotyping. DNA was extracted using the NucleoMagDNA was digested then processed following Kilian et al. , with tw2.3n ≤ 11. The number of samples per locality was small (n ≤ 11), so we could not filter loci for departures from Hardy–Weinberg equilibrium (HWE) or linkage disequilibrium; the sparse sampling of loci across the genome allows the reasonable assumption of little or no linkage between loci. We regard the data remaining after filtering as highly reliable.The SNP data and associated locus metadata were read into a genlight object  as implemented in the gl.pcoa and gl.pcoa.plot functions of dartR. A scree plot of eigenvalues Cattell, , taken i2.5Observed heterozygosity was used as a measure of relative genetic diversity. Heterozygosity was obtained for each population from allele frequencies using the gl.report.heterozygosity function of dartR.2.6B. duperreyi sensu lato, a fixed‐difference analysis was done using the scripts gl.fixed.diff and gl.collapse in dartR. An OTU is defined here as an aggregation of populations that can be differentiated by other such aggregations by one or more diagnostic characters. A fixed difference between two populations at a locus occurs when the populations share no alleles at that locus. Accumulation of fixed differences between the two populations is a strong indication of a lack of gene flow. Fixed differences were summed over populations taken pairwise, and when two populations had no fixed differences, they were combined, and the process repeated until there was no further reduction. The resultant OTUs are, by definition, putatively diagnosable at one or more SNP loci. The set of putative OTUs arising from the above fixed‐difference analysis was then tested for significance  might exist within the geographic distribution of 2.7B. duperreyi, we performed SVDquartets analysis on the individuals grouped by locality  after further filtration. We selected SVDquartets analysis  and the sole individuals from the Cooma (P6) and Mount Franklin populations (P11) each had an individual call rate of <0.4 (a threshold set taking into account the presence of the outgroups) and were removed from the data. The resultant data, including outgroup specimens (B. platynotus and B. trilineatus), are referred to as the full data set, comprising 14,063 polymorphic SNP loci from 60 ingroup sampling locality  and two sampling localities of the outgroup species (each with n = 4). Finally, the B. duperreyi dataset was obtained by subsetting the ingroup dataset to include only individuals of B. duperreyi and removing resultant monomorphic loci to yield 12,532 polymorphic SNP loci from 60 sampling localities.The full dataset, which includes all samples, comprised 232,230 polymorphic SNP loci from the sample set comprising samples from 63 sampling localities for the ingroup taxa  and six outgroup taxa. After stringent filtering on repeatability (repAvg = 0.99) and call rate (0.95), the number of SNP loci in the data set dropped to 66,907 and then 58,906, respectively. A total of 1,655 secondary SNPs, multiple SNPs occurring on a single sequence tag, were also filtered leaving one selected at random . Two outgroup specimens . Four individuals Z_60614 (P61), AA80788 (P9), Z_22574 (P60), and Z_22563 (P59) that fell in intermediate positions between major groupings were considered to be examples of contemporary admixture and were removed  to 5.3% . Given their presumed mitochondrial sequence divergence rate of 1.3% per Myr, Dubey, and Shine , and most of the major intraspecific lineages, including those in B. duperreyi, diverged between 5.7 and 1.7 Mya. On the basis of these data, they concluded that climatic fluctuations and associated sea level change during the Upper Pleistocene  did not substantially affect the extent of areas within which the lizards could persist, with the result that the genetic signature of ancient divergence events remains clearly expressed in modern‐day populations as strong geographically associated genetic structure  within  Figures  and 3. O Figures . However Figures  in that t Figure  with Tast Figure . A more ca 1 Kya). The reasons for this remain speculative, but it is possible that the intervening land bridge between the two areas, when sea levels were lower, contained habitat that was not conducive to the dispersal of B. duperreyi.In contrast, both the mitochondrial and nuclear data support isolation of the Kangaroo Island populations from the adjacent mainland that dates back beyond the last terrestrial interconnection between the two  and Tiliqua rugosa  and the second is an aggregation of diagnosable lineages (ESUs) occupying the lower elevation regions and coastal regions   Figure . They ha) Figure . The sou) Figure .B. duperreyi as currently defined (and Kangaroo Island)  has been severely impacted by fire, which raises concerns for its conservation. Tasmania and Flinders Island provide insurance, but the widespread impact of fire on the habitat of this eastern highlands and Australian Alps lineage is now of serious management concern. Similarly, our demonstration of the distinctive lineage of B. duperreyi on Kangaroo Island, also seriously impacted by the recent fires, raises its priority for its assessment and management. Our genome‐wide SNP analysis of structure within a widespread species highlights the need for biodiversity assessment at the regional scale to include an examination of cryptic diversity below the level of species and perhaps also a re‐evaluation of species delimitation. Such information on lineage diversity within species and the distribution of those lineages across the landscape can be factored into conservation planning regardless of whether a decision is made to define new species with formal taxonomic decisions.Our study has clear management implications in the context of regional catastrophic events and progressive habitat fragmentation and modification at regional levels. The recent fires in Australia were restricted to the eastern mainland portion of the range of ) Figure . ConcernThe authors declare no conflict of interest.Duminda S. B. Dissanayake: Conceptualization ; Data curation (lead); Formal analysis (lead); Writing – original draft (lead); Writing – review & editing . Clare E. Holleley: Conceptualization ; Funding acquisition ; Methodology ; Supervision ; Writing – review & editing . Joanna Sumner: Methodology ; Resources ; Writing – review & editing . Jane Melville: Methodology ; Resources ; Writing – review & editing . Arthur Georges: Conceptualization ; Formal analysis ; Funding acquisition (lead); Methodology ; Project administration (lead); Resources ; Software (lead); Supervision (lead); Writing – original draft ; Writing – review & editing .Table S1Click here for additional data file.


Cinnamomum balansae Lecomte (Lauraceae), an economically important forest tree, is distributed in the tropical forests of central and northern Vietnam, which has been threatened in recent decades due to the destruction of its habitat and over-exploitation. The genetic diversity and population structure of the species have not been fully evaluated. We used a set of 15 microsatellites to analyze 161 adult trees from 9 different populations, representing the geographical distribution of C. balansae. Ninety-two different alleles were identified. Here our results showed a low genetic diversity level with an average Ho = 0.246 and He = 0.262, and a high level of genetic differentiation (FST = 0.601). The bottleneck tests indicated evidence of a reduction in the population size of the two populations (TC and CP). Additionally, all three clustering methods  were identified in the two genetic groups. The Mantel test showed a significant positive correlation between genetic distance and geographic distance (R2 = 0.7331). This study will provide a platform for the conservation of C. balansae both in ex-situ and in-situ plans. Flowers are small, greenish-yellow, and appear between March and May. Fruiting appears from April to July, with fruit and maturation occurring in October [C. balansae is listed as an endangered species in the IUCN Red List [ Vietnam ,2,3,4. I October . Its hab October . For thaRed List  and the Red List .C. balansae and provide a platform for effective conservation strategies of this species in Vietnam.The adaptive and evolutionary potential of a species depends on its genetic diversity . Conserv22.1C. balansae  from a wild population . All sample tissues were immediately frozen in liquid nitrogen and stored at –80°C until RNA extraction.With Illumina sequencing for the development of microsatellites, we collected three plant tissues, including roots, leaves, and stems of C. balansae, the study area for this species was carried out in nine sites, one each in Hanoi, Phu Tho, Tuyen Quang, Yen Bai, Son La, Hoa Binh, Ninh Binh, Thanh Hoa, and Nghe An, representing its natural range in Vietnam (To assess the genetic variation in and population structure of  Vietnam . Samplin2.2www.cwbiotech.com). Both quantity and quality of total RNA were checked through Nanodrop ND-2000 spectrophotometer  and Agilent 2100 Bioanalyzer. An equal amount of total RNA from each sample was pooled together and sent to Breeding Biotechnologies Co. Ltd for cDNA library construction and transcriptome sequencing using Illumina HiSeq™4000. Cleaned mRNA was used for cDNA library construction extracted from 200 µg total RNA using Oligo (dT). The cDNA first strand was prepared from random hexamers using mRNA as a template, and the other strands were from the buffer, dNTPs, RNase H, and DNA polymerase I, and then cleaned with AMPure XP beads. The cleaned double-stranded cDNA was subjected to terminal repair, the sequencing linker was ligated, and then the fragment size was selected with AMPure XP beads. The cDNA library was acquired by PCR enrichment. After validating the library on an Agilent 2100 Bioanalyzer, Breeding Biotechnologies Co., Ltd sequenced the cDNA libraries on an Illumina HiSeq™ 4000. The Trimmomatic v3.0 [For Illumina sequencing, total RNA from each sample was isolated using the OmniPlant RNA Kit (DNase I) (tic v3.0  was usedtic v3.0  with deftic v3.0  was usedhttp://www.gramene.org/db/markers/ssrtool). Only unigenes longer than 1 kb were included in the EST-SSR detection. The parameters were set to detect perfect, di-, tri-, tetra-, penta-, and hexa-nucleotide motifs with a minimum of 6, 5, 5, 5, and 5 repeats, respectively. Identification of microsatellite loci showed simple sequence repeats and was deposited in GenBank.SSRs were detected in the Simple Sequence Repeat Identification Tool program . The quality of total DNA was verified by 1% agarose gel electrophoresis and NanoDrop2000 . The concentration was then diluted to 20 ng/µL and stored at −20°C.2.3TM 10000X. The sizes of the PCR products were detected and analyzed using GelAnalyzer software with a 20 bp DNA ladder (Invitrogen).Polymerase chain reaction (PCR) was performed in a 25 μL of reaction mixture containing 2.5 µL of template DNA, 12.5 µL of 2X Taq Master mix, 1 µL of each primer, and 8 µL of deionized water. All SSR primers were designed using Primer 5.0 software . The mai2.4Na), effective alleles (Ne), private alleles (Np), the proportion of polymorphic loci (P%), the coefficient of total inbreeding (FIT), the genetic differentiation (FST), Nei’s genetic distances among the populations, the observed heterozygosities (Ho), and the expected heterozygosities (He). Gene flow between populations (Nm) was calculated using the FST value: Nm = (1/FST − 1)/4. The inbreeding coefficients (FIS) value was also calculated for each population by Fstat [Genetic diversity was estimated using GenAlEx  based onby Fstat . Tests fby Fstat . Arlequiby Fstat  was usedby Fstat  was applG′ST values [FST values using Poptree2 [K). Setting the admixture model with correlated allele frequency and the ancestry models, 10 separate runs of the number of clusters (K) in the dataset were performed from 1 to 10 for each K value at 500,000 Markov Chain Monte Carlo (MCMC) repetitions and a 100,000 burn-in period. The optimal value of K was detected using Structure Harvester [K value by Evanno et al. [Principal coordinate analysis (PCoA) was implemented based on T values  using GePoptree2 . BayesiaPoptree2  to deterarvester  based ono et al. .C. balansae populations based on 999 permutations.A Mantel test  was appl33.1C. balansae in the tropical forests of Vietnam. Allele numbers ranged from 4 (VD51 and VD81) to 9 (VD08), with an average of 6.1  per population was 1.9, ranging from 1.6 (SL) to 2.2 (YB and TH).Genetic diversities for Np = 8) was detected in the CP population, followed by three populations of YB, BE, and QH with Np = 6, two populations of MC and DH with Np = 4, the BV population (Np = 2), and two populations (TC and SD) with Np = 1. The Ne value varied from 1.4 in 5 different populations  to 1.7 (YB population), with an average of 1.5 alleles. The observed heterozygosity (Ho) and expected heterozygosity (He) averaged 0.246 (0.143–0.339) and 0.262 (0.198–0.338), respectively. The QH population had the lowest genetic diversity (Ho = 0.143 and He = 0.198) and the YB population had the highest values (Ho = 0.339 and He = 0.338). Five populations of BV, SD, TC, CP, and QH had positive FIS values, indicating an excess of homozygosity and inbreeding in these populations. The highest FIS value (0.212) was found in the CP population and was significant (p < 0.05). A significant deficit of heterozygosity was detected in two populations (TC and CP), based on the Bottleneck analysis under the TPM and SMM (p < 0.05), and suggested evidence of a bottleneck.The highest number of private alleles  to 0.992 (VD25), indicating a deficiency of heterozygosity in the populations (FST) varied from 0.285 (VD108) to 0.992 (VD25) with an average of 0.601, indicating high differentiation among all the populations and reflecting low gene flow (Nm = 0.211). Our results of the AMOVA showed that the proportion of genetic variation among the populations was higher (74%) than within populations (p < 0.001).The average ulations . The genulations . The PhiR2 = 0.7331)  , indicatG′ST values  was two, with the highest value of delta K  obtained from Structure Harvester might an optimum number of genetic clusters  and high genetic differentiation among populations (FST = 0.601), compared to other widespread species, such as C. camphora in South China (Ho = 0.45 and He = 0.44) [Albanian olive (Ho = 0.75 and He = 0.60) [ugenia dysenterica (Ho = 0.545 and He = 0.62) [C. balansae [FIS values were observed in the five populations of BV, TC, SD, CP, and QH, while the negative FIS values were found in the remaining four populations of MC, DH, YB, and BE. A heterozygosity deficit was determined by the Bottleneck analysis, which detected a reduction in the population size of C. balansae. Small populations might be the result of inbreeding, which can decrease genetic variation. However, the bottlenecks also show a rapid reduction in the population sizes of TC and CP in recent decades. A high level of genetic differentiation (FST = 0.601) was determined, and reflected low gene flow (Nm = 0.211) among C. balansae populations. This is in contrast to previous reports on widespread species, such as Dalbergia cochinchinensis (FST = 0.23) [Erythrophleum fordii Oliv (FST = 0.18) [C. balansae populations may be responsible for high genetic differentiation. Moreover, habitat fragmentation can increase the isolation between populations. Thus, these suggested the geographic distance and habitat fragmentation as a barrier to restrict gene flow between populations. Population structure and genetic relationships are important for establishing the appropriate scale and subunits for species conservation and management [C. balansae in Vietnam. Thus, the best conservation strategy should be to establish an ex-situ conservation site for this species through collecting seeds, germinating, and cultivating seedlings. Collecting seeds from individuals of all the populations should be conducted so that random loss of genetic variability due to loss of individual ecotypes should be avoided and move towards new self-sustaining populations. The establishment of a new large population of C. balansae should provide new alleles, which might improve its fitness under different environmental stresses to prevent the gradual reduction in the population of C. balansae.The genetic diversity of a species is often correlated with its history and ecology ,45,46. T = 0.44) , Albania = 0.62) . Althougbalansae . Further = 0.23)  and Eryt = 0.18) . The dis = 0.18) . The larnagement . The stu5C. balansae had low genetic diversity and high genetic differentiation among populations in the evergreen tropical forests. The nine populations of C. balansae were divided into two genetic groups related to the geographic distance. Our study will contribute to understanding the population history of this species and the genetic relationships among the C. balansae populations.These results confirmed that