Desmophyllum dianthus has widespread dispersal consistent with its global distribution and resilience to disturbance. In contrast, for the matrix-forming colonial coral Solenosmilia variabilis asexual reproduction is important and the dispersal of sexually produced larvae is negligible, resulting in isolated populations. Interestingly, despite the recognised impacts of fishing on seamount communities, genetic diversity on fished and unfished seamounts was similar for both species, suggesting that evolutionary resilience remains despite reductions in biomass. Our results provide empirical evidence that a group of seamounts can function either as isolated islands or stepping stones for dispersal for different taxa. Furthermore different strategies will be required to protect the two sympatric corals and consequently the recently declared marine reserves in this region may function as a network for D. dianthus, but not for S. variabilis.Ecological processes in the deep sea are poorly understood due to the logistical constraints of sampling thousands of metres below the ocean’s surface and remote from most land masses. Under such circumstances, genetic data provides unparalleled insight into biological and ecological relationships. We use microsatellite DNA to compare the population structure, reproductive mode and dispersal capacity in two deep sea corals from seamounts in the Southern Ocean. The solitary coral  Despite recent developments in ocean observing and exploration, the deep sea remains one of the last scientific frontiers. The marine communities that exist at depths in excess of 1000 m are some of the least understood ecosystems on the planet, but they face considerable threats from fishing, mining and climate change and there is an urgency to document their diversity and understand threatening processes to provide a foundation for effective management and conservation of deep sea resources12Evidence of anthropogenic-induced declines in deep sea populations is growing. Fishing, particularly on seamounts, has resulted in depletion of many fish stocks, as well as having indirect effects on benthic communities including ecosystem engineers such as sponges and corals that are very slow to recover45For many marine species, connectivity is maintained through the planktonic dispersal of microscopic larvae or juveniles, and an assumption of a direct link between larval duration and dispersal distance has formed the basis for predicting connectivity in poorly studied ecosystems such as the deep sea81012131417The mismatch between expected and observed dispersal of marine invertebrates has highlighted the need to incorporate environmental parameters with biological, ecological and genetic data to parametrise models that better explain population or metapopulation structure and predict dispersal in the ocean; hence a growing focus on “seascape genetics” in studies of connectivity in the sea21222324261Riftia pachyptila, and reported genetic structure across distances as little as 400 m. Baco & ShankCorallium lauuense in Hawaii. Similarly, genetic studies of the deep sea coral Lophelia pertusa have revealed evidence of limited dispersal and genetic differentiation among some populations at scales of tens of kilometresNotably, most deep sea genetic studies have focussed on large-scale patterns of dispersal across thousands of kilometres between geographic features such as oceanic ridges or at continental scales e.g. refs 353637Desmophyllum dianthus and the matrix-forming, colonial coral Solenosmilia variabilis - to predict dispersal within and among seamount populations in the Southern Ocean. These two species of deep sea coral belong to the scleractinian family Caryophyllidae and are abundant and widely distributed on seamounts in the Southern Ocean. The solitary coral, Desmophyllum dianthus, has been recorded to depths of almost 2400 mD. dianthus on widely separated ridge systems are isolated  and so it is likely these are the result of asexual reproduction.Genetic diversity in ng sites . Of the D. dianthus populations ranged from 0.438 to 0.778 and was lower than expected in all populations (D. dianthus (for those sites where n > 12), more than half (52%) of these were significant, with all representing heterozygote deficits. This pattern did not change after data were adjusted for the presence of null alleles.Heterozygosity observed in ulations . Of the S. variabilis was lower than that observed in D. dianthus. We recorded between 3 and 34 alleles per locus across the nine seamounts (average = 15.2), and an average of 5.4 alleles per locus at each of the 18 sites (−4) hence they most likely represent the product of asexual reproduction. Estimates of genotypic richness in S. variabilis averaged 0.56 across all sites, but ranged from 0.22 to 0.88 across the nine seamounts , but most of these were associated with Locus SvD213 which had large heterozygote deficits at 14 of the 18 sites sampled and was likely to have null alleles. Excluding SvD213, and with only 18 of the remaining 116 locus x site tests being significant, we considered the sexual populations of S. variabilis at each site to be in Hardy Weinberg Equilibrium.Genetic diversity in 18 sites . Observe18 sites . There weamounts  indicatiD. dianthus or S. variabilis  private alleles/site. For S. variabilis, there were private alleles recorded at 16 of the 17 sites studied, with an average of 2.2 (±0.39SE) private alleles/site.Despite the known impacts of deep sea fishing on Tasmanian seamounts47riabilis . FurtherD. dianthus STRUCTURE analysis suggested K = 2 (based on ΔK)   and S1a d on ΔK)  and S1b.d on ΔK) , which ad on ΔK)  and provS. variabilis, the number of populations within the data set was also K = 2 (based on ΔK) . Interestingly, while some sites appear to be a mix of the 2 (or 3) genetic groups  other sites are dominated by a single type  (For d on ΔK)  and S2a d on ΔK)  and S2b.Site 34) , althougD. dianthus it was not possible to test for oceanographic-scale genetic structure as replication was confounded by the depth stratification. However for S. variabilis there was significant genetic differentiation between the Macquarie Ridge and all other sites . This is quite different to the findings based on DNA sequence data (16 S and control region) which revealed a single common haplotype in S. variabilis populations spanning Western Australia, Tasmania, Macquarie Ridge and New ZealandFor D. dianthus there are only very low levels of genetic subdivision, with two of three test statistics suggesting gene flow occurs among the seamounts . Pairwise comparisons showed significant differences between sites in only one comparison, between Hill Z15 and Dory Hill and again this was significant based on FST, but not DEST , Nem = 5.6  and Nem = 19.6 based on coalescent analyses.Within the 1000–1400 m depth stratum on Tasmanian Seamounts, the two closely related deep sea corals have very different population genetic structure and gene flow. For not DEST . EstimatS. variabilis there is significant genetic subdivision among all the Tasmanian seamounts  indicating populations are not panmictic. Most pairwise comparisons among seamounts showed significant genetic differentiation indicative of limited gene flow, with the exception of four of the 153 tests , Nem = 2.25  and Nem = 0.94 based on coalescent analyses.For D. dianthus: Mantel’s R2 = 0.025, p = 0.321; S. variabilis Mantel’s R2 = 0.014, p = 0.106). For D. dianthus, values of Nem based on coalescent estimates of migration were generally large and ranged from 0.09 to 156. Of the 50 estimates of migration between all pairs of sites, 38 resulted in Nem > 1, and 20 of these with Nem > 10 indicating sufficient gene flow for ecological connectivity among most seamountsNem among seamounts were significantly greater than 1  compared with Nem of 0.49 in the opposite direction and into MiniMatt from Hill Z56  compared with Nem of 2.84 in the opposite direction.For than one . For S. S. variabilis  than in D. dianthus . Contemporary estimates of effective population size revealed similar patterns, with populations of S. variabilis relatively small but more variable across sites than Θ  and populations of D. dianthus very large  significantly different to zero in most comparisons  and Jost’s D  although FST was significant . Similarly on the Macquarie Ridge, the two shallow sites sampled on the top of Seamount 5 (~3 km apart) were not significantly differentiated from each other based on G’ST  and Jost’s D  but were based on FST  and the same pattern was evident for the three deep sites sampled on the Cascade Plateau and that are separated by as little as 300 m. However the consensus between G’ST and Jost’s D is compelling evidenceD. dianthus populations at the within-seamount scale, and that contemporary gene flow occurs among these sites. Coalescent estimates of migration among sites are, however, low  and mitochondrial (16S and CO1) haplotypes in specimens from Australia to the Mediterranean . Our microsatellite genetic data provides further evidence that larval dispersal and gene flow can occur in this species across hundreds of kilometres. Indeed patterns of migration appear to be influenced, at least in part, by the prevailing westerly currents across the Tasmanian Seamounts suggesting passive larval dispersal facilitated by stepping-stones such as intermediate seamounts may play a role in the distribution of this widespread and common species.The distinct genetic structures and contrasting connectivity in Solenosmilia variabilis is common in the southern hemisphere, forming extensive reef-like structures particularly around southern Australia and New Zealand47www.gbif.org). A much reduced dispersal capacity, as inferred from genetic differentiation within and among Tasmanian seamounts, may explain the restricted distribution and localised abundance of S. variabilis. For the confamilial and matrix-forming Lophelia pertusa, planulae are active swimmers and can survive for at least eight weeks in the water column, although they will commence settlement behaviour after 3–5 weeksL. pertusa populations are not panmictic and that dispersal may be affected by local hydrodynamic and geographic featuresS. variabils and L. pertusa are the southern and northern hemisphere ecological equivalents of each other, and it is interesting that genetic structure indicative of restricted larval dispersal is apparent in both these matrix-forming species that have apparently constrained distributions.D. dianthus and S. variabilis to know if the approximately three times greater level of genetic differentiation seen in S. variabilis compared with D. dianthus (based on G’st and Jost’s D) links directly to larval duration, other aspects of their life history, or environment. For example, spawning in winter compared with summer may result in very different dispersal potential based on the magnitude of currents at 995 m in the Tasmanian Seamounts (D. dianthus suggests either a different reproductive period than assumed here (January to May), or that other factors such as larval behaviour are influencing dispersal patterns. Of note also is that the hydrodynamic model used here , is consistent with their reported relative capacity to recover and/or recolonise following disturbance, and supports the suggestion that solitary corals such as D. dianthus will be less vulnerable to fishing effects than colonial speciesD. dianthus than in S. variabilis, migration rates are still low to moderate in both species, and arguably lower than expected if populations were panmictic. Although only “one migrant per generation” is considered sufficient gene flow to prevent evolutionary divergence among populations, from a conservation and management perspective, Nem of >10 migrants per generation may be a more realistic measure of connectivity49D. dianthus, but not for S. variabilis. In this context, S. variabilis is likely to be more vulnerable to anthropogenic impacts than D. dianthus.Solitary corals are among the species that seem least affected by fishingD. dianthus, but not for S. variabilis. Similarly, the size and timing of management actions such as fishing closures would have different consequences for recovery in each species. Given the importance placed on conservation of ecosystem engineers in managing marine ecosystems more broadly68Collectively, the results from this study provide critical input to the future management of deep sea corals. Based on genetic data it is clear that these two closely related coral species have very different population structures and capacity for dispersal. In this context, conservation measures such as Marine Protected Areas will need to consider the different scales across which dispersal processes are operating in order to achieve adequate protection or ensure the provision of networks of connectivity for all taxa. For example, the recently declared Commonwealth Marine Reserves in SE Australia will most likely be operating as networks for S. variabilis has relatively small effective population sizes compared with D. dianthus both in evolutionary and ecological timescales, hence S. variabilis populations may be particularly vulnerable to the effects of genetic drift, and this may be exacerbated if populations are further reduced e.g. from fishing or climate change. Furthermore, the low apparent migration rate and importance of asexual reproduction in S. variabilis are also life history traits that emphasise the vulnerability of this speciesD. dianthus.From a conservation perspective, the magnitude of difference in effective population size between the two coral species must also be considered. Maintaining large effective size of populations is considered paramount in conservation, as small populations will be susceptible to the effects of drift and concomitant loss of genetic diversity and adaptive capacityThis study provides another example of the value of genetic data to underpin informed management and conservation measures, but this is particularly so in ecosystems such as the deep sea which is remote and where it is logistically difficult to obtain ecological data in alternate ways.D. dianthus and eight seamounts and one slope location for S. variabilis (Specimens of both species were collected by benthic sled from seamount and shelf locations at depths ranging from 489–2395 m during three research voyages in the Southern Ocean: The South East MPA Survey south of Tasmania on the RV Southern Surveyor in March/April 2007 (Voyage SS200702), the Macquarie Ridge on the RV Tangaroa in 2008 (Voyage TAN0803) and the Tasmanian Seamounts on the Thomas T. Thompson in 2008 . Sleds typically covered a few hundred metres of ground at each site. All samples were preserved whole in 95% ethanol or ultra-frozen for genetic analysis. In total 10 different seamounts and one slope location were sampled for riabilis  spanningD. dianthus individuals from 16 sites  and Locus SvC4 amplified in a separate reaction. Amplifications were in 25 μL volumes comprising 12.5 μL of 2× Qiagen Multiplex PCR Master Mix, 0.1 μM of all primers excepting B116-F, B116-R, D213-F and D213-R which were added to a concentration of 0.2 μM, 2.5 μL of 5× Q-solution and 10ng DNA. Thermal cycling comprised 15 min at 95 °C, followed by 10 cycles of 94 °C for 30 sec, 57 °C annealing for 90 sec and 72 °C extension for 60 sec, then 25 cycles of 94 °C for 30 sec, 55 °C annealing for 90 sec and 72 °C extension for 60 sec with a final 30 min extension at 72 °C.For ine loci ; two mulFor both species, PCR products were diluted 10–20 fold into a 20 μL volume containing 9.8 μL HiDi Formamide and 0.2 μL GeneScan 500 LIZ (ABI) internal size standard, prior to electrophoresis on an ABI 3730. Alleles were analysed and scored based on fragment size using the GeneMapper V4 software (Applied Biosystems Inc.) and binned using Tandem V 1.02FIS in Genepop 4.2) was used to examine the size and nature of any departures from random mating. We calculated allelic richness using FSTATR = (G − 1)/(N − 1)The final data sets for each species were checked for evidence of linkage disequilibrium using Genepop 4.273D. dianthus except locus DdC107 and at two loci (SvB116 and SvD213) in S. variabilis. We therefore adjusted each data set to account for null alleles using Micro-checker, based on the Oosterhout correction algorithm. Null alleles at each locus were labelled as the largest allele + one repeat. Because these adjustments are based on assumptions of HWE, which may not be appropriate for coral populations as they often reproduce asexually and can be inbred, the population genetic analyses were done on the raw data as well as the data adjusted for the presence of null alleles, for comparison.We tested for the presence of null alleles using Micro-checker 2.2.3D. dianthus and K = 1–17 for S. variabilis). Structure HarvesterD. dianthus).We used STRUCTURE 2.3.3D. dianthus and S. variabilis; among sites on the same seamount (<1 km) and among seamounts (5–106 km) using AMOVA and by calculating a range of pairwise genetic differentiation measures including FST, G’ST and DEST  to provide insight on evolutionary vs. contemporary relationshipsAnalysis of connectivity among seamounts was focussed on a single depth stratum in the Tasmanian Seamounts (mid-depth range 1000–1400 m) as this sub-set of the data represented the best level of replication for both species . Here weNem using private allelesFST using the formula Nem = (1/FST) − 1 (Wright 1931) as each gives a different temporal perspective i.e. private alleles reflect relatively recent gene flow and FST methods represent gene flow through longer time spansFST against geographic distance among all sites within the mid-depth range in the Tasmanian Seamounts. Tests for a significant relationship between genetic and geographic distance were done using a Mantel Test in Genalex 6.5. In addition we examined variation in the directionality of dispersal among mid-depth seamount sites in the Tasmanian Seamounts using LAMARC 2.1.9Θ and M were based on the average of three preliminary runs using default settings and uniform prior distributions. Final runs consisted of 1 final chain, 1,000,000 steps and a burn-in of 10,000 steps, and were run with two simultaneous searches with adaptive heating and temperatures set to 1 and 1.1. Following the final run, we plotted the curve files to confirm that a single optimum value was estimated for each parameter. We calculated Nem from the LAMARC estimates of migration by multiplying effective population size (Θ) by migration (M) among all sites. Additionally we calculated contemporary effective population size using the linkage disequilibrium method of Waples and Do (2008) using NeEstimator V2To assess gene flow in both species, we calculated th interval. Bayes factors and the probability of each model were calculated according to BeerliD. dianthus as S. variabilis populations were considered effectively isolated (see results).To better understand if patterns of dispersal across the Tasmanian Seamounts at mid-depth were linked to the directionality of oceanographic currents, we tested four alternate models of gene flow among the seamounts: (1) Panmixis, (2) Westward, (3) Eastward, and (4) a full model that considered gene flow among all pairs of sites. This analysis was conducted using Migrate-N v3.6.11D. dianthus it was also possible to assess migration within seamounts for deep  and shallow  sites. These analyses were conducted as described above for the mid-depth sites in the Tasmanian Seamounts.For How to cite this article: Miller, K. J. and Gunasekera, R. M. A comparison of genetic connectivity in two deep sea corals to examine whether seamounts are isolated islands or stepping stones for dispersal. Sci. Rep.7, 46103; doi: 10.1038/srep46103 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Bos taurus breed that have adapted to the wet tropical conditions of the Amazon. This breed has integrated into the culture of the indigenous Shuar-Asuar nations probably since its origins, being one of the few European zoogenetic resources assimilated by the deep-jungle Amazon communities. Despite its potential for local endogenous sustainable development, this breed is currently endangered. The present study used molecular genetics tools to investigate the within- and between-breeds diversity, in order to characterize the breed population, define its associations with other breeds, and infer its origin and evolution. The within-breed genetic diversity showed high values, as indicated by all genetic parameters, such as the mean number of alleles (MNA = 7.25±2.03), the observed heterozygosity (Ho = 0.72±0.02) and the expected heterozygosity (He = 0.72±0.02). The between-breeds diversity analysis, which included factorial correspondence analysis, Reynolds genetic distance, neighbor-joining analysis, and genetic structure analysis, showed that the Macabea breed belongs to the group of the American Creoles, with a Southern-Spain origin. Our outcomes demonstrated that the Macabea breed has a high level of purity and null influences of exotic cosmopolitan breeds with European or Asiatic origin. This breed is an important zoogenetic resource of Ecuador, with relevant and unique attributes; therefore, there is an urgent need to develop conservation strategies for the Macabea breed.Macabea cattle are the only  The group of the American Creole cattle breeds, which were formed in the American continent after the European colonization , represeCapitanies [Bos indicus breeds from the Asian colonies of the British Empire. Already at the beginning of the 20th century, Asiatic breeds such as Guzerat, Nelore, and Gyr had an extended distribution across the United States, Mexico, and Brazil [The first arrival of cattle to America occurred in the second voyage of Columbus in 1493, which set sail from the south of the Iberian Peninsula . After tBos taurus and B. indicus have a common ancestor in the Aurochsen wild B. primigenius, which marked the start of domestication approximately 11000 years ago [ears ago , even thears ago .Bos indicus animals became massive and indiscriminate, producing extensive deforestation especially in river basins. Today only few local breeds from Bos Taurus type exist one of this is the Ecuadorian Macabea breed. The animals from this breed present excellent meat attributes.The Amazonian region was almost free of cattle until the 20th century, when farming practices became more aggressive and sprawled into natural environments. At the same time, the introduction of The origin of the Macabea breed is unknown. Presumably, they reached the Ecuadorian Amazon along with the Spanish incursions developed between 1540 and 1548 from Quito and Guayaquil . HoweverMacabea cattle  are currThere are several enigmatic controversies around the genetics origins of Macabea breed, and in particular, if it should be admitted as a resource for the sustainable development of the Amazonian region. There is a persistent pressure from conservationist groups against the presence of farm animals in the natural environment. The aim of this study was to genetically characterize the Macabea cattle breed based on microsatellites markers, in order to generate scientific data about this rare genetic resource and its genetic relation with other Creole or exotic breeds, searching for a geo-evolutionary explanation of its origin and dissemination. These findings would support the conservation of this important breed, and propose the Macabea breed as a resource for the endogenous sustainable development of the region, in terms of its excellent meat quality and its ability to adapt to the wet tropic. Microsatellite markers have been widely used for population genetic analyses of livestock species –11, as tEthical approval was not needed for this study. All hair samples collections were non-invasive (hair roots) and carried out during routine veterinary visits in the farms on live animals. The fieldwork did not involve any endangered or protected species. Hair root were manually collected without any injury in the back of the animals No other kind of tissues  were used in this study.2 area of the Amazonian Provinces of Pastaza and Morona Santiago, in Ecuador; in particular the following location were visited: Palora ; Jimbitono ; Macas ; Puyo ; Morona-Santiago ; All the farms were isolated, distributed in the deep-jungle, accessed only by river routes, and with a considerable distance between them (~50–100 km). Cattle owners belonged to the native nationality Shuar-Achuar, which still maintain strong traditional culture practices. After collection, hair samples were stored in labeled envelopes, and brought from the collecting point to the Universidad Estatal Amazónica . DNA was extracted using three hair roots cut and incubated at 95°C during 15 minutes and at 99°C during 3 minutes in a 100 μl solution of Chelex100 resin . After incubation, extracted DNA was conserved at –20°C until use.Hair samples of 25 Macabea individuals were randA panel of 28 microsatellite markers , selectewww.datadryad.org): doi:10.5061/dryad.1dh4cData used in this paper have been archived at Dryad (http://www.biobovis.jimdo.com); these breeds represented evolutionary branches to be tested to determine the genetic origin and the evolutionary associations of Macabea. Data are deposited and available at Laboratory of Applied Molecular Genetics. As outgroup-breeds, we chose the Rubia Gallega (RGA), which represents Celtic animals from northern Spain, and the Berrenda en Colorado (BC) and the Marismeña (MA), both representing southern Spanish resources. In theory, Macabea cattle reached the Amazon with colonizers from the Pacific coast; therefore, we included the Ecuadorian Creole Ecuadorian of Southern (EC) and the Colombian Creoles Hartón del Valle (HV), and Blanco Orejinegro (BON). In order to test recent influences of cosmopolitan European breeds specialized in milk and beef production, we included the most influential breeds of these groups in the region: Hereford (HER), Brown Swiss (BWS), Holstein (HOL), Jersey (JER), Simmental (SIM), and Charolaise (CHAR). Finally, to test the possible influence of the zebuine expansion in the Amazon on the Macabea breed, the Brahman (BRH), Gyr (GYR), Nellore (NEL), and Cuban Zebu (ZEBU) were also used in this study. To explore the between-breeds diversity, we used 621 genotypes belonging to outgroup-animals. This information, and the individual breeds sample sizes are shown in We obtained data on different bovine breeds from the BIOBOVIS project , unbiased expected heterozygosity (He), the average number of alleles (Na) and the content of polymorphic information (PIC) for the breed and for each marker by means of using the Microsatellite Toolkit software . The Fisa posteriori distribution of each individual admixture coefficient (q). The mean in this distribution represents an estimation of the proportion of the parental population genome present in the individuals. This program develops a clustering of the individuals in different number of clusters (K), representing the number of populations admitted in an admixture model, in which each individual genome could content different percentages of the ancestral population genomes where they come from. Alternatively, two structure runs were carried out: in the first one, all breeds were included, and the results were displayed using Distruct v1.1 software [k colored segments, which represents the genotypic fractions of each inferred cluster. Secondly, we calculated a structure run only including MAC, EC, BON and HV breeds, where we used the kriging interpolation method [To infer the genetic relation between the Macabea breed and all the determined outgroups, we performed a factorial correspondence analysis (FCA) using the Genetix v. 4.05.2 software . In addisoftware  and the software . In the n method  to assesn method  was usedThe microsatellites panel used in this study has been previously applied and proved in several cattle studies, conducted by our own research team , 2, 29. FIS = 0.03(0.02–0.05), FIT = 0.16(0.14–0.18), and FST = 0.13(0.12–0.15). Macabea cattle showed a high mean of alleles, with a value 7.79±2.02; the other Ecuadorian breed EC presented the highest value (9.47±2.44), and the lower value was detected in JER (4.79±1.03). This trend was confirmed by the allelic richness and the heterozygosity data  and significant (P<0.05). When observed by breed, the FIS index from EC, BC, HER, GYR, and NEL breeds showed slightly significant values, and with Macabea presented no significant deviation.Most of the markers in the studied breeds were in HW equilibrium ; seven bity data . The oveFIS and Reynolds distances). In both cases, Macabea showed extreme distances in respect to the zebuine breeds, and a close position in respect to the EC and the Colombian breeds (HV and BON). These results are supported by FST pairwise-distances are graphically represented by using a color gradient matrix. Two clusters belonging to the Bos indicus and Bos taurus cattle types are visible. In this scenario, Macabea cattle breed showed very large distances with respect to all the Bos indicus breeds, with FST values ranging between 0.18 and 0.23, and between 0.18 and 0.21 for Reynolds distances. In general, Macabea breed also showed important distances in respect the other international Bos taurus breeds, with FST values ranging between 0.07 and 0.15, and between 0.06 and 0.14 for Reynolds distances. The shorter distance of Macabea with international breeds was detected in respect to the BWS breed. The Spanish outgroups RGA (representing the Celtic breeds from the northern Spain), and the MA and BC (Southern-Spain breeds) showed diverse patterns of distances with MAC, being the southern breeds closer than the northern breeds, with FST values of 0.06, 0.08, and 0.11, respectively, and Reynolds distances of 0.06, 0.08 and 0.10, respectively. Finally, the group that was detected to be the most related to Macabea was formed by the other Creoles, in particular, the Colombian HV and the EC .Bos taurus vs. Bos indicus); and the second level considered each geographical origin . P<0.01). Variation between-groups were 11.67% (P <0.05) and 7.86% (P<0.01) for the phylogenetic and geographical groups comparisons, respectively. The results of the factorial correspondence analysis conducted with all the studied breeds, and then avoiding the zebuines, both supported the results obtained in the AMOVA: breeds were grouped in the space according to their phylogenetic origin , using as reference the clusters k2 and k3, results very illustrative. We described a unique cattle breed adapted in a tropical environment of Ecuador. The importance of this genetic resource goes further in the field of biodiversity conservation; in fact, these animals reared in extremely marginal areas, with low technological inputs, demonstrate a unique capacity of adaptation to produce high quality beef in the wet tropics, intended as a money reservoir for native nationalities. In general, the daily protein consumption of families is sustained through hunting, fishing, and pigs and chicken. The cattle, however, are often converted into money when needed by the family. The official recognition supported by the molecular findings could add value to this particular economy and improve the quality of life of the disadvantaged population.Within-breed diversity results supplied robust and important arguments to support Macabea conservation status. We must first highlight that only four of our 28 markers were not in HW equilibrium; this outcome denotes a genetic stability in the population that corresponds to a consolidated breed with no recent bottleneck or migration events. Other general parameters also support this hypothesis, such as the mean number of alleles, all of which reflect a high level of within-breed variability. These general parameters were higher than those previously reported for European breeds , 32, 33,Cattle reached Ecuador from Panama during the beginning of the regional Spanish conquest arriving directly to the Caribbean Islands, which was the first point of cattle colonization in the Americas . ProbablThe panel of microsatellites markers used in the present study resulted highly informative and with sufficient statistical power for biodiversity studies as just described in different works on bovine species  suitableFIS values, which were undistinguishable from cero, demonstrated a general HW equilibrium. These results indicated that Macabea presents a level of genetic differentiation that is sufficient to be considered as an independent breed, according to international conventions [The general ventions . Thus, MFST distances were robust: we demonstrated the no existence of zebuines breeds introgression on Macabea, which remark its resistance despite a challenging context with massive introductions of zebuines in the region. In addition, we demonstrated the isolation of Macabea breed with respect of previous introductions of international Bos taurus breeds, highly specialized in meat or dairy productions.Once covered the objective of breed-genetic characterization by means of the within-breed diversity study, the second purpose of this study was to explore Macabea phylogenetic evolution. This second objective was tackled by means of the between-breeds diversity study, taking into account representatives of all branches used as outgroups, representing different hypothesis of the origin, genetic relationships, and evolution of the Macabea breed. The results of the Reynolds and Our results on the genetic association of the Macabea with the Spanish breeds, both the southern and northern representatives, are very interesting and support the hypothesis of the traditional integration of the breed in the Shuar-Asuar culture (old “head reducers”). The relationship between the Macabea cattle and the Shuar-Asuar communities, as pointed out by us earlier, probably started in 1599 when the city of Sevilla de Oro; the first European Amazonian settling founded in 1577, was destroyed by these native nationalities [There was a strong association of Macabea with southern Spanish breeds, supporting the hypothesis extracted from the chronicles, which described that the commercial trade between Spain and the American colonies was monopolized by the southern-Spanish ports for a long period , 38. FinBos taurus members, in particular, when the zebuines were included Click here for additional data file.S1 Table(DOCX)Click here for additional data file.


Bovine visceral schistosomiasis has been reported as an important disease entity as it affects animal health, productivity, causes economic losses due to liver condemnation, and produces a high morbidity. This study was conducted to standardize an easy, reliable dot-enzyme-linked immmunosorbent assay (ELISA) for the diagnosis of visceral schistosomiasis caused by Schistosoma spindale and to know the prevalence rate in and around Hyderabad.A dot-ELISA was standardized in the laboratory using whole worm antigen (WWA) and excretory-secretory antigen (ESA) of S. spindale. The standardized test was used for the diagnosis of bovine visceral schistosomiasis at field level. The sensitivity and specificity of the test was compared with counter current immunoelectrophoresis. In total, 288 sera  were screened by dot-ELISA.The dot-ELISA detected 32.63% of infection (94/288) using WWA and 40.62% of infection (117/288) using ESA. In cattle, the prevalence rate was 32.80% (41/125) using WWA and 40.80% (51/125) of infection. Similarly, in buffaloes, the prevalence rate was 32.51% (53/163) using WWA and 40.49% (66/163) of infection using ESA. The overall sensitivity of dot-ELISA was 76.74% and 80.48% with WWA and ESA, respectively, and specificity was 73.3% and 78.57% in WWA and ESA, respectively.As ante-mortem diagnosis of visceral schistosomiasis is difficult in subclinical conditions, dot-ELISA can be used as a reliable immunodiagnostic test for diagnosis at field level. Schistosoma species such as Schistosoma spindale and Schistosoma indicum. High rates of prevalence of subclinical infections cause significant losses due to long-term effects on animal growth, productivity, reduced conception and pregnancy rates ) for the diagnosis of visceral schistosomiasis and to evaluate it for the diagnosis of the disease in field levels.S. spindale .Two rabbits were used for raising hyperimmune sera (HIS) against whole worm antigen (WWA) and ES antigen (ESA) of S. spindale male worms were identified by their smooth cuticle with 3-5 number of testes and female worms lodged in gynecophoric canal of male worms containing spindle-shaped eggs in the uterus with terminal spine at one end. S. indicum worms can be separated based on rough cuticle (tuberculated/spiny) with 5-7 testes and the female worms containing oval-shaped eggs with terminal spine at one end. After species separation, S. spindale worms were used for further studies.The mesenteric veins of the freshly collected bovine intestines from slaughter house were examined against sunlight, and the adult schistosomes were collected carefully in sterile phosphate-buffered saline (PBS). After three washings in sterile PBS, the parasites were segregated species wise based on their morphological characters under light microscopy. Around 500 freshly collected live flukes were washed thoroughly in normal saline and transferred to 2 ml of 0.01 M PBS (pH 7.4) containing ampicillin (40 mg), amikacin (40 mg), sodium azide (0.1%), protease inhibitor, and phenylmethylsulfonyl fluoride (PMSF 1 mM). The worms were incubated at 37°C in an incubator with 5% carbon dioxide for overnight. On next day morning, the incubated fluid containing excretory-secretory (ES) products was collected and centrifuged at 13,000 rpm at 4°C for 30 min. The supernatant was collected and stored at −20°C.S. spindale after washing thrice in PBS (pH 7.4) and triturated with 5 ml of PBS (pH 7.4) using glass tissue homogenizer (Potter Elvehjem glass Teflon) for 10 min at 4°C. The contents were sonicated at 20 kHz for 10 cycles for 90 s each with an interval of 1 min in between. The contents were centrifuged at 9500 ×g for 15 min at 4°C in a high-speed centrifuge . The supernatant was collected and preserved by adding one drop of 1% sodium azide and 1 mM of PMSF at −20°C, after making the solution into several aliquots.Similarly, the WWA were prepared by taking around 500 worms of et al. (1951) using protein estimation kit obtained from Genei, Bengaluru.The protein concentration of antigens was estimated as per the method of Lowry th day of last booster injection. Serum was separated under sterile conditions, and complement inactivation was done by keeping in water bath at 56°C for 30 min. Sera were tested for the presence of antibodies using corresponding antigen with double immunodiffusion (DID) and counter current immunoelectrophoresis (CCIEP) techniques. The sera containing antibodies for respective antigens were made into aliquots and stored at −20°C till further use.WWA (0.25 ml) containing 3.88 mg/ml of protein along with equal volume of Freund’s complete adjuvant (FCA) was injected subcutaneously into one rabbit. Similarly, 0.3 ml of ESA (2.01 mg/ml of protein) along with 0.3 ml of FCA was injected subcutaneously to another rabbit. Four booster doses containing either WWA (0.25 ml) or ESA (0.3 ml) along with equal volume of Freund’s incomplete adjuvant were administered subcutaneously to the respective rabbits at weekly intervals. The animals were bled by the puncture of marginal ear vein and checked for antibody (Ab) response by agar gel precipitation test before administering each booster injection. Blood was collected by cardiac puncture on the 10The immunoprecipitation reactions between antigen (WWA/ESA) with respective hyperimmune sera developed in rabbits were detected by DID and CCIEP.2, which was previously washed in autoclaved double-distilled water and dried at room temperature. The strips were kept in the incubator at 37°C for 1 h. The serum samples (HIS and negative controls) at different dilutions  with 0.05% Tween 20 in PBS (PBST) were allowed to react with the antigen-loaded strip for 1 h at 37°C followed by washing of NC strips for 6 times in PBST (pH 7.4). The NC membranes were treated with goat anti-rabbit immunoglobulin G (IgG) horseradish peroxidase (HRP) conjugate at different dilutions  with PBST followed by washing 4 times each for 10 min. Subsequently, the Ab and conjugate-treated antigen-coated NC membrane strips were finally treated with the chromogen substrate di-aminobenzidine  in dark for 2-3 min. The dark brown spot appeared on the NC strip indicated positive reaction. The reaction was stopped with double-distilled water. Irrespective of the intensity of the color, the reaction was considered as positive and was documented by digital zoom camera (Nikon COOL PIX AW 120).Dot-ELISA was standardized by charging 1.5 µl of different dilutions of the antigens  on to nitrocellulose (NC) membrane of 1 cmThe lowest possible concentration of either WWA or ESA giving positive reaction with highest possible dilution of respective HIS and goat anti-IgG HRP conjugate in the form of brown spot on NC membrane, irrespective of color intensity, was considered as cutoff value and the same was taken as standard dilution for the screening of bovine serum samples from the field.CCIEP was also done to compare the sensitivity and specificity of the standardized dot-ELISA. Agarose was prepared in Tris borate buffer (pH 8.2). 1 g of agarose special, low EEO (HIMEDIA), was boiled in 100 ml of Tris borate buffer. 5 ml of molten gel was poured on to glass slides and allowed to solidify. Two wells of 4 mm diameter were cut with a well distance of 5 mm for trials with corresponding hyperimmune sera. The slides were connected by a filter paper wick dipped in buffer. A current of 50 mA per slide was applied and results were recorded after 90 min.The sensitivity and specificity of dot-ELISA was measured by standardized dot-ELISA procedure described as earlier.S. spindale and other (anodic well) with corresponding hyperimmune serum for evaluation of the test and later with sera from known positive or negative animal. Electrophoresis was carried out in suitable trough containing electrophoresis buffer. Both ends of the slides were connected with a filter paper wick dipped in buffer. A current of 50 mA per slide was applied for 90 min. The slides were washed in normal saline and stained with Coomassie brilliant blue.To evaluate the sensitivity and specificity of CCIEP, two rows of wells, each row having seven wells (each well having 4 mm diameter and a distance of 5 mm in between), were punched on agar slide. Wells were cut and the bases were sealed with molten agar. The well to be located on the cathode side was filled with antigens of The sensitivity of dot-ELISA and CCIEP was measured by screening 33 known positive sera collected from cattle which were later confirmed by finding schistosomes in the mesentery on post-slaughter examination.The specificity of laboratory dot-ELISA and CCIEP was measured by screening the sera of cattle reared in confined area and was found negative for the clinical symptoms of schistosomiasis or any other helminth ova in the feces.The laboratory-standardized dot-ELISA was tested for its efficacy in the diagnosis of bovine visceral schistosomiasis and further evaluation of dot-ELISA at field level.Around 288 bovine sera were collected from different parts in and around Hyderabad, Telangana state (erstwhile Andhra Pradesh) and subjected to standardized dot-ELISA with different antigens.The dot-ELISA was standardized at an antigen concentration of 91 ng for WWA and 93 ng for ESA which gave brown color dot with the chromogen substrate DAB after reacting with the serum and conjugate at 1:100 and 1:2000 dilutions, respectively .The overall sensitivity of dot-ELISA was determined as 76.74% and 80.48% with WWA and ESA, respectively, and specificity was 73.33% and 78.57% in WWA and ESA, respectively Tables- and 2. AS. spindale is the major cause of visceral schistosomiasis among bovines [Schistosomiasis has been recognized as one of the major parasitic diseases of livestock and human beings.  bovines . Routine bovines . The pre bovines . This stDot-ELISA, a modification of the standard ELISA assay, offers a practical tool for field studies. Moreover, the control of a disease is possible only based on the sensitivity and specificity of the diagnostic method. Dot-ELISA technique was first applied for detecting the anti-leishmania antibodies in human beings.Schistosoma haematobium infection in Egypt using purified soluble egg antigen, and the tests were proved to be valuable and can be used as an easy, fast, and accurate diagnostic technique [Different immunological techniques, namely, latex agglutination test, sandwich ELISA, and dot-ELISA were evaluated for the diagnosis of echnique .S. spindale dotted on NCM could give a positive brown-colored dot with 1:100 dilution of HIS when coupled with goat anti-rabbit IgG HRP followed by reaction with DAB substrate.In the present investigation, 91 ng of WWA and 93 ng of ESA of Various authors have tried to develop different kinds of ELISA tests including dot-ELISA which required antigens in nanogram quantities and the present findings were similar to them ,11-15.et al. [et al. [The dot-ELISA using WWA could detect 23 positive cases out of 33 known positive bovine sera, indicating an overall sensitivity of 76.74% whereas the same test with ESA detected 25 positive cases among 33 known positive bovine sera showing an overall sensitivity of 80.48%. Similarly, dot-ELISA using WWA gave 4 positive reactions with 11 known negative sera showing 73.33% of specificity. Whereas ESA reacted positively with 3 out of 11 known bovine sera negative for schistosomiasis indicating 78.57% of specificity. Our results were in correlation with the findings of earlier workers ,15. In tS. indicum and S. spindale were prepared and subjected to sodium dodecyl sulfate polyacrylamide gel electrophoresis to know the polypeptide profiles of the prepared antigen. Finally, four immunodominant proteins  were obtained and no significant variation was found between the immunodominant proteins S. indicum and S. spindale. As mixed infection is common in bovines, in this study, the mixed worm antigen was used for the detection of humoral immune status of infected cattle, sheep, and goats [Adult worm homogenates of nd goats .et al. [Cattle sera showed 32.8% (41/125) infection with WWA, 40.80% (51/125) infection with ESA, whereas buffalo sera showed 32.51% (53/163) infection with WWA and 40.49% (66/163) infection with ESA. Use of WWA in dot-ELISA detected anti-schistosomal antibodies in cattle indicating 90.93% (291/320) . The reset al.  who advoIn this study, buffaloes showed 32.51% and 40.49% infection using WWA and ESA, respectively. Results cannot be compared, due to the paucity of literature, with various authors as they reported either in cattle or in general bovines, but the present study shows a significant infection rate of schistosomiasis in cattle and buffaloes separately in Telangana state.S. spindale infection in bovines. The superiority of ESA in serodiagnosis has been observed by several workers for detecting other trematode infections, namely, Clonorchis sinensis, Paragonimus spp., Fasciola hepatica [Opisthorchis felineus [Paramphistomum cervi [As a whole, the dot-ELISA with ESA was found to be more sensitive (80.48%) and specific (78.57%) than WWA in detecting antibodies to hepatica , Opisthofelineus , and Parum cervi . This ESet al. [Even though some differences have been identified regarding the sensitivity and specificity of the dot-ELISA in its different applications ,20, the et al. .S. spindale antigens were useful for serodiagnosis of visceral schistosomiasis in bovines by dot-ELISA. Dot-ELISA using ESA could also be considered for ante-mortem diagnosis of schistosomal infection with a high degree of reliability under field conditions. This technique could form the basis for evolving a uniform system of seromonitoring of S. spindale in local bovine population, in turn enabling implementation of a suitable disease control strategy in the country.It is concluded that GSSM and KS have designed the concept and supervised the plan of work and also have prepared the manuscript. GR helped in collecting intestines from slaughter house and provided technical, as well as material support. GSSM analyzed and interpreted the data. All authors read and approved the final manuscript.


GEAs) requires controlling for neutral patterns of population structure to reduce the risk of false positives. However, a high degree of collinearity between climatic gradients and neutral population structure can greatly reduce power, and the performance of GEA methods in such case is rarely evaluated in empirical studies. In this study, we attempted to disentangle the effects of local adaptation and isolation by environment (IBE) from those of isolation by distance (IBD) and isolation by colonization from glacial refugia (IBC) using range‐wide samples in two white pine species. For this, SNPs from 168 genes, including 52 candidate genes for growth and phenology, were genotyped in 133 and 61 populations of Pinus strobus and P. monticola, respectively. For P. strobus and using all 153 SNPs, climate (IBE) did not significantly explained among‐population variation when controlling for IBD and IBC in redundancy analyses (RDAs). However, 26 SNPs were significantly associated with climate in single‐locus GEA analyses (Bayenv2 and LFMM), suggesting that local adaptation took place in the presence of high gene flow. For P. monticola, we found no evidence of IBE using RDAs and weaker signatures of local adaptation using GEA and FST outlier tests, consistent with adaptation via phenotypic plasticity. In both species, the majority of the explained among‐population variation (69 to 96%) could not be partitioned between the effects of IBE, IBD, and IBC. GEA methods can account differently for this confounded variation, and this could explain the small overlap of SNPs detected between Bayenv2 and LFMM. Our study illustrates the inherent difficulty of taking into account neutral structure in natural populations and the importance of sampling designs that maximize climatic variation, while minimizing collinearity between climatic gradients and neutral structure.Accurately detecting signatures of local adaptation using genetic‐environment associations ( Tree species generally exhibit moderate to high among‐population genetic variation for adaptive traits along climatic gradients  diverged <12 million years ago  “Can we detect genes showing signatures of local adaptation to climate in each species and in both species?” and (2) “Did local adaptation to climate contribute to the observed population structure (IBE) in P. monticola and P. strobus, or was it mostly driven by neutral processes ?”Here, we look for evidence of signatures of local adaptation and IBE using single nucleotide polymorphism (SNP) markers developed from 168 orthologous genes and genotyped on 133 22.1P. strobus and 348 individuals (61 populations) of P. monticola  before sampling.To investigate patterns of adaptation, we used a previously developed dataset  using the full contigs (coding and noncoding regions). We used only those matches with E‐values < 1 e−10 to conserve only high similarity matches. To look for candidates for local adaptation, all genes were blasted  against the Picea glauca gene catalog  from the Arabidopsis database . This was particularly useful for partial white pine sequences that were mainly composed of intron sequences.SNP development was conducted in parallel using putative orthologous gene sequences available for both Pinus strobus SNPs and 72 P. monticola SNPs occurred at different nucleotide positions within orthologous genes. Forty‐one genes (51 SNPs) and 48 genes (52 SNPs) contained SNPs only in P. strobus and P. monticola, respectively. We deduced SNP annotations  for 71 fully annotated genes from the WHISP dataset . Sixty‐eight 2.2r < .80) in at least one of the species (Table r > .80) in one species could still be retained if it was less correlated in the other species (r < .80) to ensure that we did not miss any important climatic variation . In addition, to reduce collinearity with the main axes of ancestry, we ensured that the selected variables were not highly correlated (r < .70) with the Q‐values from STRUCTURE (K = 2 within each species) obtained from Nadeau et al. .All analyses were performed separately for each species. We first looked for signatures of selection using 2.4P. strobus: r = .694; P. monticola: r = .794) and of BFs  were moderately high. The significance of each tested locus was determined according to Jeffrey's scale of evidence  unobserved or latent factors. We implemented the LFMM method using the default individual‐based data specification to avoid potential biases due to unequal population sample sizes . For k = 7, the average λ was close to or lower than 1 in each species  as recommended. A Benjamini and Hochberg .The second GEA method used latent factor mixed models (LFMM), as implemented in the software LFMM v.1.4 ) and the matrix of log‐transformed geographic distances . We then tested for IBE, while controlling for IBD, using partial Mantel tests. Climatic distances for the eight climatic variables were computed as the Euclidean distance between pairs of populations using the dist function in R. The correlation between linearized FST and climatic distance was tested for each climatic variable separately, with geographic distance included as a covariate. The significance of Mantel's r statistics for IBD and IBE was tested using n = 1,000 random permutations using the mantel function in the R ecodist package  to ensure that linear gradients in the data, as well as more complex patterns, were extracted. To prevent overfitting, we used a forward selection procedure with a stringent alpha value of 0.01  and three for P. strobus . Results were similar if we included only x and y . The north–south ancestry variable was the population Q‐values from STRUCTURE, which separated populations into K = 2 glacial lineages (northern and southern) within each species  were performed to partition the among‐population genetic variation into three components: IBE, IBD, and IBC. RDA is a multiple linear regression method performed between a matrix of dependent variables and matrices of independent variables. This type of multivariate analysis is more appropriate than Mantel tests when multiple climatic variables are analyzed to identify ecological drivers of population genetic structure . Missing data in the allele frequency matrix  were replaced by the within‐group (northern or southern group) average allele frequency. Small sample sizes can lead to inaccurate estimates of population allele frequencies and affect Mantel tests and RDAs. Therefore, we present the results of Mantel tests and RDAs performed using populations with sample sizes ≥5  Bayenv2 (BF > 3); and 2) LFMM  and three SNPs with atypically low FST values  and Z‐scores (LFMM) than those in P. monticola . Despite the large number of SNPs detected by each method, we found little overlap between Bayenv2 and LFMM . In P. strobus, five SNPs (19% of SNPs detected by GEAs) were detected by both Bayenv2 and LFMM; in P. monticola, no SNPs were common to both methods.GEA tests Bayenv2 and LFMM) detected several SNPs showing significant associations with one or more climatic variables  in P. strobus and 18 SNPs (18 genes) in P. monticola were detected as outliers by at least one method. A complete list of outlier SNPs and their annotations can be found in the online supporting information. Based on these results, we narrowed our search down to a set of highly supported candidate genes: Five SNPs (four genes) in P. strobus and one SNP in P. monticola were supported by two or more methods  were located within the same gene and were in moderate linkage disequilibrium , the number of genes containing outlier SNPs in both species did not differ from random expectation (p (≥3) = .415; permutation test with 10,000 random draws in R). None of the 34 orthologous SNPs  were outliers in both species.Finally, we looked for orthologous SNPs or genes that were detected as outliers in both species by any of the three methods . Three of the 79 orthologous genes contained outlier SNPs in both species Table . Given t3.23.2.1P. strobus, partial Mantel tests found that climatic distances for TD, bFFP, and eFFP were significantly correlated with genetic distances when controlled for geographic distance (p < .05), but only TD remained significant after correction for multiple testing (q = 0.036). In P. monticola, only elevational distance significantly explained genetic distance (p < .017), and this effect was marginally significant after correction for multiple testing (q = 0.077).We investigated the importance of IBE, IBD, and IBC as drivers of genomewide population structure with partial Mantel tests and RDAs. Mantel tests detected significant IBD in both species as genetic distance increased with geographic distance Table . In P. sQ‐values from STRUCTURE) representing recolonization history from northern and southern glacial refugia (IBC). In the uncorrected RDAs, climate, geography, and north–south ancestry each explained significant proportions of the genetic variation in both P. strobus and P. monticola, as measured by the adjusted R2  and geography  explained significant proportions of variation, but climate did not . Similarly, in P. monticola, significant variation could be attributed exclusively to north–south ancestry  and to geography , but not to climate . For both species, 69.0 to 73.9% of the explained variation was confounded between the effects of climate, north–south ancestry, and geography . This unexplained variation could be due to environmental variables that we did not take into account , but most of it is likely due to genetic drift. For example, under a standard island model, all population differentiation is only the result of the balance between genetic drift and nonspatial migration . In such a case, 100% of the among‐population genetic variation would remain unexplained by IBE, IBD, or IBC.Using RDAs, we partitioned among‐population genetic differentiation into three components: climate (IBE), geography (IBD), and north–south ancestry , but not in P. monticola  than when using all SNPs. However, the largest proportion of this explained variation (70.5 to 96.5%) was confounded between the three components.Finally, we performed RDAs using the subsets of candidate SNPs that showed signatures of local adaptation in Bayenv2 and LFMM analyses. In 4P. monticola and P. strobus. Using three GEA and FST outlier methods, we detected signatures of local adaptation in P. strobus, but such signatures were weaker in P. monticola. We found that, for the most part, the among‐population genetic differentiation could not be partitioned into exclusive effects of IBE, IBD, and IBC in both species, thus making it difficult to separate signatures of local adaptation from neutral patterns of population structure.In this study, we attempted to disentangle the effects of local adaptation and isolation by environment (IBE) from neutral processes, such as isolation by distance (IBD) or recolonization history from glacial refugia , in shaping among‐population genetic differentiation across the distribution of 4.1P. strobus, when using all SNPs, we did not detect strong evidence of IBE using partial Mantel tests , and climate did not explain among‐population variation in a RDA that controlled for IBD and IBC. However, single‐locus GEA analyses found a relatively large number of SNPs associated with climate and a significant proportion of the variation at these SNPs could be exclusively attributed to climate in multilocus RDAs. This corresponds to a scenario where gene flow is reduced among ecologically distant populations at loci directly involved in local adaptation or at closely linked loci, while there are no selective constraints on gene flow among environments for the rest of the genome  than in P. strobus. Moreover, climate did not explain among‐population variation in RDAs after controlling for IBD and IBC, even for the subsets of SNPs that were detected by GEA methods. Previous studies showed no or little differentiation in phenotypic traits among populations within the large northern group, and it has been suggested that P. monticola has adapted to a wide variety of climates mostly via phenotypic plasticity  explained the largest amount of among‐population variation in P. strobus and the second largest in P. monticola. This was expected since STRUCTURE looks for the dominant population structure patterns. For both species, populations from the northern and southern genetic groups detected by STRUCTURE may have originated from different glacial refugia, thus representing IBC  was determined by local adaptation to climate (IBE), geography (IBD), or postglacial recolonization from glacial refugia (IBC). For both species, IBD and IBC were significant drivers of population structure, but climate alone was not. After controlling for IBE and IBD, north–south ancestry . Although both methods essentially operate based on the same principles, that is, they test for GEAs after controlling for the portion of variation that is due to neutral population structure, their results differed greatly . The relative performance of Bayenv and LFMM depends on the demographic scenario and sampling design, and a relatively low overlap between the two methods has previously been observed in simulation studies  may explain the greater overlap between methods as compared with P. monticola. Thus, our results show that model differences in the correction for population structure can lead to little overlap between methods. Therefore, more studies comparing GEA methods that account differently for population structure in natural populations . In comparison, our dataset included candidate genes  as well as noncandidate genes. The higher percentage of GEAs detected in our study  may reflect the greater power derived from sampling a wider range of environmental variation. We included a larger number of populations from the southern and western edges of the distribution that experience different temperature and precipitation regimes compared with the rest of the range. Moreover, we included eight populations  from the southern genetic group detected in Nadeau et al. ; and a member of a plant‐specific C2 domain (GQ0081.BR.1 D09) involved in chloroplast and nuclear relocation in response to light (TAIR). Therefore, those genes are good candidates for further functional studies to confirm their role in local adaptation. SNPs that are not shared across methods should not be discarded entirely as simulations showed that loci under weak selection are often detected by only one method, although these loci may include more false positives . The discovery of genes that are involved in local adaptation to climate in both species could be expected given their relatively recent divergence (< 12 MYA) and the high degree of synteny among conserved orthologous genes in conifers , Prunier, Laroche, Beaulieu, and Bousquet (P. glauca and Pinus contorta (divergence time ~140 MYA), an exome‐wide study detected 47 genes (~10–18% of top candidate genes) with convergent signatures of local adaptation to low temperatures , IBD, and IBC, with only a small proportion of the variation attributed exclusively to climate in P. strobus. Such confounding of patterns of local adaptation with neutral population structure is expected to be common in natural landscapes  contains GenBank accession numbers for DNA sequences  are available upon request); gene and SNP annotations; SNP genotype table; sampling locations and climatic data; input files and scripts for the Bayescan, Bayenv2, LFMM, and RDA analyses. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Malayopython reticulatus ssp.) are primarily harvested from the wild for their skins—which are prized in the luxury leather goods industry. Trade dynamics of this CITES Appendix II listed species are complex and management approaches on the country or regional level appear obscure. Little is known about the actual geographic point-of-harvest of snakes, how genetic diversity is partitioned across the species range, how current harvest levels may affect the genetic viability of populations, and whether genetic structure could (or should) be accounted for when managing harvest quotas. As an initial survey, we use mitochondrial sequence data to define the broad-scale geographic structure of genetic diversity across a significant portion of the reticulated python’s native range. Preliminary results reveal: (1) prominent phylogenetic structure across populations east and west of Huxley’s modification of Wallace’s line. Thirty-four haplotypes were apportioned across two geographically distinct groups, estimated to be moderately (5.2%); (2) Philippine, Bornean and Sulawesian populations appear to cluster distinctly; (3) individuals from Ambon Island suggest recent human introduction. Malayopython reticulatus is currently managed as a single taxonomic unit across Southeast Asia yet these initial results may justify special management considerations of the Philippine populations as a phylogenetically distinct unit, that warrants further examination. In Indonesia, genetic structure does not conform tightly to political boundaries and therefore we advocate the precautionary designation and use of Evolutionary Significant Units within Malayopython reticulatus, to inform and guide regional adaptive management plans.As an important economic natural resource in Southeast Asia, reticulated pythons ( Habitat loss and degradation as a result of unsustainable per capita consumption of natural resources and rising human population levels  are haviMalayopython reticulatus ssp., Python bivittatus ssp., P. curtus, P. brongersmai and P. breitensteini) being heavily exploited for this purpose. Among these the reticulated python (M. reticulatus ssp.) is the most economically important species , the Philippine governments banned the export of M. reticulatus in 1986, and Viet Nam banned wild harvest of M. reticulatus in 1998 )Malayopython reticulatus across the species contemporary range, they offer an encouraging conservation genetics baseline that justifies implementing a precautionary approach [Although the results presented here offer a very provisional insight to the genetic structure of approach  to populMalayopython reticulatus are to be continually exploited for the skin trade, management strategies should not solely be tailored to obtaining the maximum economic yield. Populations should instead be managed following an adaptive management scheme to ensure their long-term sustainability . Among ity , and maTo regulate trade dynamics, wild harvest rates and exploitation levels require regular monitoring of the status of resource population(s) to reduce uncertainties.Further fine scale genetic analysis is also warranted to delineate local genetic partitions, and the potential application of adaptive genetic markers to establish conservation units should be considered (see ).To encourage and foster scientific collaborative networks with the countries of origin to permit construction of comprehensive, reference sample databases on which to base the development of robust traceability protocols.S1 TableThe table contains information about samples included in this study along with the corresponding haplotypes inferred from sequence variation across a mitochondrial cytochrome b fragment.(PDF)Click here for additional data file.


Seabirds are important components of marine ecosystems, both as predators and as indicators of ecological change, being conspicuous and sensitive to changes in prey abundance. To determine whether fluctuations in population sizes are localised or indicative of large-scale ecosystem change, we must first understand population structure and dispersal. King penguins are long-lived seabirds that occupy a niche across the sub-Antarctic zone close to the Polar Front. Colonies have very different histories of exploitation, population recovery, and expansion.We investigated the genetic population structure and patterns of colonisation of king penguins across their current range using a dataset of 5154 unlinked, high-coverage single nucleotide polymorphisms generated via restriction site associated DNA sequencing (RADSeq). Despite breeding at a small number of discrete, geographically separate sites, we find only very slight genetic differentiation among colonies separated by thousands of kilometers of open-ocean, suggesting migration among islands and archipelagos may be common. Our results show that the South Georgia population is slightly differentiated from all other colonies and suggest that the recently founded Falkland Island colony is likely to have been established by migrants from the distant Crozet Islands rather than nearby colonies on South Georgia, possibly as a result of density-dependent processes.The observed subtle differentiation among king penguin colonies must be considered in future conservation planning and monitoring of the species, and demographic models that attempt to forecast extinction risk in response to large-scale climate change must take into account migration. It is possible that migration could buffer king penguins against some of the impacts of climate change where colonies appear panmictic, although it is unlikely to protect them completely given the widespread physical changes projected for their Southern Ocean foraging grounds. Overall, large-scale population genetic studies of marine predators across the Southern Ocean are revealing more interconnection and migration than previously supposed.The online version of this article (doi:10.1186/s12862-016-0784-z) contains supplementary material, which is available to authorized users. Understanding the patterns and mechanisms of population structure is essential for successful species conservation . For exaAptenodytes patagonicus) are thought to be vulnerable to climate change impacts in the future [King penguins Aptenodyte future –11, folle future . The gloe future .Fig. 1KiOwing to their large and growing population size across most of their range, king penguins are currently listed as being of Least Concern on the IUCN’s Red List of Threatened Species  althoughAptenodytes forsteri) [Pygoscelis adeliae) [Pygoscelis papua) [Pygoscelis antarctica) [There have been no studies of genetic population structure of king penguins across their breeding range to date. A decade-long study at one colony in the Crozet Islands found that 77 % of juvenile king penguins returned to their natal colony . This suorsteri) , 28 and adeliae) , 30. This papua)  and chinarctica) , which darctica) , 34 thatOverall, king penguins are a highly mobile marine species with huge potential for dispersal; however, genetic divergence among colonies may exist as a result of nonphysical barriers, such as philopatry, local adaptation or isolation by colonisation . We therBlood was collected from 16 king penguins at each of: Volunteer Point on the Falkland Islands (Feb 2014), Fortuna Bay on South Georgia (Dec 2012), Baie du Marin on Possession Island in the Crozet Islands (Dec 2003–Jan 2004) and Sandy Bay on Macquarie Island (Dec 2005–Jan 2006)  to reduce RNA contamination. DNA concentration was measured with a Qubit (ThermoFisher Scientific) and high molecular weight was confirmed on a 1 % gel. We sequenced the mitochondrial hypervariable region  because this marker has revealed phylogeographic patterns within other penguin species , 29, 41.https://genomics.ed.ac.uk/) as described in Gonen et al. [We employed RADSeq to generate a dataset of genome-wide SNPs to assess population structure among the king penguin colonies. RAD libraries were prepared using the SbfI restriction enzyme, which was chosen because it produces a large number of RAD loci in king penguins . RADSeq n et al.  after Etn et al. . Brieflyprocess_radtags within the Stacks pipeline v1.35 [http://gigadb.org/dataset/100005) using bwa-mem [http://broadinstitute.github.io/picard).FastQC was used to assess read quality and check for adapter contamination. We used ne v1.35 , 45 to d bwa-mem . We prev bwa-mem ). We rempstacks – cstacks – sstacks – rxstacks – cstacks – sstacks - populations) to prepare a dataset of unlinked, filtered SNPs from the RAD reads, following many of the suggestions outlined in the framework of Benestan et al. [pstacks we selected a minimum stack depth of six reads mapping to the same location and used the bounded SNP model with a significance level of α = 0.05, an upper bound of 0.1 and a lower bound of 0.0041 (corresponding to the highest sequencing error rate recorded by phiX spikes in the sequencing lanes). All 64 individuals were used to build the catalog in cstacks. In rxstacks we removed confounded loci  with a conservative confidence limit of 0.25. Also in rxstacks, we removed excess haplotypes from individuals as well as any loci with a mean log likelihood < −10. Further filtering was conducted in the populations module. We removed SNPs with a minor allele frequency (MAF) < 0.01 because these are likely to be the result of sequencing errors. We also removed loci with a heterozygosity > 0.5, as these could be paralogs [p < 0.01 using the adegenet package in R [We used the Stacks pipeline  [The genetic structuring among king penguin colonies was assessed using several different methods. Firstly, the Weir and Cockerham  unbiased v2.0b27 . The hyp (SGoF+) .find.clusters K-means clustering algorithm within the adegenet package [structure v2.3.4 [FST results suggested that it is highly likely that these colonies have experienced admixture in the past and/or are still exchanging migrants. Models were run both with and without location priors to reflect the colony that each individual was sampled at, to detect subtle versus strong population structure. We conducted an initial run to infer the value of lambda, using a setting of K = 1 and an MCMC length of 100,000 generations , allowing lambda to vary. The value of lambda was then fixed at 0.39 for subsequent analyses. K values (the number of inferred clusters) from one to four were tested, with each value of K run a total of ten times from different random seeds. Each analysis was run for 150,000 generations with the first 50,000 discarded as burn-in. structure harvester web v0.6.94 [K values using the Evanno method [K were aligned using CLUMPP to check for multimodality, and the membership coefficients of each individual to each cluster were visualised with DISTRUCT v1.1 [To identify the number of genetic populations (“clusters”) among the 64 individuals, we used the  package , 51, rete v2.3.4 . The ana v0.6.94  was usedo method  and prepo method . ReplicaUCT v1.1 .optim.a.score.Discriminant Analysis of Principal Components (DAPC)  can be utraining set and a hold-out set and we identified the most informative SNPs for colony assignment using the training set in TRES v1.0 [n) to identify ancestry informative markers (AIMs), as In has been shown to be the most powerful method for estimating ancestry proportions [hold-out set of individuals to their populations of origin within Genodive. If the minor allele was not sampled in either population (i.e. its frequency was zero) the frequency was replaced with 0.005 as recommended by Paetkau et al. [Lh) as the test statistic and a Monte Carlo test with 10,000 generations to estimate the null distribution of likelihood values. The threshold value was defined for each population based on the null distribution, at α = 0.05.We conducted individual-based population assignment tests, in which an assignment algorithm attempts to assign the individuals in the test set to their population of origin . IndividRES v1.0 . We usedportions . For popu et al. . We usedWe used a species tree approach, as implemented in SNAPP  within Bhttps://rstudio.stat.washington.edu/shiny/phrynomics/). After this filtering step 1727 SNPs remained in the dataset. We conducted a rapid bootstrap analysis and search for the best-scoring maximum likelihood tree in a single program run using the MRE-based bootstopping criterion [http://popart.otago.ac.nz).We used RAxML v8.2.7  to inferriterion  to ascerriterion , 41, 76,riterion  and gentriterion , 41. We process_radtags and, of these, an average of 97.7 % successfully aligned to the emperor penguin reference genome. After specifying a minimum stack depth of six, a total of 34,171 RAD-tags remained, containing 35,766 SNPs. Our SNP filtering protocols resulted in a final dataset of 5154 SNPs [The 64 king penguin samples yielded 6.27–55.9 million unpaired reads per individual, with an average of 15.7 million reads per individual. On average, 97.3 % of reads per individual passed the quality filters in 154 SNPs  for use 154 SNPs ) and nonK = 3 and K = 2 for structure analyses with and without location priors, respectively, as determined by the Evanno method. However, the highest posterior mean log probability of the data for both scenarios (i.e. with and without the sampling location specified as a prior) was at K = 1. The rate of change in log probability (deltaK) is not defined at K = 1, and so the Evanno method is unable to determine whether this is actually the true value of K. This suggests that the signal for multiple clusters is weak. Inspection of the individual assignment plots , and that Macquarie and Crozet Islands are not significantly differentiated from each other (FST = 0.001). All other pairs of populations are statistically significantly differentiated after SGoF+ correction for multiple tests, however, the values of FST are very small (0.003–0.005), indicating only subtle genetic differences between these pairs of colonies. Therefore there are at least two slightly differentiated genetic populations among the sampled colonies: (1) the South Georgia population and (2) a population including the Falkland Islands, Crozet and Macquarie.Our measures of pairwise ST Table  indicateDAPC was unable to distinguish among the four sampled colonies or between the two slightly differentiated populations, with the distribution of individuals overlapping in both scenarios Fig. . For theca. 7500 km, whereas the nearby South Georgia colony is differentiated; based on our results it seems most likely that the Falkland Islands colony was founded by individuals from the Crozet Islands, rather than nearby South Georgia, even though there seems to be no obvious biological explanation for why this might be so.Overall, our analyses of population structure among the four king penguin colonies have yielded some surprising results. Despite separation of thousands of kilometers, there is very little genetic differentiation among these colonies. The South Georgia population was subtly differentiated from all other colonies, and the Macquarie population was further very subtly differentiated from some colonies by a subset of our analyses. It is particularly interesting that the Falkland Islands colony is genetically indistinguishable from the Crozet Islands colony, despite a separation of structure and pairwise FST results. However, aside from this one clade, the rest of the branching structure among the colonies is unresolved.We attempted to ascertain the branching structure among colonies using the species tree approach implemented in SNAPP. We have presented the full posterior distribution of trees in order to highlight the uncertainty in the topology Fig. . The majWe constructed maximum likelihood phylogenies for the full set of individuals using both HVR and the dataset of SNPs in order to determine if there are any strongly supported phylogenetic lineages that are not necessarily affiliated with the contemporary colony sites. The MRE bootstopping-criterion was satisfied by 550 and 800 bootstraps for the SNP and HVR searches, respectively. The best-scoring likelihood and majority rule extended consensus trees for the SNP dataset had very low support across the entire topology, with only a single node having a branch support value > 50 (topology not shown). The HVR topology did not show any more resolution, with 75 % of nodes in the tree having branch support values < 50 and no evidence of any well-supported phylogenetic lineages (topology not shown). A median joining network of the haplotypes of the mitochondrial HVR also showed no clear phylogeographic pattern and no evidence of ancestral haplotypes . Furthermore, the rate of population growth at Possession Island over the past several decades has been too great to have been maintained by intrinsic recruitment alone; therefore, the population growth must be partially attributable to immigration [The recent formation of new colonies at Volunteer Point on the Falkland Islands , Possessigration . Small nigration –25, 77. Previous studies have shown that seabirds with large foraging ranges or those that disperse widely in the non-breeding season are least likely to show genetic differentiation among colonies . During It is unclear whether the observed low level of genetic differentiation is maintained by consistent background levels of migration, or whether episodic periods of higher migration have occurred, or both. Abiotic factors such as glacial expansion and retreat, landslides, erosion, flooding, volcanic activity or other such catastrophic events  could reThe difference in the oceanic regime experienced by king penguins at South Georgia could explain why this colony was genetically differentiated from all other colonies . South GFST values are less than 0.05 (i.e. an order of magnitude greater than observed among king penguins) [F-statistics are also unreliable because the assumptions of the island model [FST to the number of migrants entering a population (Nm) are usually violated in natural systems, limiting the amount of quantitative information about migration that can be gained from F-statistics [While it would be useful to be able to determine the actual migration rates among the colonies studied here, the very low levels of genetic differentiation preclude the calculation of accurate estimates. Hence, whether the colonies are demographically linked or should be considered as separate management units cannot be determined . Furtherenguins) . Methodsnd model  that relatistics . Finallyatistics , which eatistics . Coalescatistics , 92.Aptenodytes genus, also has remarkable dispersal abilities, exhibiting very low levels of genetic differentiation around its global range [The lack of phylogenetic signal or mitochondrial lineages suggests that small populations of king penguins have not been isolated from one another in their recent history. Some colonies went through rapid declines when king penguins were harvested for their blubber. For example, the Macquarie Island colony was reduced from hundreds of thousands of birds to about 3000 . These ral range , 28, simal range , 76. Yetal range , reducinal range  would prOur study has revealed an unexpectedly low level of genetic differentiation among king penguin colonies spanning thousands of kilometers of the Southern Ocean, with some colonies separated by more than 7000 km showing no significant genetic divergence. On the other hand, the South Georgia colony does appear to be subtly differentiated from all other studied colonies, despite it lying in close proximity to the Falkland Island colony.The very low level of genetic differentiation we have shown among king penguin colonies needs to be considered in management plans to mitigate future climate change impacts on the species. Colonies within the same archipelago are highly likely to be panmictic and demographically linked, and thus monitoring of king penguins should be considered at the archipelago level, rather than at the colony level. The subtle differentiation we found between some archipelagos, and our inability to determine whether migration is consistent or episodic, cautions against the assumption that colonies are demographically linked globally. Therefore, as a precaution, we recommend that populations at the archipelago level are managed as separate units. Given the relatively few archipelagos that host king penguins, and that climate change effects will be heterogeneous across their range, declines at any of these locations should be considered as significant and would hinder the recovery of the species, even if a loss of genetic diversity would not occur.Demographic models that attempt to forecast extinction risk in response to large-scale climate change must also take into account migration. Recently, Tavecchia et al. 2016) showed that migration can decouple the relationship between population growth rates and climate variables, such that even if demographic rates are sensitive to climate-driven variations, this does not necessarily result in climate-driven population changes when immigration of new individuals occurs . Migrati showed t


Pelecanus occidentalis) in the southeastern United States have been exposed to regional extirpations, translocations, colony losses, and oil spills, but potential impacts on genetic diversity and population structure remain unknown. To investigate the cumulative impacts of recent disturbances and management actions, we analyzed seven microsatellite loci using genetic samples collected from 540 nestlings across twelve pelican colonies from two time periods, corresponding to before (n = 305) and after (n = 235) the 2010 Deepwater Horizon oil spill. Pre-2010 populations in Texas were significantly differentiated from Louisiana, Alabama, and Florida populations to the east, with reintroduced populations in southeastern Louisiana having less genetic diversity than sites in Texas, consistent with a recent bottleneck. In contrast, there was no evidence of a geographic component to genetic structure among colonies sampled after the spill, consistent with increased dispersal among sites following the event. This pattern may be associated with reduced philopatry in response to colony abandonment in the areas most heavily impacted by the Deepwater Horizon event, though other factors  were likely also involved. Future monitoring is necessary to determine if bottlenecks and loss of genetic variation are associated with the oil spill over time, and is recommended for other systems in which disturbance effects may be inferred via repeated genetic sampling.Environmental disturbances, both natural and anthropogenic, have the capacity to substantially impact animal behavior and abundance, which can in turn influence patterns of genetic diversity and gene flow. However, little empirical information is available on the nature and degree of such changes due to the relative rarity of longitudinal genetic sampling of wild populations at appropriate intervals. Addressing this knowledge gap is therefore of interest to evolutionary biologists, policy makers, and managers. In the past half century, populations of the brown pelican ( Regional patterns of intraspecific genetic diversity are of great interest to both evolutionary and conservation biologists, as populations lacking sufficient genetic variability are susceptible to an accumulation of fixed deleterious alleles via inbreeding and/or genetic drift, which may result in decreased adaptability, fitness, and probability of persistence –3. InforWhile genetic methods are often employed in ecological studies, variation in genetic parameters over ecologically relevant time scales has received relatively little attention compared to 'snapshot' studies, in which a single time frame is characterized with little information on how genetic patterns may be changing over time ,7. AmongPopulation genetic data can also be leveraged to investigate the impacts of large regional disturbances and human responses on genetic diversity and structure ,22–24, bPelecanus occidentalis carolinensis) is a widespread and iconic seabird whose northern Gulf of Mexico populations declined precipitously in the mid-1900s in response to anthropogenic stressors, leading to extirpation in the state of Louisiana by 1963 [The eastern brown pelican . We hereafter refer to these samples as “pre-2010” as we sampled all 2010 individuals well before Deepwater Horizon oil slicks in 2010 reached the colonies under examination. We sampled the region again in 2011 , including 8 of the 10 colonies sampled pre-2010. We sampled chicks aged 3–9 weeks , in JunPelecanus erythrorhynchos) [Pelecanus onocrotalus), Pel086 [We collected blood samples from the brachial vein in 75 mm capillary tubes and stored them in 600μL cell lysis solution until DNA could be extracted. We performed DNA extractions using Qiagen DNeasy Blood and Tissue Kits following manufacturer protocols, and isolated novel microsatellite loci for the species from a single individual using 454 sequencing  at the Shynchos) , PeEr04,, Pel086 . Probabi, Pel086 . We used, Pel086 ,52 to chThis study was carried out in accordance with field and laboratory protocols approved by the Institutional Animal Care and Use Committees of Tulane University (protocol no. 0395) and the University of Louisiana at Lafayette . Sampling efforts on individual colonies were limited by land manager recommendations, and all efforts were made during field sampling to minimize stress to study individuals and the colonies at large. Additionally, island access and sampling on protected or managed islands were approved by the Texas Parks and Wildlife Department (permit no. SPR-0410-046), Louisiana Department of Wildlife and Fisheries , Alabama Department of Conservation and Natural Resources , and Florida Fish and Wildlife Conservation Commission .O and HE, respectively), and inbreeding coefficients (FIS). We calculated allelic richness (AR) for each population and locus using the program ADZE version 1.0 [R and HE did not differ among population samples for either of the time periods. In analyses where we identified differences in genetic diversity estimates among samples, we used a Tukey test to determine statistical significance. For those breeding colonies where we had >25 samples in a time period, we assessed signatures of the species’ reintroduction using BOTTLENECK version 1.2.02 [We used GenAlEx to calculate several basic genetic parameters in both samples: number of alleles, observed and expected heterozygosity (Hsion 1.0 . We usedn 1.2.02 . We usedn 1.2.02 . We perfn 1.2.02 .ST) [ST/(1-Fst)) matrices and linear geographic distances between each colony pair [To investigate regional population structure, we applied several analyses to avoid potential issues of reliability associated with over-dependence on individual metrics or software . We calcST)  in GENEPST)  with theST) . To asseST)  on pairwony pair . We ran ony pair  and TESSony pair ,64 to inony pair . We ran ony pair  to obtaiony pair  along wiony pair . We alsoony pair  to impleony pair  and DISTony pair  to displony pair  and admiST matrix for each sampling period in GENEPOP, and imported matrices to program R version 3.4.0 [We used non-metric multi-dimensional scaling (NMDS) to visualize relationships among populations in both the pre- and post-2010 samples . We geneon 3.4.0  for ordion 3.4.0 .R and HE between the time periods using ANOVA, blocked by locus. To test for temporal changes in allele frequencies from each sampling location, we used Fisher’s test, implemented in GENEPOP. To assess temporal change in allele frequencies across loci, we estimated FC, an index of temporal allele frequency change [C while excluding alleles with frequencies of < 0.05 in any population; however, this exclusion had no effect on the results of comparisons among populations. To ensure that changes between pre- and post-2010 periods were not affected by a pre-2010 colony’s sampling year, we conducted a simple linear regression to correlate Fc with the interval between sampling bouts for each colony; this relationship was non-significant .We quantified changes in Ay change ,76, for y change , we alsoR and HE . The general pattern was for less genetic diversity in some sites in southeastern Louisiana relative to samples from Texas . With STRUCTURE analysis accounting for information on sampling location, the Evanno approach suggested the optimal number of clusters (K) was two. However, examining changes in the likelihood of different numbers of K suggested that there was no strong support for more than one cluster, a result supported by examination of individual assignments, which also did not provide evidence for multiple clusters. When we did not use sampling location as part of the analysis, both the Evanno approach and examination of likelihoods suggested there were two clusters present in the data, but examination of individual assignments still did not provide clear patterns of structuring in the data. In contrast, TESS results indicated that as many as six clusters were present. Individual TESS assignment plots from DISTRUCT with K = 2, the number suggested by STRUCTURE, showed partial separation between the two Texas colonies and the others to the east, with admixture in the western Louisiana colonies .The sizes of differences in gene frequencies, as measured by F samples . HoweverThe STRUCTURE analysis of the post-2010 samples was similar to the analysis for the pre-2010 samples. The Evanno approach suggested K = 3 with sampling location informing the analysis and K = 2 without; however, likelihood estimates and individual assignments suggested there was only one population cluster. In contrast to the pre-2010 analyses, examination of assignment plots in TESS based on runs with the lowest DIC values also did not yield a clear suggestion of any structuring. The NMDS ordination  and no significant interactions between time period and population . There were considerable changes in allele frequencies in all the populations, but the magnitude of the change was much larger in some populations than others. Allele frequencies were significantly different, following sequential Bonferroni adjustment of error rates, for Galliard Island in Alabama (P < 0.001) and Port Orange Island in Florida (P = 0.004). The estimates of FC reflected this pattern, with the largest values of change seen in Galliard, Port Orange, and Bird Islands  do not suggest that the predicted levels of variation would occur naturally between sampling events, and would support our initial assumption that the sampling bouts represent two distinct periods of interest. Also, if the oil spill caused widespread abandonment of nest sites in heavily impacted areas from southeastern Louisiana to western Florida, post-2010 genetic structure would be reduced relative to pre-2010 genetic structure. Alternatively, if prior gene flow was sufficient to prevent genetic differentiation among colonies, no observable effects of the spill would be expected.As predicted, we found considerable changes between the two sampling periods. The geographic component of observed differences in genetic diversity prior to the oil spill was absent in the samples collected post-2010, and temporal variation in population allele frequencies was non-zero in most sites. Furthermore, we found no effect of time between the pre- and post-2010 sampling on change in allele frequencies, despite variable time intervals between sampling periods for these colonies, supporting our assumption that the 2010 spill represents a legitimate point of demarcation between two ecologically relevant time periods. Several processes could explain these observed differences between the two samples. A study of Louisiana colonies over forty years suggested that when conditions at a colony site deteriorate, birds may move en masse to another site . SeveralAnother potential driver of our observed patterns is the dynamic nature of the Gulf coast network of breeding colonies, independent of large, punctuated disturbances such as the Deepwater Horizon spill. Coastal land loss and tropical storms have impacted barrier islands to a considerable degree throughout the region, with associated fluctuations in the size of breeding pelican populations ,102, as Our study represents one of the first examples of large change in gene frequencies and population structure in an avian population over a relatively short time , thus hiS1 File(DOCX)Click here for additional data file.S2 File(TIF)Click here for additional data file.