Comparison of Bayesian clustering and edge detection methods for inferring boundaries in landscape genetics

Assessing Genetic Structure in Common but Ecologically Distinct Carnivores: The Stone Marten and Red Fox

The identification of populations and spatial genetic patterns is important for ecological and conservation research, and spatially explicit individual-based methods have been recognised as powerful tools in this context. Mammalian carnivores are intrinsically vulnerable to habitat fragmentation but not much is known about the genetic consequences of fragmentation in common species. Stone martens (Martes foina) and red foxes (Vulpes vulpes) share a widespread Palearctic distribution and are considered habitat generalists, but in the Iberian Peninsula stone martens tend to occur in higher quality habitats. We compared their genetic structure in Portugal to see if they are consistent with their differences in ecological plasticity, and also to illustrate an approach to explicitly delineate the spatial boundaries of consistently identified genetic units. We analysed microsatellite data using spatial Bayesian clustering methods (implemented in the software BAPS, GENELAND and TESS), a progressive partitioning approach and a multivariate technique (Spatial Principal Components Analysis-sPCA). Three consensus Bayesian clusters were identified for the stone marten. No consensus was achieved for the red fox, but one cluster was the most probable clustering solution. Progressive partitioning and sPCA suggested additional clusters in the stone marten but they were not consistent among methods and were geographically incoherent. The contrasting results between the two species are consistent with the literature reporting stricter ecological requirements of the stone marten in the Iberian Peninsula. The observed genetic structure in the stone marten may have been influenced by landscape features, particularly rivers, and fragmentation. We suggest that an approach based on a consensus clustering solution of multiple different algorithms may provide an objective and effective means to delineate potential boundaries of inferred subpopulations. sPCA and progressive partitioning offer further verification of possible population structure and may be useful for revealing cryptic spatial genetic patterns worth further investigation.

Landscape genetics and population structure in Valley Oak (Quercus lobata Née)

PREMISE OF THE STUDY

Although long-distance pollen movement is common in wind-pollinated trees, barriers to gene flow may occur in species that have discontinuous ranges or are confined to certain habitat types. We investigated the genetic structure of Quercus lobata Née populations throughout much of their range in California. We assessed the connectivity of populations and determined if barriers to gene flow occurred, and if so, if they corresponded to landscape features.

METHODS

We collected leaf samples from 270 trees from 12 stands of Quercus lobata and genotyped these trees using eight polymorphic microsatellite loci. Genetic structure and clustering was evaluated using genetic distance methods, Bayesian clustering approaches, and network analysis of spatial genetic structure.

KEY RESULTS

The southernmost population of Quercus lobata sampled from the Santa Monica area comprised a separate genetic cluster from the rest of the species, suggesting that Transverse Ranges such as the San Gabriel Mountains limit gene flow. Population differentiation among the other sites was small but significant. Network analysis reflected higher connectivity among populations along the Central Coast range, with few connections spanning the dry, low Central Valley.

CONCLUSIONS

While long distance pollen movement has been shown to be common in oaks, on larger spatial scales, topographic features such as mountain ranges and the large, flat Central Valley of California limit gene flow. Such landscape features explain gene flow patterns much better than geographic distance alone.

Two Mitochondrial Barcodes for one Biological Species: The Case of European Kuhl's Pipistrelles (Chiroptera)

The Kuhl's pipistrelle (Pipistrellus kuhlii) is a Western Palaearctic species of bat that exhibits several deeply divergent mitochondrial lineages across its range. These lineages could represent cryptic species or merely ancient polymorphism, but no nuclear markers have been studied so far to properly assess the taxonomic status of these lineages. We examined here two lineages occurring in Western Europe, and used both mitochondrial and nuclear markers to measure degrees of genetic isolation between bats carrying them. The sampling focused on an area of strict lineage sympatry in Switzerland but also included bats from further south, in North Africa. All individuals were barcoded for the COI gene to identify their mitochondrial lineages and five highly polymorphic microsatellite loci were used to cluster them according to their nuclear genotypes. Despite this low number of nuclear markers, all North African nuclear genotypes were grouped in a highly distinct subpopulation when compared with European samples sharing the same mitochondrial barcodes. The reverse situation prevailed in Switzerland where bats carrying distinct barcodes had similar nuclear genotypes. There was a weak east/west nuclear structure of populations, but this was independent of mitochondrial lineages as bats carrying either variant were completely admixed. Thus, the divergent mitochondrial barcodes present in Western Europe do not represent cryptic species, but are part of a single biological species. We argue that these distinct barcodes evolved in allopatry and came recently into secondary contact in an area of admixture north of the Alps. Historical records from this area and molecular dating support such a recent bipolar spatial expansion. These results also highlight the need for using appropriate markers before claiming the existence of cryptic species based on highly divergent barcodes.

Inferring Population Genetic Structure in Widely and Continuously Distributed Carnivores: The Stone Marten (Martes foina) as a Case Study

The stone marten is a widely distributed mustelid in the Palaearctic region that exhibits variable habitat preferences in different parts of its range. The species is a Holocene immigrant from southwest Asia which, according to fossil remains, followed the expansion of the Neolithic farming cultures into Europe and possibly colonized the Iberian Peninsula during the Early Neolithic (ca. 7,000 years BP). However, the population genetic structure and historical biogeography of this generalist carnivore remains essentially unknown. In this study we have combined mitochondrial DNA (mtDNA) sequencing (621 bp) and microsatellite genotyping (23 polymorphic markers) to infer the population genetic structure of the stone marten within the Iberian Peninsula. The mtDNA data revealed low haplotype and nucleotide diversities and a lack of phylogeographic structure, most likely due to a recent colonization of the Iberian Peninsula by a few mtDNA lineages during the Early Neolithic. The microsatellite data set was analysed with a) spatial and non-spatial Bayesian individual-based clustering (IBC) approaches (STRUCTURE, TESS, BAPS and GENELAND), and b) multivariate methods [discriminant analysis of principal components (DAPC) and spatial principal component analysis (sPCA)]. Additionally, because isolation by distance (IBD) is a common spatial genetic pattern in mobile and continuously distributed species and it may represent a challenge to the performance of the above methods, the microsatellite data set was tested for its presence. Overall, the genetic structure of the stone marten in the Iberian Peninsula was characterized by a NE-SW spatial pattern of IBD, and this may explain the observed disagreement between clustering solutions obtained by the different IBC methods. However, there was significant indication for contemporary genetic structuring, albeit weak, into at least three different subpopulations. The detected subdivision could be attributed to the influence of the rivers Ebro, Tagus and Guadiana, suggesting that main watercourses in the Iberian Peninsula may act as semi-permeable barriers to gene flow in stone martens. To our knowledge, this is the first phylogeographic and population genetic study of the species at a broad regional scale. We also wanted to make the case for the importance and benefits of using and comparing multiple different clustering and multivariate methods in spatial genetic analyses of mobile and continuously distributed species.

Challenges in analysis and interpretation of microsatellite data for population genetic studies

Advancing technologies have facilitated the ever-widening application of genetic markers such as microsatellites into new systems and research questions in biology. In light of the data and experience accumulated from several years of using microsatellites, we present here a literature review that synthesizes the limitations of microsatellites in population genetic studies. With a focus on population structure, we review the widely used fixation (F ST) statistics and Bayesian clustering algorithms and find that the former can be confusing and problematic for microsatellites and that the latter may be confounded by complex population models and lack power in certain cases. Clustering, multivariate analyses, and diversity-based statistics are increasingly being applied to infer population structure, but in some instances these methods lack formalization with microsatellites. Migration-specific methods perform well only under narrow constraints. We also examine the use of microsatellites for inferring effective population size, changes in population size, and deeper demographic history, and find that these methods are untested and/or highly context-dependent. Overall, each method possesses important weaknesses for use with microsatellites, and there are significant constraints on inferences commonly made using microsatellite markers in the areas of population structure, admixture, and effective population size. To ameliorate and better understand these constraints, researchers are encouraged to analyze simulated datasets both prior to and following data collection and analysis, the latter of which is formalized within the approximate Bayesian computation framework. We also examine trends in the literature and show that microsatellites continue to be widely used, especially in non-human subject areas. This review assists with study design and molecular marker selection, facilitates sound interpretation of microsatellite data while fostering respect for their practical limitations, and identifies lessons that could be applied toward emerging markers and high-throughput technologies in population genetics.

Lack of detectable genetic differentiation between den populations of the Prairie Rattlesnake (Crotalusviridis) in a fragmented landscape

Numerous studies have reported genetic fragmentation of species whose habitat has been modified by roads and other anthropogenic features, but it is still not clear how most species respond to roads and whether genetic effects can be detected over a limited number of generations. We used road-crossing models and population genetic analysis (based on microsatellite loci) to make inferences about functional connectivity between populations of the Prairie Rattlesnake (Crotalus viridis (Rafinesque, 1818)) on opposite sides of the Trans-Canada Highway near Medicine Hat (Alberta, Canada). The road-crossing model predicted a high probability of mortality while crossing the Trans-Canada Highway. However, model-based genetic clustering methods (STRUCTURE and BAPS) did not detect structure; a nonmodel-based clustering method (DAPC) found structure, but most groups consisted of individuals captured throughout the study area. Estimates of effective population size were immeasurably large and power to detect genic differentiation was diminished if the effective size exceeded 500; this reduction in power was intensified when the number of loci was reduced (from eight to five to account for null alleles). Our results corroborate accounts of long-distance migration by this species and indicate that genetic fragmentation may not be easily detectable over this spatial and temporal scale.

Conservation genetics of the endangered Spotted Turtle (Clemmys guttata) illustrate the risks of “bottleneck tests”

Studies of population genetics in turtles have suggested that turtles do not experience genetic impacts of bottlenecks as strongly as expected. However, recent studies cast doubt on two commonly used tests implemented in the program BOTTLENECK, suggesting that these findings should be re-evaluated. The Spotted Turtle (Clemmys guttata (Schneider, 1792)) is endangered both globally and within Canada, but genetic data required to develop effective recovery strategies are unavailable. Here, we conducted the first study of population genetic structure in C. guttata. We then used multiple small populations of C. guttata as replicates to test whether the commonly used program BOTTLENECK could detect the genetic signature of bottlenecks in our study populations, which are all thought to have experienced significant declines in the past 2–3 generations (75 years). Turtles (n = 256) were genotyped at 11 microsatellite loci. A suite of Bayesian population genetics analyses and a principal coordinates analysis identified a minimum of 6 distinct genetic populations and a maximum of 10 differentiated subpopulations across the sampled Canadian range of C. guttata, which corresponded to demographically independent units. BOTTLENECK failed to detect population declines. A literature review found that bottleneck tests in 17 of 18 previous genetic studies of tortoises and freshwater turtles were based on suboptimal sampling, potentially confounding their results. High retention of genetic diversity (allelic richness and heterozygosity) in isolated populations of C. guttata and other turtle species is encouraging for species recovery, but conclusions about the prevalence of genetic bottlenecks in such populations should be re-examined.

Nonstationary patterns of isolation-by-distance: inferring measures of local genetic differentiation with Bayesian kriging

Patterns of isolation-by-distance (IBD) arise when population differentiation increases with increasing geographic distances. Patterns of IBD are usually caused by local spatial dispersal, which explains why differences of allele frequencies between populations accumulate with distance. However, spatial variations of demographic parameters such as migration rate or population density can generate nonstationary patterns of IBD where the rate at which genetic differentiation accumulates varies across space. To characterize nonstationary patterns of IBD, we infer local genetic differentiation based on Bayesian kriging. Local genetic differentiation for a sampled population is defined as the average genetic differentiation between the sampled population and fictive neighboring populations. To avoid defining populations in advance, the method can also be applied at the scale of individuals making it relevant for landscape genetics. Inference of local genetic differentiation relies on a matrix of pairwise similarity or dissimilarity between populations or individuals such as matrices of F_ST between pairs of populations. Simulation studies show that maps of local genetic differentiation can reveal barriers to gene flow but also other patterns such as continuous variations of gene flow across habitat. The potential of the method is illustrated with two datasets: single nucleotide polymorphisms from human Swedish populations and dominant markers for alpine plant species.

Temporal analysis of genetic structure to assess population dynamics of reintroduced swift foxes

Reintroductions are increasingly used to reestablish species, but a paucity of long-term postrelease monitoring has limited understanding of whether and when viable populations subsequently persist. We conducted temporal genetic analyses of reintroduced populations of swift foxes (Vulpes velox) in Canada (Alberta and Saskatchewan) and the United States (Montana). We used samples collected 4 years apart, 17 years from the initiation of the reintroduction, and 3 years after the conclusion of releases. To assess program success, we genotyped 304 hair samples, subsampled from the known range in 2000 and 2001, and 2005 and 2006, at 7 microsatellite loci. We compared diversity, effective population size, and genetic connectivity over time in each population. Diversity remained stable over time and there was evidence of increasing effective population size. We determined population structure in both periods after correcting for differences in sample sizes. The geographic distribution of these populations roughly corresponded with the original release locations, which suggests the release sites had residual effects on the population structure. However, given that both reintroduction sites had similar source populations, habitat fragmentation, due to cropland, may be associated with the population structure we found. Although our results indicate growing, stable populations, future connectivity analyses are warranted to ensure both populations are not subject to negative small-population effects. Our results demonstrate the importance of multiple sampling years to fully capture population dynamics of reintroduced populations. Análisis Temporal de la Estructura Genética para Evaluar la Dinámica Poblacional de Zorros (Vulpes velox) Reintroducidos.

Optimizing the trade-off between spatial and genetic sampling efforts in patchy populations: towards a better assessment of functional connectivity using an individual-based sampling scheme

Genetic data are increasingly used in landscape ecology for the indirect assessment of functional connectivity, that is, the permeability of landscape to movements of organisms. Among available tools, matrix correlation analyses (e.g. Mantel tests or mixed models) are commonly used to test for the relationship between pairwise genetic distances and movement costs incurred by dispersing individuals. When organisms are spatially clustered, a population-based sampling scheme (PSS) is usually performed, so that a large number of genotypes can be used to compute pairwise genetic distances on the basis of allelic frequencies. Because of financial constraints, this kind of sampling scheme implies a drastic reduction in the number of sampled aggregates, thereby reducing sampling coverage at the landscape level. We used matrix correlation analyses on simulated and empirical genetic data sets to investigate the efficiency of an individual-based sampling scheme (ISS) in detecting isolation-by-distance and isolation-by-barrier patterns. Provided that pseudo-replication issues are taken into account (e.g. through restricted permutations in Mantel tests), we showed that the use of interindividual measures of genotypic dissimilarity may efficiently replace interpopulation measures of genetic differentiation: the sampling of only three or four individuals per aggregate may be sufficient to efficiently detect specific genetic patterns in most situations. The ISS proved to be a promising methodological alternative to the more conventional PSS, offering much flexibility in the spatial design of sampling schemes and ensuring an optimal representativeness of landscape heterogeneity in data, with few aggregates left unsampled. Each strategy offering specific advantages, a combined use of both sampling schemes is discussed.

Biological races in humans

Races may exist in humans in a cultural sense, but biological concepts of race are needed to access their reality in a non-species-specific manner and to see if cultural categories correspond to biological categories within humans. Modern biological concepts of race can be implemented objectively with molecular genetic data through hypothesis-testing. Genetic data sets are used to see if biological races exist in humans and in our closest evolutionary relative, the chimpanzee. Using the two most commonly used biological concepts of race, chimpanzees are indeed subdivided into races but humans are not. Adaptive traits, such as skin color, have frequently been used to define races in humans, but such adaptive traits reflect the underlying environmental factor to which they are adaptive and not overall genetic differentiation, and different adaptive traits define discordant groups. There are no objective criteria for choosing one adaptive trait over another to define race. As a consequence, adaptive traits do not define races in humans. Much of the recent scientific literature on human evolution portrays human populations as separate branches on an evolutionary tree. A tree-like structure among humans has been falsified whenever tested, so this practice is scientifically indefensible. It is also socially irresponsible as these pictorial representations of human evolution have more impact on the general public than nuanced phrases in the text of a scientific paper. Humans have much genetic diversity, but the vast majority of this diversity reflects individual uniqueness and not race.

Fragmentation of Atlantic forest has not affected gene flow of a widespread seed-dispersing bat

Habitat loss and resultant fragmentation are major threats to biodiversity, particularly in tropical and subtropical ecosystems. It is increasingly urgent to understand fragmentation effects, which are often complex and vary across taxa, time and space. We determined whether recent fragmentation of Atlantic forest is causing population subdivision in a widespread and important Neotropical seed disperser: Artibeus lituratus (Chiroptera: Phyllostomidae). Genetic structure within highly fragmented forest in Paraguay was compared to that in mostly contiguous forest in neighbouring Misiones, Argentina. Further, observed genetic structure across the fragmented landscape was compared with expected levels of structure for similar time spans in realistic simulated landscapes under different degrees of reduction in gene flow. If fragmentation significantly reduced successful dispersal, greater population differentiation and stronger isolation by distance would be expected in the fragmented than in the continuous landscape, and genetic structure in the fragmented landscape should be similar to structure for simulated landscapes where dispersal had been substantially reduced. Instead, little genetic differentiation was observed, and no significant correlation was found between genetic and geographic distance in fragmented or continuous landscapes. Furthermore, comparison of empirical and simulated landscapes indicated empirical results were consistent with regular long-distance dispersal and high migration rates. Our results suggest maintenance of high gene flow for this relatively mobile and generalist species, which could be preventing or significantly delaying reduction in population connectivity in fragmented habitat. Our conclusions apply to A. lituratus in Interior Atlantic Forest, and do not contradict broad evidence that habitat fragmentation is contributing to extinction of populations and species, and poses a threat to biodiversity worldwide.

The influence of landscape on gene flow in the eastern massasauga rattlesnake (Sistrurus c. catenatus): insight from computer simulations

Understanding how gene flow shapes contemporary population structure requires the explicit consideration of landscape composition and configuration. New landscape genetic approaches allow us to link such heterogeneity to gene flow within and among populations. However, the attribution of cause is difficult when landscape features are spatially correlated, or when genetic patterns reflect past events. We use spatial Bayesian clustering and landscape resistance analysis to identify the landscape features that influence gene flow across two regional populations of the eastern massasauga rattlesnake, Sistrurus c. catenatus. Based on spatially explicit simulations, we inferred how habitat distribution modulates gene flow and attempted to disentangle the effects of spatially confounded landscape features. We found genetic clustering across one regional landscape but not the other, and also local differences in the effect of landscape on gene flow. Beyond the effects of isolation-by-distance, water bodies appear to underlie genetic differentiation among individuals in one regional population. Significant effects of roads were additionally detected locally, but these effects are possibly confounded with the signal of water bodies. In contrast, we found no signal of isolation-by-distance or landscape effects on genetic structure in the other regional population. Our simulations imply that these local differences have arisen as a result of differences in population density or tendencies for juvenile rather than adult dispersal. Importantly, our simulations also demonstrate that the ability to detect the consequences of contemporary anthropogenic landscape features (e.g. roads) on gene flow may be compromised when long-standing natural features (e.g. water bodies) co-exist on the landscape.

Effects of land management strategies on the dispersal pattern of a beneficial arthropod

Several arthropods are known to be highly beneficial to agricultural production. Consequently it is of great relevance to study the importance of land management and land composition for the conservation of beneficial aphid-predator arthropod species in agricultural areas. Therefore our study focusing on the beneficial arthropod Bembidion lampros had two main purposes: I) identifying the physical barriers to the species' dispersal in the agricultural landscape, and II) assessing the effect of different land management strategies (i.e. use of pesticides and intensiveness) on the dispersal patterns. The study was conducted using genetic analysis (microsatellite markers) applied to samples from two agricultural areas (in Denmark) with different agricultural intensity. Land management effects on dispersal patterns were investigated with particular focus on: physical barriers, use of pesticide and intensity of cultivation.

The results showed that Bembidion lampros disperse preferably through hedges rather than fields, which act as physical barriers to gene flow. Moreover the results support the hypothesis that organic fields act as reservoirs for the re-colonization of conventional fields, but only when cultivation intensity is low. These results show the importance of non-cultivated areas and of low intensity organic managed areas within the agricultural landscape as corridors for dispersal (also for a species typically found within fields). Hence, the hypothesis that pesticide use cannot be used as the sole predictor of agriculture's effect on wild species is supported as land structure and agricultural intensity can be just as important.

Gene flow from North Africa contributes to differential human genetic diversity in southern Europe

Human genetic diversity in southern Europe is higher than in other regions of the continent. This difference has been attributed to postglacial expansions, the demic diffusion of agriculture from the Near East, and gene flow from Africa. Using SNP data from 2,099 individuals in 43 populations, we show that estimates of recent shared ancestry between Europe and Africa are substantially increased when gene flow from North Africans, rather than Sub-Saharan Africans, is considered. The gradient of North African ancestry accounts for previous observations of low levels of sharing with Sub-Saharan Africa and is independent of recent gene flow from the Near East. The source of genetic diversity in southern Europe has important biomedical implications; we find that most disease risk alleles from genome-wide association studies follow expected patterns of divergence between Europe and North Africa, with the principal exception of multiple sclerosis.

Fine-scale population structure of blue whale wintering aggregations in the Gulf of California

Population differentiation in environments without well-defined geographical barriers represents a challenge for wildlife management. Based on a comprehensive database of individual sighting records (1988–2009) of blue whales from the winter/calving Gulf of California, we assessed the fine-scale genetic and spatial structure of the population using individual-based approaches. Skin samples of 187 individuals were analyzed for nine microsatellite loci. A single population with no divergence among years and months and no isolation by distance (Rxy = 0.1–0.001, p>0.05) were found. We ran two Bayesian clustering methods using Structure and Geneland softwares in two different ways: 1) a general analysis including all individuals in which a single cluster was identified with both softwares; 2) a specific analysis of females only in which two main clusters (Loreto Bay and northern areas, and San Jose-La Paz Bay area) were revealed by Geneland program. This study provides information indicating that blue whales wintering in the Gulf of California are part of a single population unit and showed a fine-scale structure among females, possibly associated with their high site fidelity, particularly when attending calves. It is likely that the loss of genetic variation is minimized by male mediated gene flow, which may reduce the genetic drift effect. Opportunities for kin selection may also influence calf survival and, in consequence, have a positive impact on population demography in this small and endangered population.

Landscape genetics of leaf-toed geckos in the tropical dry forest of northern Mexico

Habitat fragmentation due to both natural and anthropogenic forces continues to threaten the evolution and maintenance of biological diversity. This is of particular concern in tropical regions that are experiencing elevated rates of habitat loss. Although less well-studied than tropical rain forests, tropical dry forests (TDF) contain an enormous diversity of species and continue to be threatened by anthropogenic activities including grazing and agriculture. However, little is known about the processes that shape genetic connectivity in species inhabiting TDF ecosystems. We adopt a landscape genetic approach to understanding functional connectivity for leaf-toed geckos (Phyllodactylus tuberculosus) at multiple sites near the northernmost limit of this ecosystem at Alamos, Sonora, Mexico. Traditional analyses of population genetics are combined with multivariate GIS-based landscape analyses to test hypotheses on the potential drivers of spatial genetic variation. Moderate levels of within-population diversity and substantial levels of population differentiation are revealed by FST and Dest. Analyses using structure suggest the occurrence of from 2 to 9 genetic clusters depending on the model used. Landscape genetic analysis suggests that forest cover, stream connectivity, undisturbed habitat, slope, and minimum temperature of the coldest period explain more genetic variation than do simple Euclidean distances. Additional landscape genetic studies throughout TDF habitat are required to understand species-specific responses to landscape and climate change and to identify common drivers. We urge researchers interested in using multivariate distance methods to test for, and report, significant correlations among predictor matrices that can impact results, particularly when adopting least-cost path approaches. Further investigation into the use of information theoretic approaches for model selection is also warranted.

A simulation-based evaluation of methods for inferring linear barriers to gene flow

Different analytical techniques used on the same data set may lead to different conclusions about the existence and strength of genetic structure. Therefore, reliable interpretation of the results from different methods depends on the efficacy and reliability of different statistical methods. In this paper, we evaluated the performance of multiple analytical methods to detect the presence of a linear barrier dividing populations. We were specifically interested in determining if simulation conditions, such as dispersal ability and genetic equilibrium, affect the power of different analytical methods for detecting barriers. We evaluated two boundary detection methods (Monmonier's algorithm and WOMBLING), two spatial Bayesian clustering methods (TESS and GENELAND), an aspatial clustering approach (STRUCTURE), and two recently developed, non-Bayesian clustering methods [PSMIX and discriminant analysis of principal components (DAPC)]. We found that clustering methods had higher success rates than boundary detection methods and also detected the barrier more quickly. All methods detected the barrier more quickly when dispersal was long distance in comparison to short-distance dispersal scenarios. Bayesian clustering methods performed best overall, both in terms of highest success rates and lowest time to barrier detection, with GENELAND showing the highest power. None of the methods suggested a continuous linear barrier when the data were generated under an isolation-by-distance (IBD) model. However, the clustering methods had higher potential for leading to incorrect barrier inferences under IBD unless strict criteria for successful barrier detection were implemented. Based on our findings and those of previous simulation studies, we discuss the utility of different methods for detecting linear barriers to gene flow.

Pleistocene and ecological effects on continental-scale genetic differentiation in the bobcat (Lynx rufus)

The potential for widespread, mobile species to exhibit genetic structure without clear geographic barriers is a topic of growing interest. Yet the patterns and mechanisms of structure--particularly over broad spatial scales--remain largely unexplored for these species. Bobcats occur across North America and possess many characteristics expected to promote gene flow. To test whether historical, topographic or ecological factors have influenced genetic differentiation in this species, we analysed 1 kb mtDNA sequence and 15 microsatellite loci from over 1700 samples collected across its range. The primary signature in both marker types involved a longitudinal cline with a sharp transition, or suture zone, occurring along the Great Plains. Thus, the data distinguished bobcats in the eastern USA from those in the western half, with no obvious physical barrier to gene flow. Demographic analyses supported a scenario of expansion from separate Pleistocene refugia, with the Great Plains representing a zone of secondary contact. Substructure within the two main lineages likely reflected founder effects, ecological factors, anthropogenic/topographic effects or a combination of these forces. Two prominent topographic features, the Mississippi River and Rocky Mountains, were not supported as significant genetic barriers. Ecological regions and environmental correlates explained a small but significant proportion of genetic variation. Overall, results implicate historical processes as the primary cause of broad-scale genetic differentiation, but contemporary forces seem to also play a role in promoting and maintaining structure. Despite the bobcat's mobility and broad niche, large-scale landscape changes have contributed to significant and complex patterns of genetic structure.