Looks can be deceiving: speciation dynamics of co-distributed Angophora (Myrtaceae) species in a varying landscape

Understanding the mechanisms underlying species divergence remains a central goal in evolutionary biology. Landscape genetics can be a powerful tool for examining evolutionary processes. We used genome-wide scans to genotype samples from populations of eight Angophora species. Angophora is a small genus within the eucalypts comprising common and rare species in a heterogeneous landscape, making it an appropriate group to study speciation. We found A. hispida was highly differentiated from the other species. Two subspecies of A. costata (subsp. costata and subsp. euryphylla) formed a group, while the third (subsp. leiocarpa, which is only distinguished by its smooth fruits and provenance) was supported as a distinct pseudocryptic species. Other species that are morphologically distinct could not be genetically differentiated (e.g., A. floribunda and A. subvelutina). Distribution and genetic differentiation within Angophora were strongly influenced by temperature and humidity, as well as biogeographic barriers, particularly rivers and higher elevation regions. While extensive introgression was found between many populations of some species (e.g., A. bakeri and A. floribunda), others only hybridized at certain locations. Overall, our findings suggest multiple mechanisms drove evolutionary diversification in Angophora and highlight how genome-wide analyses of related species in a diverse landscape can provide insights into speciation.

The use and misuse of regression models in landscape genetic analyses

The field of landscape genetics has been rapidly evolving, adopting and adapting analytical frameworks to address research questions. Current studies are increasingly using regression-based frameworks to infer the individual contributions of landscape and habitat variables on genetic differentiation. This paper outlines appropriate and inappropriate uses of multiple regression for these purposes, and demonstrates through simulation the limitations of different analytical frameworks for making correct inference. Of particular concern are recent studies seeking to explain genetic differences by fitting regression models with effective distance variables calculated independently on separate landscape resistance surfaces. When moving across the landscape, organisms cannot respond independently and uniquely to habitat and landscape features. Analyses seeking to understand how landscape features affect gene flow should model a single conductance or resistance surface as a parameterized function of relevant spatial covariates, and estimate the values of these parameters by linking a single set of resistance distances to observed genetic dissimilarity via a loss function. While this loss function may involve a regression-like step, the associated nuisance parameters are not interpretable in terms of organismal movement and should not be conflated with what is actually of interest: the mapping between spatial covariates and conductance/resistance. The growth and evolution of landscape genetics as a field has been rapid and exciting. It is the goal of this paper to highlight past missteps and demonstrate limitations of current approaches to ensure that future use of regression models will appropriately consider the process being modeled, which will provide clarity to model interpretation.

Different landscape effects on the genetic structure of two broadly distributed woody legumes, Acacia salicina and A. stenophylla (Fabaceae)

Restoring degraded landscapes has primarily focused on re-establishing native plant communities. However, little is known with respect to the diversity and distribution of most key revegetation species or the environmental and anthropogenic factors that may affect their demography and genetic structure. In this study, we investigated the genetic structure of two widespread Australian legume species (Acacia salicina and Acacia stenophylla) in the Murray-Darling Basin (MDB), a large agriculturally utilized region in Australia, and assessed the impact of landscape structure on genetic differentiation. We used AFLP genetic data and sampled a total of 28 A. salicina and 30 A. stenophylla sampling locations across southeastern Australia. We specifically evaluated the importance of four landscape features: forest cover, land cover, water stream cover, and elevation. We found that both species had high genetic diversity (mean percentage of polymorphic loci, 55.1% for A. salicina versus. 64.3% for A. stenophylla) and differentiation among local sampling locations (A. salicina: ΦPT = 0.301, 30%; A. stenophylla: ΦPT = 0.235, 23%). Population structure analysis showed that both species had high levels of structure (6 clusters each) and admixture in some sampling locations, particularly A. stenophylla. Although both species have a similar geographic range, the drivers of genetic connectivity for each species were very different. Genetic variation in A. salicina seems to be mainly driven by geographic distance, while for A. stenophylla, land cover appears to be the most important factor. This suggests that for the latter species, gene flow among populations is affected by habitat fragmentation. We conclude that these largely co-occurring species require different management actions to maintain population connectivity. We recommend active management of A. stenophylla in the MDB to improve gene flow in the adversity of increasing disturbances (e.g., droughts) driven by climate change and anthropogenic factors.

Anthropogenic and natural barriers affect genetic connectivity in an Alpine butterfly

Dispersal is a key biological process serving several functions including connectivity among populations. Habitat fragmentation caused by natural or anthropogenic structures may hamper dispersal, thereby disrupting genetic connectivity. Investigating factors affecting dispersal and gene flow is important in the current era of anthropogenic global change, as dispersal comprises a vital part of a species' resilience to environmental change. Using finescale landscape genomics, we investigated gene flow and genetic structure of the Sooty Copper butterfly (Lycaena tityrus) in the Alpine Ötz valley system in Austria. We found surprisingly high levels of gene flow in L. tityrus across the region. Nevertheless, ravines, forests, and roads had effects on genetic structure, while rivers did not. The latter is surprising as roads and rivers have a similar width and run largely in parallel in our study area, pointing towards a higher impact of anthropogenic compared with natural linear structures. Additionally, we detected eleven loci potentially under thermal selection, including ones related to membranes, metabolism, and immune function. This study demonstrates the usefulness of molecular approaches in obtaining estimates of dispersal and population processes in the wild. Our results suggest that, despite high gene flow in the Alpine valley system investigated, L. tityrus nevertheless seems to be vulnerable to anthropogenically-driven habitat fragmentation. With anthropogenic rather than natural linear structures affecting gene flow, this may have important consequences for the persistence of species such as the butterfly studied here in altered landscapes.

Canonical correlations reveal adaptive loci and phenotypic responses to climate in perennial ryegrass

Germplasm from perennial ryegrass (Lolium perenne L.) natural populations is useful for breeding because of its adaptation to a wide range of climates. Climate-adaptive genes can be detected from associations between genotype, phenotype and climate but an integrated framework for the analysis of these three sources of information is lacking. We used two approaches to identify adaptive loci in perennial ryegrass and their effect on phenotypic traits. First, we combined Genome-Environment Association (GEA) and GWAS analyses. Then, we implemented a new test based on a Canonical Correlation Analysis (CANCOR) to detect adaptive loci. Furthermore, we improved the previous perennial ryegrass gene set by de novo gene prediction and functional annotation of 39,967 genes. GEA-GWAS revealed eight outlier loci associated with both environmental variables and phenotypic traits. CANCOR retrieved 633 outlier loci associated with two climatic gradients, characterized by cold-dry winter versus mild-wet winter and long rainy season versus long summer, and pointed out traits putatively conferring adaptation at the extremes of these gradients. Our CANCOR test also revealed the presence of both polygenic and oligogenic climatic adaptations. Our gene annotation revealed that 374 of the CANCOR outlier loci were positioned within or close to a gene. Co-association networks of outlier loci revealed a potential utility of CANCOR for investigating the interaction of genes involved in polygenic adaptations. The CANCOR test provides an integrated framework to analyse adaptive genomic diversity and phenotypic responses to environmental selection pressures that could be used to facilitate the adaptation of plant species to climate change.

MetaPopGen 2.0: A multilocus genetic simulator to model populations of large size

Multilocus genetic processes in subdivided populations can be complex and difficult to interpret using theoretical population genetics models. Genetic simulators offer a valid alternative to study multilocus genetic processes in arbitrarily complex scenarios. However, the use of forward-in-time simulators in realistic scenarios involving high numbers of individuals distributed in multiple local populations is limited by computation time and memory requirements. These limitations increase with the number of simulated individuals. We developed a genetic simulator, MetaPopGen 2.0, to model multilocus population genetic processes in subdivided populations of arbitrarily large size. It allows for spatial and temporal variation in demographic parameters, age structure, adult and propagule dispersal, variable mutation rates and selection on survival and fecundity. We developed MetaPopGen 2.0 in the R environment to facilitate its use by non-modeler ecologists and evolutionary biologists. We illustrate the capabilities of MetaPopGen 2.0 for studying adaptation to water salinity in the striped red mullet Mullus surmuletus.

The effect of gene flow from unsampled demes in landscape genetic analysis

An assumption of correlative landscape genetic methods is that genetic differentiation at neutral markers arises solely from the degree to which the intervening landscape between individuals or populations resists gene flow. However, this assumption is violated when gene flow occurs into the sampled population from an unsampled, differentiated deme. This may happen when sampling within only a portion of a population's extent or when closely related species hybridize with the sampled population. In both cases, violation of the modelling assumptions has the potential to reduce landscape genetic model selection accuracy and result in poor inferences. We used individual-based population genetic simulations in complex landscapes within a model selection framework to explore the potential confounding effect of gene flow from unsampled demes. We hypothesized that as gene flow from outside the sampling extent increased, model selection accuracy would decrease due to the formation of a hybrid zone where allele frequencies were perturbed in a way that was not correlated with effective distances between sampled individuals. Surprisingly, we found this expectation was unfounded, because the reduced accuracy due to admixture was counteracted by an increase in allelic diversity as alleles spread from the unsampled deme into the sampled population. These new alleles increased the power to detect landscape genetic relationships and even slightly improving model selection accuracy overall. This is a reassuring result, suggesting that sampling the full extent of a population or related species that may hybridize may be unnecessary, as long as other well-established sampling requirements are met.

The Influence of Environmental Variation on the Genetic Structure of a Poison Frog Distributed Across Continuous Amazonian Rainforest

Biogeographic barriers such as rivers have been shown to shape spatial patterns of biodiversity in the Amazon basin, yet relatively little is known about the distribution of genetic variation across continuous rainforest. Here, we characterize the genetic structure of the brilliant-thighed poison frog (Allobates femoralis) across an 880-km-long transect along the Purus-Madeira interfluve south of the Amazon river, based on 64 individuals genotyped at 7609 single-nucleotide polymorphism (SNP) loci. A population tree and clustering analyses revealed 4 distinct genetic groups, one of which was strongly divergent. These genetic groups were concomitant with femoral spot coloration differences, which was intermediate within a zone of admixture between two of the groups. The location of these genetic groups did not consistently correspond to current ecological transitions between major forest types. A multimodel approach to quantify the relative influence of isolation-by-geographic distance (IBD) and isolation-by-environmental resistance (IBR) nevertheless revealed that, in addition to a strong signal of IBD, spatial genetic differentiation was explained by IBR primarily linked to dry season intensity (r2 = 8.4%) and canopy cover (r2 = 6.4%). We show significant phylogenetic divergence in the absence of obvious biogeographical barriers and that finer-scaled measures of genetic structure are associated with environmental variables also known to predict the density of A. femoralis.

Population expansion and genomic adaptation to agricultural environments of the soybean looper, Chrysodeixis includens

Evolutionary studies of insect pests improve our ability to anticipate problems in agricultural ecosystems, such as pest outbreaks, control failures, or expansions of the host range. Here, we investigated the mechanisms underlying the evolutionary processes behind the recent census size expansion and local adaptation of Chrysodeixis includens. First, we sequenced mitochondrial markers to conduct a phylogeographic investigation of C. includens historical processes. Then, we combined a de novo genotyping-by-sequencing approach with a study of agricultural landscapes to uncover recent processes of adaptation. Primarily, we found low genetic diversity across all markers and clear indications of a recent demographic expansion. We also found a lack of significant isolation by distance (IBD), and weak or absent genetic structure considering geographic locations. However, we did find initial signs of population differentiation that were associated with host plant types (i.e., soybean and cotton). Agricultural landscape attributes, including soybean crops, were significantly associated with putative markers under positive selection. Moreover, positive selection associated with host differentiation was putatively linked to digestive enzymes. This study showed how landscape composition and host plants can affect the evolutionary process of agricultural pest insects such as C. includens.

Distribution of genetic variation underlying adult migration timing in steelhead of the Columbia River basin

Fish migrations are energetically costly, especially when moving between freshwater and saltwater, but are a viable strategy for Pacific salmon and trout (Oncorhynchus spp.) due to the advantageous resources available at various life stages. Anadromous steelhead (O. mykiss) migrate vast distances and exhibit variation for adult migration phenotypes that have a genetic basis at candidate genes known as greb1L and rock1. We examined the distribution of genetic variation at 13 candidate markers spanning greb1L, intergenic, and rock1 regions versus 226 neutral markers for 113 populations (n = 9,471) of steelhead from inland and coastal lineages in the Columbia River. Patterns of population structure with neutral markers reflected genetic similarity by geographic region as demonstrated in previous studies, but candidate markers clustered populations by genetic variation associated with adult migration timing. Mature alleles for late migration had the highest frequency overall in steelhead populations throughout the Columbia River, with only 9 of 113 populations that had a higher frequency of premature alleles for early migration. While a single haplotype block was evident for the coastal lineage, we identified multiple haplotype blocks for the inland lineage. The inland lineage had one haplotype block that corresponded to candidate markers within the greb1L gene and immediately upstream in the intergenic region, and the second block only contained candidate markers from the intergenic region. Haplotype frequencies had similar patterns of geographic distribution as single markers, but there were distinct differences in frequency between the two haplotype blocks for the inland lineage. This may represent multiple recombination events that differed between lineages where phenotypic differences exist between freshwater entry versus arrival timing as indicated by Micheletti et al. (2018a). Redundancy analyses were used to model environmental effects on allelic frequencies of candidate markers, and significant variables were migration distance, temperature, isothermality, and annual precipitation. This study improves our understanding of the spatial distribution of genetic variation underlying adult migration timing in steelhead as well as associated environmental factors and has direct conservation and management implications.

DNA barcode assessment and population structure of aphidophagous hoverfly Sphaerophoria scripta: Implications for conservation biological control

With the advent of integrated pest management, the conservation of indigenous populations of natural enemies of pest species has become a relevant practice, necessitating the accurate identification of beneficial species and the inspection of evolutionary mechanisms affecting the long-time persistence of their populations. The long hoverfly, Sphaerophoria scripta, represents one of the most potent aphidophagous control agents due to a worldwide distribution and a favorable constellation of biological traits. Therefore, we assessed five European S. scripta populations by combining molecular (cytochrome c oxidase subunit I- COI, internal transcribed spacer 2- ITS2, and allozyme loci) and morphological (wing size and shape) characters. COI sequences retrieved in this study were conjointly analyzed with BOLD/GenBank sequences of the other Sphaerophoria species to evaluate whether COI possessed a sufficient diagnostic value as a DNA barcode marker to consistently delimit allospecific individuals. Additionally, the aforementioned characters were used to inspect the population structure of S. scripta in Europe using methods based on individual- and population-based genetic differences, as well as geometric morphometrics of wing traits. The results indicate numerous shared COI haplotypes among different Sphaerophoria species, thus disqualifying this marker from being an adequate barcoding region in this genus. Conversely, the analyses of population structuring revealed high population connectivity across Europe, therefore indicating strong tolerance of S. scripta to environmental heterogeneity. The results imply a multilocus approach as the next step in molecular identification of different Sphaerophoria species, while confirming the status of S. scripta as a powerful biocontrol agent of economically relevant aphid pests.

Comparative landscape genetics reveals differential effects of environment on host and pathogen genetic structure in Tasmanian devils (Sarcophilus harrisii) and their transmissible tumour

Genetic structure in host species is often used to predict disease spread. However, host and pathogen genetic variation may be incongruent. Understanding landscape factors that have either concordant or divergent influence on host and pathogen genetic structure is crucial for wildlife disease management. Devil facial tumour disease (DFTD) was first observed in 1996 and has spread throughout almost the entire Tasmanian devil geographic range, causing dramatic population declines. Whereas DFTD is predominantly spread via biting among adults, devils typically disperse as juveniles, which experience low DFTD prevalence. Thus, we predicted little association between devil and tumour population structure and that environmental factors influencing gene flow differ between devils and tumours. We employed a comparative landscape genetics framework to test the influence of environmental factors on patterns of isolation by resistance (IBR) and isolation by environment (IBE) in devils and DFTD. Although we found evidence for broad-scale costructuring between devils and tumours, we found no relationship between host and tumour individual genetic distances. Further, the factors driving the spatial distribution of genetic variation differed for each. Devils exhibited a strong IBR pattern driven by major roads, with no evidence of IBE. By contrast, tumours showed little evidence for IBR and a weak IBE pattern with respect to elevation in one of two tumour clusters we identify herein. Our results warrant caution when inferring pathogen spread using host population genetic structure and suggest that reliance on environmental barriers to host connectivity may be ineffective for managing the spread of wildlife diseases. Our findings demonstrate the utility of comparative landscape genetics for identifying differential factors driving host dispersal and pathogen transmission.

Genetic Structure of Invasive Baby's Breath (Gypsophila paniculata L.) Populations in a Michigan Dune System

Coastal sand dunes are dynamic ecosystems with elevated levels of disturbance and are highly susceptible to plant invasions. One invasive plant that is of concern to the Great Lakes system is Gypsophila paniculata L. (perennial baby’s breath). The presence of G. paniculata negatively impacts native species and has the potential to alter ecosystem dynamics. Our research goals were to (1) estimate the genetic structure of invasive G. paniculata along the Michigan dune system and (2) identify landscape features that influence gene flow in this area. We analyzed 12 populations at 14 nuclear and two chloroplast microsatellite loci. We found strong genetic structure among populations (global F_ST = 0.228), and pairwise comparisons among all populations yielded significant F_ST values. Results from clustering analysis via STRUCTURE and discriminant analysis of principal components (DAPC) suggest two main genetic clusters that are separated by the Leelanau Peninsula, and this is supported by the distribution of chloroplast haplotypes. Land cover and topography better explained pairwise genetic distances than geographic distance alone, suggesting that these factors influence the genetic distribution of populations within the dunes system. Together, these data aid in our understanding of how invasive populations move through the dune landscape, providing valuable information for managing the spread of this species.

Gene flow and climate-associated genetic variation in a vagile habitat specialist

Previous work in landscape genetics suggests that geographic isolation is of greater importance to genetic divergence than variation in environmental conditions. This is intuitive when configurations of suitable habitat are a dominant factor limiting dispersal and gene flow, but has not been thoroughly examined for habitat specialists with strong dispersal capability. Here, we evaluate the effects of geographic and environmental isolation on genetic divergence for a vagile invertebrate with high habitat specificity and a discrete dispersal life stage: Dod's Old World swallowtail butterfly, Papilio machaon dodi. In Canada, P. m. dodi are generally restricted to eroding habitat along major river valleys where their larval host plant occurs. A series of causal and linear mixed effects models indicate that divergence of genome-wide single nucleotide polymorphisms is best explained by a combination of environmental isolation (variation in summer temperatures) and geographic isolation (Euclidean distance). Interestingly, least-cost path and circuit distances through a resistance surface parameterized as the inverse of habitat suitability were not supported. This suggests that, although habitat associations of many butterflies are specific due to reproductive requirements, habitat suitability and landscape permeability are not equivalent concepts due to considerable adult vagility. We infer that divergent selection related to variation in summer temperatures has produced two genetic clusters within P. m. dodi, differing in voltinism and diapause propensity. Within the next century, temperatures are predicted to rise by amounts greater than the present-day difference between regions of the genetic clusters, potentially affecting the persistence of the northern cluster under continued climate change.

Genomics of Clinal Local Adaptation in Pinus sylvestris Under Continuous Environmental and Spatial Genetic Setting

Understanding the consequences of local adaptation at the genomic diversity is a central goal in evolutionary genetics of natural populations. In species with large continuous geographical distributions the phenotypic signal of local adaptation is frequently clear, but the genetic basis often remains elusive. We examined the patterns of genetic diversity in Pinus sylvestris, a keystone species in many Eurasian ecosystems with a huge distribution range and decades of forestry research showing that it is locally adapted to the vast range of environmental conditions. Making P. sylvestris an even more attractive subject of local adaptation study, population structure has been shown to be weak previously and in this study. However, little is known about the molecular genetic basis of adaptation, as the massive size of gymnosperm genomes has prevented large scale genomic surveys. We generated a both geographically and genomically extensive dataset using a targeted sequencing approach. By applying divergence-based and landscape genomics methods we identified several loci contributing to local adaptation, but only few with large allele frequency changes across latitude. We also discovered a very large (ca. 300 Mbp) putative inversion potentially under selection, which to our knowledge is the first such discovery in conifers. Our results call for more detailed analysis of structural variation in relation to genomic basis of local adaptation, emphasize the lack of large effect loci contributing to local adaptation in the coding regions and thus point out the need for more attention toward multi-locus analysis of polygenic adaptation.

Landscape does matter: Disentangling founder effects from natural and human-aided post-introduction dispersal during an ongoing biological invasion

Environmental features impacting the spread of invasive species after introduction can be assessed using population genetic structure as a quantitative estimation of effective dispersal at the landscape scale. However, in the case of an ongoing biological invasion, deciphering whether genetic structure represents landscape connectivity or founder effects is particularly challenging. We examined the modes of dispersal (natural and human-aided) and the factors (landscape or founders history) shaping genetic structure in range edge invasive populations of the Asian tiger mosquito, Aedes albopictus, in the region of Grenoble (Southeast France). Based on detailed occupancy-detection data and environmental variables (climatic, topographic and land-cover), we modelled A. albopictus potential suitable area and its expansion history since first introduction. The relative role of dispersal modes was estimated using biological dispersal capabilities and landscape genetics approaches using genome-wide SNP dataset. We demonstrate that both natural and human-aided dispersal have promoted the expansion of populations. Populations in diffuse urban areas, representing highly suitable habitat for A. albopictus, tend to disperse less, while roads facilitate long-distance dispersal. Yet, demographic bottlenecks during introduction played a major role in shaping the genetic variability of these range edge populations. The present study is one of the few investigating the role of founder effects and ongoing expansion processes in shaping spatial patterns of genetic variation in an invasive species at the landscape scale. The combination of several dispersal modes and large proportions of continuous suitable habitats for A. albopictus promoted range filling of almost its entire potential distribution in the region of Grenoble only few years after introduction.

Spatial predictors of genomic and phenotypic variation differ in a lowland Middle American bird (Icterus gularis)

Spatial patterns of intraspecific variation are shaped by geographical distance among populations, historical changes in gene flow and interactions with local environments. Although these factors are not mutually exclusive and operate on both genomic and phenotypic variation, it is unclear how they affect these two axes of variation. We address this question by exploring the predictors of genomic and phenotypic divergence in Icterus gularis, a broadly distributed Middle American bird that exhibits marked geographical variation in body size across its range. We combined a comprehensive single nucleotide polymorphism and phenotypic data set to test whether genome-wide genetic and phenotypic differentiation are best explained by (i) isolation by distance, (ii) isolation by history or (iii) isolation by environment. We find that the pronounced genetic and phenotypic variation in I. gularis are only partially correlated and differ regarding spatial predictors. Whereas genomic variation is largely explained by historical barriers to gene flow, phenotypic diversity can be best predicted by contemporary environmental heterogeneity. Our genomic analyses reveal strong phylogeographical structure coinciding with the Chivela Pass at the Isthmus of Tehuantepec that was formed during the Pleistocene, when populations were isolated in north-south refugia. In contrast, we found a strong association between body size and environmental variables, such as temperature and precipitation. The relationship between body size and local climate is consistent with a pattern produced by either natural selection or environmental plasticity. Overall, these results provide empirical evidence for why phenotypic and genomic data are often in conflict in taxonomic and phylogeographical studies.

Genomic Signatures of Local Adaptation in Clam Shrimp (Eulimnadia texana) from Natural Vernal Pools

Vernal pools are unique in their isolation and the strong selection acting on their resident species. Vernal pool clam shrimp (Eulimnadia texana) are a promising model due to ease of culturing, short generation time, small genomes, and obligate desiccated diapaused eggs. Clam shrimp are also androdioecious (sexes include males and hermaphrodites), and here we use population-scaled recombination rates to support the hypothesis that the heterogametic sex is recombination free in these shrimp. We collected short-read sequence data from pooled samples from different vernal pools to gain insights into local adaptation. We identify genomic regions in which some populations have allele frequencies that differ significantly from the metapopulation. BayPass (Gautier M. 2015. Genome-wide scan for adaptive divergence and association with population-specific covariates. Genetics 201(4):1555-1579.) detected 19 such genomic regions showing an excess of population subdivision. These regions on average are 550 bp in size and had 2.5 genes within 5 kb of them. Genes located near these regions are involved in Malpighian tubule function and osmoregulation, an essential function in vernal pools. It is likely that salinity profiles vary between pools and over time, and variants at these genes are adapted to local salinity conditions.

Genetic consequences of being a dwarf: do evolutionary changes in life-history traits influence gene flow patterns in populations of the world's smallest goldenrod?

BACKGROUND AND AIMS

Contrasting life-history traits can evolve through generations of dwarf plant ecotypes, yet such phenotypic changes often involve decreased plant size and reproductive allocation, which can configure seed dispersal patterns and, subsequently, population demography. Therefore, evolutionary transitions to dwarfism can represent good study systems to test the roles of life-history traits in population demography by comparing genetic structure between related but phenotypically divergent ecotypes.

METHODS

In this study, we examined an ecotypic taxon pair of the world's smallest goldenrod (stem height 2.6 cm) in alpine habitats and its closely related lowland taxon (30-40 cm) found on Yakushima Island, Japan. Genetic variation in chloroplast DNA sequences, nuclear microsatellites and genome-wide single-nucleotide polymorphisms were used to investigate 197 samples from 16 populations, to infer the population genetic demography and compare local genetic structure of the ecotypes.

KEY RESULTS

We found a pronounced level of genetic differentiation among alpine dwarf populations, which were much less geographically isolated than their lowland counterparts. In particular, several neighbouring dwarf populations (located ~500 m apart) harboured completely different sets of chloroplast haplotypes and nuclear genetic clusters. Demographic modelling revealed that the dwarf populations have not exchanged genes at significant levels after population divergence.

CONCLUSIONS

These lines of evidence suggest that substantial effects of genetic drift have operated on these dwarf populations. The low-growing stature and reduced fecundity (only 3.1 heads per plant) of the dwarf plants may have reduced gene flow and rare long-distance seed dispersal among habitat patches, although the effects of life-history traits require further evaluation using ecological approaches.

Regional differences in the abiotic environment contribute to genomic divergence within a wild tomato species

The wild currant tomato Solanum pimpinellifolium inhabits a wide range of abiotic habitats across its native range of Ecuador and Peru. Although it has served as a key genetic resource for the improvement of domestic cultivars, little is known about the genetic basis of traits underlying local adaptation in this species, nor what abiotic variables are most important for driving differentiation. Here we use redundancy analysis (RDA) and other multivariate statistical methods (structural equation modelling [SEM] and generalized dissimilarity modelling [GDM]) to quantify the relationship of genomic variation (6,830 single nucleotide polymorphisms [SNPs]) with climate and geography, among 140 wild accessions. RDA, SEM and GDM each identified environment as explaining more genomic variation than geography, suggesting that local adaptation to heterogeneous abiotic habitats may be an important source of genetic diversity in this species. Environmental factors describing temporal variation in precipitation and evaporative demand explained the most SNP variation among accessions, indicating that these forces may represent key selective agents. Lastly, by studying how SNP-environment associations vary throughout the genome (44,064 SNPs), we mapped the location and investigated the functions of loci putatively contributing to climatic adaptations. Together, our findings indicate an important role for selection imposed by the abiotic environment in driving genomic differentiation between populations.

Harnessing paleo-environmental modeling and genetic data to predict intraspecific genetic structure

Spatially explicit simulations of gene flow within complex landscapes could help forecast the responses of populations to global and anthropological changes. Simulating how past climate change shaped intraspecific genetic variation can provide a validation of models in anticipation of their use to predict future changes. We review simulation models that provide inferences on population genetic structure. Existing simulation models generally integrate complex demographic and genetic processes but are less focused on the landscape dynamics. In contrast to previous approaches integrating detailed demographic and genetic processes and only secondarily landscape dynamics, we present a model based on parsimonious biological mechanisms combining habitat suitability and cellular processes, applicable to complex landscapes. The simulation model takes as input (a) the species dispersal capacities as the main biological parameter, (b) the species habitat suitability, and (c) the landscape structure, modulating dispersal. Our model emphasizes the role of landscape features and their temporal dynamics in generating genetic differentiation among populations within species. We illustrate our model on caribou/reindeer populations sampled across the entire species distribution range in the Northern Hemisphere. We show that simulations over the past 21 kyr predict a population genetic structure that matches empirical data. This approach looking at the impact of historical landscape dynamics on intraspecific structure can be used to forecast population structure under climate change scenarios and evaluate how species range shifts might induce erosion of genetic variation within species.

Assessment of spatial genetic structure to identify populations at risk for infection of an emerging epizootic disease

Understanding the geographic extent and connectivity of wildlife populations can provide important insights into the management of disease outbreaks but defining patterns of population structure is difficult for widely distributed species. Landscape genetic analyses are powerful methods for identifying cryptic structure and movement patterns that may be associated with spatial epizootic patterns in such cases.We characterized patterns of population substructure and connectivity using microsatellite genotypes from 2,222 white-tailed deer (Odocoileus virginianus) in the Mid-Atlantic region of the United States, a region where chronic wasting disease was first detected in 2009. The goal of this study was to evaluate the juxtaposition between population structure, landscape features that influence gene flow, and current disease management units.Clustering analyses identified four to five subpopulations in this region, the edges of which corresponded to ecophysiographic provinces. Subpopulations were further partitioned into 11 clusters with subtle (F ST ≤ 0.041), but significant genetic differentiation. Genetic differentiation was lower and migration rates were higher among neighboring genetic clusters, indicating an underlying genetic cline. Genetic discontinuities were associated with topographic barriers, however.Resistance surface modeling indicated that gene flow was diffuse in homogenous landscapes, but the direction and extent of gene flow were influenced by forest cover, traffic volume, and elevational relief in subregions heterogeneous for these landscape features. Chronic wasting disease primarily occurred among genetic clusters within a single subpopulation and along corridors of high landscape connectivity.These results may suggest a possible correlation between population substructure, landscape connectivity, and the occurrence of diseases for widespread species. Considering these factors may be useful in delineating effective management units, although only the largest features produced appreciable differences in subpopulation structure. Disease mitigation strategies implemented at the scale of ecophysiographic provinces are likely to be more effective than those implemented at finer scales.

Biome stability predicts population structure of a southern African aridland bird species

Environments are heterogeneous in space and time, and the permeability of landscape and climatic barriers to gene flow may change over time. When barriers are present, they may start populations down the path toward speciation, but if they become permeable before the process of speciation is complete, populations may once more merge. In Southern Africa, aridland biomes play a central role in structuring the organization of biodiversity. These biomes were subject to substantial restructuring during Plio-Pleistocene climatic fluctuations, and the imprint of this changing environment should leave genetic signatures on the species living there. Here, we investigate the role of adjacent aridland biome boundaries in structuring the genetic diversity within a widespread generalist bird, the Cape Robin-chat (Cossypha caffra). We find evidence supporting a central role for aridland biomes in structuring populations across Southern Africa. Our findings support a scenario wherein populations were isolated in different biome refugia, due to separation by the exceptionally arid Nama Karoo biome. This biome barrier may have arisen through a combination of habitat instability and environmental unsuitability, and was highly unstable throughout the Plio-Pleistocene. However, we also recovered a pattern of extensive contemporary gene flow and admixture across the Nama Karoo, potentially driven by the establishment of homesteads over the past 200 years. Thus, the barrier has become permeable, and populations are currently merging. This represents an instance where initial formation of a barrier to gene flow enabled population differentiation, with subsequent gene flow and the merging of populations after the barrier became permeable.

Is Niagara Falls a barrier to gene flow in riverine fishes? A test using genome-wide SNP data from seven native species

Since the early Holocene, fish population genetics in the Laurentian Great Lakes have been shaped by the dual influences of habitat structure and post-glacial dispersal. Riverscape genetics theory predicts that longitudinal habitat corridors and unidirectional downstream water-flow drive the downstream accumulation of genetic diversity, whereas post-glacial dispersal theory predicts that fish genetic diversity should decrease with increasing distance from glacial refugia. This study examines populations of seven native fish species codistributed above and below the 58 m high Niagara Falls - a hypothesized barrier to gene flow in aquatic species. A better understanding of Niagara Falls' role as a barrier to gene flow and dispersal is needed to identify drivers of Great Lakes genetic diversity and guide strategies to limit exotic species invasions. We used genome-wide SNPs and coalescent models to test whether populations are: (a) genetically distinct, consistent with the Niagara Falls barrier hypothesis; (b) more genetically diverse upstream, consistent with post-glacial expansion theory, or downstream, consistent with the riverscape habitat theory; and (c) have migrated either upstream or downstream past Niagara Falls. We found that genetic diversity is consistently greater below Niagara Falls and the falls are an effective barrier to migration, but two species have probably dispersed upstream past the falls after glacial retreat yet before opening of the Welland Canal. Models restricting migration to after opening of the Welland Canal were generally rejected. These results help explain how river habitat features affect aquatic species' genetic diversity and highlight the need to better understand post-glacial dispersal pathways.

Sea ice loss increases genetic isolation in a high Arctic ungulate metapopulation

Sea ice loss may have dramatic consequences for population connectivity, extinction-colonization dynamics, and even the persistence of Arctic species subject to climate change. This is of particular concern in face of additional anthropogenic stressors, such as overexploitation. In this study, we assess the population-genetic implications of diminishing sea ice cover in the endemic, high Arctic Svalbard reindeer (Rangifer tarandus platyrhynchus) by analyzing the interactive effects of landscape barriers and reintroductions (following harvest-induced extirpations) on their metapopulation genetic structure. We genotyped 411 wild reindeer from 25 sampling sites throughout the entire subspecies' range at 19 microsatellite loci. Bayesian clustering analysis showed a genetic structure composed of eight populations, of which two were admixed. Overall population genetic differentiation was high (mean F_ST  = 0.21). Genetic diversity was low (allelic richness [AR] = 2.07-2.58; observed heterozygosity = 0.23-0.43) and declined toward the outer distribution range, where populations showed significant levels of inbreeding. Coalescent estimates of effective population sizes and migration rates revealed strong evolutionary source-sink dynamics with the central population as the main source. The population genetic structure was best explained by a landscape genetics model combining strong isolation by glaciers and open water, and high connectivity by dispersal across winter sea ice. However, the observed patterns of natural isolation were strongly modified by the signature of past harvest-induced extirpations, subsequent reintroductions, and recent lack of sea ice. These results suggest that past and current anthropogenic drivers of metapopulation dynamics may have interactive effects on large-scale ecological and evolutionary processes. Continued loss of sea ice as a dispersal corridor within and between island systems is expected to increase the genetic isolation of populations, and thus threaten the evolutionary potential and persistence of Arctic wildlife.