Representing genetic variation as continuous surfaces: an approach for identifying spatial dependency in landscape genetic studies

Landscape genetics, an emerging field integrating landscape ecology and population genetics, has great potential to influence our understanding of habitat connectivity and distribution of organisms. Whereas typical population genetics studies summarize gene flow as pairwise measures between sampling localities, landscape characteristics that influence population genetic connectivity are often continuously distributed in space. Thus, there are currently gaps in both the ability to analyze genotypic data in a continuous spatial context and our knowledge of expected of landscape genetic structure under varying conditions. We present a framework for generating continuous “genetic surfaces”, evaluate their statistical properties, and quantify statistical behavior of landscape genetic structure in a simple landscape. We simulated microsatellite genotypes under varying parameters (time since vicariance, migration, effective population size) and used ancestry (q) values from STRUCTURE to interpolate a genetic surface. Using a spatially adjusted Pearson's correlation coefficient to test the significance of landscape variable(s) on genetic structure we were able to detect landscape genetic structure on a contemporary time scale (≥5 generations post vicariance, migration probability ≤0.10) even when population differentiation was minimal (F_ST≥0.00015). We show that genetic variation can be significantly correlated with geographic distance even when genetic structure is due to landscape variable(s), demonstrating the importance of testing landscape influence on genetic structure. Finally, we apply genetic surfacing to analyze an empirical dataset of black bears from northern Idaho USA. We find black bear genetic variation is a function of distance (autocorrelation) and habitat patch (spatial dependency), consistent with previous results indicating genetic variation was influenced by landscape by resistance. These results suggest genetic surfaces can be used to test competing hypotheses of the influence of landscape characteristics on genetic structure without delineation of categorical groups.     

Effects of geography and life history traits on genetic differentiation in benthic marine fishes

Dispersal of planktonic larvae can create connections between geographically separated adult populations of benthic marine animals. How geographic context and life history traits affect these connections is largely unresolved. We use data from genetic studies (species level F_ST) of benthic teleost fishes combined with linear models to evaluate the importance of transitions between biogeographic regions, geographic distance, egg type (benthic or pelagic eggs), pelagic larval duration (PLD), and type of genetic marker as factors affecting differentiation within species. We find that transitions between biogeographic regions and egg type are significant and consistent contributors to population genetic structure, whereas PLD does not significantly explain population structure. Total study distance frequently contributes to significant interaction terms, particularly in association with genetic markers, whereby F_ST increases with study distance for studies employing mtDNA sequences, but allozyme and microsatellite studies show no increase in F_ST with study distance. These results highlight the importance of spatial context (biogeography and geographic distance) in affecting genetic differentiation and imply that there are inherent differences in dispersal ability associated with egg type. We also find that the geographic distance over which the maximum pairwise F_ST between populations occurs (relative to total study distance) is highly variable and can be observed at any scale. This result is consistent with stochastic processes inflating genetic differentiation and/or insufficient consideration of geographic and biological factors relevant to connectivity.     

Environmental factors affecting population level genetic divergence of the striped field mouse (<Emphasis Type="Italic">Apodemus agrarius</Emphasis>) in South Korea

The cognizing of connectivity among small mammal populations across heterogeneous landscapes is complicated due to complex influences of landscape and anthropogenic factors on gene flow. A landscape genetics approach offers inferences on how landscape features drive population structure. Through a landscape genetics approach, we investigated influences of geographical, environmental, and anthropogenic features on populations of Apodemus agrarius, the striped field mouse, the prime vector of hemorrhagic fever by a landscape genetic approach. We identified landscape features that might affect the population structure of striped field mice by analyzing microsatellite markers of 197 striped field mice from 21 populations throughout South Korea. We developed Maximum-likelihood population effects models based on landscape distances and resistance matrices and pairwise F_ST values for meta-populations of striped field mouse. We also conducted Mantel and partial Mantel tests to investigate geographic patterns of genetic similarities. In Mantel and partial Mantel tests, the F_ST was significantly correlated with all three models of movement; movement cost, Euclidian distance and least-cost distance, although the magnitudes of correlations varied. The 4 top-ranked models included three variables; temperature, precipitation and one human disturbance factor (population). We did not attain a significant effect for anthropogenic factors on genetic similarities among populations in the Korean striped field mouse, but we confirmed a significant association for genetic similarity with climatic features (temperature and precipitation).     

Where movement happens: scale‐dependent landscape effects on genetic differentiation in the European tree frog

Functional connectivity among fragmented populations depends on the landscape matrix between occupied habitat patches and its effect on the frequency of animal movement and gene flow. The quantification of landscape effects on gene flow should therefore be scale‐dependent. Here, we explored the impact of different spatial scales in a landscape genetic analysis of the European tree frog Hyla arborea in a fragmented landscape in Switzerland. We examined the effects of landscape elements and geographic distance on genetic differentiation at three distance classes reflecting varying frequencies of tree frog movement. We calculated pairwise F_ST‐values and assembled 16 landscape elements within 1 km wide corridors between all pairs of tree frog breeding sites. Per distance class, we computed a multiple regression model with stepwise backward elimination and permutation testing. At distances of<2 km, only a larger river acted as a barrier to gene flow. At distances>2 km, geographic distance had a negative effect on gene flow as had landscape elements such as forests and roads. In general, hedgerows and various structure‐rich landscape elements positively affected gene flow. As we found distinct scale‐dependent landscape effects on gene flow, future landscape genetic studies should analyse the effects of landscape variables at different spatial dimensions relevant for the movement and dispersal of the study organisms. Corresponding studies should also carefully consider relevant correlations among the landscape elements tested and should preferentially replicate their analysis at the landscape‐level in order to avoid idiosyncratic results owing to the particular scale and landscape studied.     

Sun skink landscape genomics: assessing the roles of micro‐evolutionary processes in shaping genetic and phenotypic diversity across a heterogeneous and fragmented landscape

Incorporating genomic data sets into landscape genetic analyses allows for powerful insights into population genetics, explicitly geographical correlates of selection, and morphological diversification of organisms across the geographical template. Here, we utilize an integrative approach to examine gene flow and detect selection, and we relate these processes to genetic and phenotypic population differentiation across South‐East Asia in the common sun skink, Eutropis multifasciata. We quantify the relative effects of geographic and ecological isolation in this system and find elevated genetic differentiation between populations from island archipelagos compared to those on the adjacent South‐East Asian continent, which is consistent with expectations concerning landscape fragmentation in island archipelagos. We also identify a pattern of isolation by distance, but find no substantial effect of ecological/environmental variables on genetic differentiation. To assess whether morphological conservatism in skinks may result from stabilizing selection on morphological traits, we perform F_ST–P_ST comparisons, but observe that results are highly dependent on the method of comparison. Taken together, this work provides novel insights into the manner by which micro‐evolutionary processes may impact macro‐evolutionary scale biodiversity patterns across diverse landscapes, and provide genomewide confirmation of classic predictions from biogeographical and landscape ecological theory.     

Landscape drivers of genomic diversity and divergence in woodland Eucalyptus

Spatial genetic patterns are influenced by numerous factors, and they can vary even among coexisting, closely related species due to differences in dispersal and selection. Eucalyptus (L'Héritier 1789; the “eucalypts”) are foundation tree species that provide essential habitat and modulate ecosystem services throughout Australia. Here we present a study of landscape genomic variation in two woodland eucalypt species, using whole‐genome sequencing of 388 individuals of Eucalyptus albens and Eucalyptus sideroxylon. We found exceptionally high genetic diversity (π ≈ 0.05) and low genome‐wide, interspecific differentiation (F_ST = 0.15) and intraspecific differentiation between localities (F_ST ≈ 0.01–0.02). We found no support for strong, discrete population structure, but found substantial support for isolation by geographic distance (IBD) in both species. Using generalized dissimilarity modelling, we identified additional isolation by environment (IBE). Eucalyptus albens showed moderate IBD, and environmental variables have a small but significant amount of additional predictive power (i.e. IBE). Eucalyptus sideroxylon showed much stronger IBD and moderate IBE. These results highlight the vast adaptive potential of these species and set the stage for testing evolutionary hypotheses of interspecific adaptive differentiation across environments.     

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 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.     

Microgeographic population structure of green swordail fish: genetic differentiation despite abundant migration

Swordtails (Xiphophorus; Poeciliidae) have figured prominently in research on fish mating behaviours, sexual selection, and carcinogenesis, but their population structures and dispersal patterns have been relatively neglected. Using nine microsatellite loci, we estimated genetic differentiation in Xiphophorus helleri within and between adjacent streams in Belize. The genetic data were complemented by a tagging study of movement within one stream. In the absence of physical dispersal barriers (waterfalls), population structure followed an isolation by distance (IBD) pattern. Genetic differentiation (F_ST up to 0.07) was significant between and within creeks, despite high dispersal in the latter as judged by the tagging data. Such heterogeneity apparently was a result of genetic drift in local demes, due to small population sizes and highly skewed paternity. The IBD pattern was interrupted by waterfalls, boosting F_ST above 0.30 between adjacent samples across these barriers. Overall, our results are helpful in understanding the interplay of evolutionary forces and population dynamics in a small fish living in a changeable habitat.     

Natural selection contributes to geographic patterns of thermal plasticity in Plantago lanceolata

A long‐standing debate in evolutionary biology concerns the relative importance of different evolutionary forces in explaining phenotypic diversification at large geographic scales. For example, natural selection is typically assumed to underlie divergence along environmental gradients. However, neutral evolutionary processes can produce similar patterns. We collected molecular genetic data from 14 European populations of Plantago lanceolata to test the contributions of natural selection versus neutral evolution to population divergence in temperature‐sensitive phenotypic plasticity of floral reflectance. In P. lanceolata, reflectance plasticity is positively correlated with latitude/altitude. We used population pairwise comparisons between neutral genetic differentiation (F_ST and Jost's D) and phenotypic differentiation (P_ST) to assess the contributions of geographic distance and environmental parameters of the reproductive season in driving population divergence. Data are consistent with selection having shaped large‐scale geographic patterns in thermal plasticity. The aggregate pattern of P_ST versus F_ST was consistent with divergent selection. F_ST explained thermal plasticity differences only when geographic distance was not included in the model. Differences in the extent of cool reproductive season temperatures, and not overall temperature variation, explained plasticity differences independent of distance. Results are consistent with the hypothesis that thermal plasticity is adaptive where growing seasons are shorter and cooler, that is, at high latitude/altitude.     

Isolation by distance,not incipient ecological speciation,explains genetic differentiation in an Andean songbird (Aves: Furnariidae: Cranioleuca antisiensis,Line‐cheeked Spinetail) despite near threefold body size change across an environmental gradient

During the process of ecological speciation, reproductive isolation results from divergent natural selection and leads to a positive correlation between genetic divergence and adaptive phenotypic divergence, that is, isolation by adaptation (IBA). In natural populations, phenotypic differentiation is often autocorrelated with geographic distance, making IBA difficult to distinguish from the neutral expectation of isolation by distance (IBD). We examined these two alternatives in a dramatic case of clinal phenotypic variation in an Andean songbird, the Line‐cheeked Spinetail (Cranioleuca antisiensis). At its geographic extremes, this species shows a near threefold difference in body mass (11.5 to 31.0 g) with marked plumage differences. We analysed phenotypic, environmental and genetic data (5,154 SNPs) from 172 individuals and 19 populations sampled along its linear distribution in the Andes. We found that body mass was tightly correlated with environmental temperature, consistent with local adaptation as per Bergmann's rule. Using a P_ST–F_ST analysis, we found additional support for natural selection driving body mass differentiation, but these results could also be explained by environment‐mediated phenotypic plasticity. When we assessed the relative support for patterns of IBA and IBD using variance partitioning, we found that IBD was the best explanation for genetic differentiation along the cline. Adaptive phenotypic or environmental divergence can reduce gene flow, a pattern interpreted as evidence of ecological speciation's role in diversification. Our results provide a counterexample to this interpretation. Despite conditions conducive to ecological speciation, our results suggest that dramatic size and environmental differentiation within C. antisiensis are not limiting gene flow.     

The influence of contemporary and historic landscape features on the genetic structure of the sand dune endemic,Cirsium pitcheri (Asteraceae)

Narrow endemics are at risk from climate change because of their restricted habitat preferences, lower colonization ability and dispersal distances. Landscape genetics combines new tools and analyses that allow us to test how both past and present landscape features have facilitated or hindered previous range expansion and local migration patterns, and thereby identifying potential limitations to future range shifts. We have compared current and historic habitat corridors in Cirsium pitcheri, an endemic of the linear dune ecosystem of the Great Lakes, to determine the relative contributions of contemporary migration and post-glacial range expansion on genetic structure. We used seven microsatellite loci to characterize the genetic structure for 24 populations of Cirsium pitcheri, spanning the center to periphery of the range. We tested genetic distance against different measures of geographic distance and landscape permeability, based on contemporary and historic landscape features. We found moderate genetic structure (Fst=0.14), and a north–south pattern to the distribution of genetic diversity and inbreeding, with northern populations having the highest diversity and lowest levels of inbreeding. High allelic diversity, small average pairwise distances and mixed genetic clusters identified in Structure suggest that populations in the center of the range represent the point of entry to the Lake Michigan and a refugium of diversity for this species. A strong association between genetic distances and lake-level changes suggests that historic lake fluctuations best explain the broad geographic patterns, and sandy habitat best explains local patterns of movement.     

A new analytical approach to landscape genetic modelling: least-cost transect analysis and linear mixed models

Landscape genetics aims to assess the effect of the landscape on intraspecific genetic structure. To quantify interdeme landscape structure, landscape genetics primarily uses landscape resistance surfaces (RSs) and least-cost paths or straight-line transects. However, both approaches have drawbacks. Parameterization of RSs is a subjective process, and least-cost paths represent a single migration route. A transect-based approach might oversimplify migration patterns by assuming rectilinear migration. To overcome these limitations, we combined these two methods in a new landscape genetic approach: least-cost transect analysis (LCTA). Habitat-matrix RSs were used to create least-cost paths, which were subsequently buffered to form transects in which the abundance of several landscape elements was quantified. To maintain objectivity, this analysis was repeated so that each landscape element was in turn regarded as migration habitat. The relationship between explanatory variables and genetic distances was then assessed following a mixed modelling approach to account for the nonindependence of values in distance matrices. Subsequently, the best fitting model was selected using the statistic. We applied LCTA and the mixed modelling approach to an empirical genetic dataset on the endangered damselfly, Coenagrion mercuriale. We compared the results to those obtained from traditional least-cost, effective and resistance distance analysis. We showed that LCTA is an objective approach that identifies both the most probable migration habitat and landscape elements that either inhibit or facilitate gene flow. Although we believe the statistical approach to be an improvement for the analysis of distance matrices in landscape genetics, more stringent testing is needed.     

Landscape genetics of alpine Sierra Nevada salamanders reveal extreme population subdivision in space and time

Quantifying the influence of the landscape on the genetic structure of natural populations remains an important empirical challenge, particularly for poorly studied, ecologically cryptic species. We conducted an extensive microsatellite analysis to examine the population genetics of the southern long‐toed salamander (Ambystoma macrodactylum sigillatum) in a naturally complex landscape. Using spatially explicit modelling, we investigated the influence of the Sierra Nevada topography on potential dispersal corridors between sampled populations. Our results indicate very high‐genetic divergence among populations, high within‐deme relatedness, and little evidence of recent migration or population admixture. We also discovered unexpectedly high between‐year genetic differentiation (F_ST) for breeding sites, suggesting that breeding groups vary over localized space and time. While environmental factors associated with high‐elevation montane habitats apparently play an important role in shaping population differentiation, additional, species‐specific biological processes must also be operating to account for observed deviations from temporal, among‐year panmixia. Our study emphasizes the population‐level insights that can be gained from high‐density sampling in space and time, and the highly substructured population biology that may characterize amphibians in extreme montane habitats.     

An exploratory analysis of geographic genetic variation in southern African nyala (Tragelaphus angasii)

We report patterns of genetic variation based on microsatellite, allozyme and mitochondrial control region markers in nyala from geographic locations sampled in South Africa, Mozambique, Malawi and Zimbabwe. Highly significant differences were observed among allele frequencies at three microsatellite loci between populations from KwaZulu-Natal, Limpopo and Malawi, with the Malawi and KwaZulu-Natal groupings showing the highest differentiation (R_ST=0.377). Allozyme frequencies showed minor, non-statistically significant regional differences among the South African populations, with maximum F_ST values of 0.048–0.067. Mitochondrial DNA analyses indicated a unique haplotype in each location sampled. Since none of these indices of population differentiation showed significant correlation to absolute geographic distance, we conclude that geographic variation in this species is probably a function of a distribution pattern stemming from habitat specificity. It is suggested that translocations among geographically distant regional populations be discouraged at present, pending a more elaborate investigation. Transfer of native individuals among local populations may, however, be required for minimizing the likelihood of inbreeding depression developing in small captive populations.     

Dispersal,Mating Events and Fine-Scale Genetic Structure in the Lesser Flat-Headed Bats

Population genetic structure has important consequences in evolutionary processes and conservation genetics in animals. Fine-scale population genetic structure depends on the pattern of landscape, the permanent movement of individuals, and the dispersal of their genes during temporary mating events. The lesser flat-headed bat (Tylonycteris pachypus) is a nonmigratory Asian bat species that roosts in small groups within the internodes of bamboo stems and the habitats are fragmented. Our previous parentage analyses revealed considerable extra-group mating in this species. To assess the spatial limits and sex-biased nature of gene flow in the same population, we used 20 microsatellite loci and mtDNA sequencing of the ND2 gene to quantify genetic structure among 54 groups of adult flat-headed bats, at nine localities in South China. AMOVA and F _ST estimates revealed significant genetic differentiation among localities. Alternatively, the pairwise F _ST values among roosting groups appeared to be related to the incidence of associated extra-group breeding, suggesting the impact of mating events on fine-scale genetic structure. Global spatial autocorrelation analyses showed positive genetic correlation for up to 3 km, indicating the role of fragmented habitat and the specialized social organization as a barrier in the movement of individuals among bamboo forests. The male-biased dispersal pattern resulted in weaker spatial genetic structure between localities among males than among females, and fine-scale analyses supported that relatedness levels within internodes were higher among females than among males. Finally, only females were more related to their same sex roost mates than to individuals from neighbouring roosts, suggestive of natal philopatry in females.     

THE EFFECT OF COLLECTIVE DISPERSAL ON THE GENETIC STRUCTURE OF A SUBDIVIDED POPULATION

Correlated dispersal paths between two or more individuals are widespread across many taxa. The population genetic implications of this collective dispersal have received relatively little attention. Here we develop two‐sample coalescent theory that incorporates collective dispersal in a finite island model to predict expected coalescence times, genetic diversities, and F‐statistics. We show that collective dispersal reduces mixing in the system, which decreases expected coalescence times and increases F_ST. The effects are strongest in systems with high migration rates. Collective dispersal breaks the invariance of within‐deme coalescence times to migration rate, whatever the deme size. It can also cause F_ST to increase with migration rate because the ratio of within‐ to between‐deme coalescence times can decrease as migration rate approaches unity. This effect is most biologically relevant when deme size is small. We find qualitatively similar results for diploid and gametic dispersal. We also demonstrate with simulations and analytical theory the strong similarity between the effects of collective dispersal and anisotropic dispersal. These findings have implications for our understanding of the balance between drift–migration–mutation in models of neutral evolution. This has applied consequences for the interpretation of genetic structure (e.g., chaotic genetic patchiness) and estimation of migration rates from genetic data.     

Spatial Genetic Structure in Natural Populations of Phragmites australis in a Mosaic of Saline Habitats in the Yellow River Delta, China

Determination of spatial genetic structure (SGS) in natural populations is important for both theoretical aspects of evolutionary genetics and their application in species conservation and ecological restoration. In this study, we examined genetic diversity within and among the natural populations of a cosmopolitan grass Phragmites australis (common reed) in the Yellow River Delta (YRD), China, where a mosaic of habitat patches varying in soil salinity was detected. We demonstrated that, despite their close geographic proximity, the common reed populations in the YRD significantly diverged at six microsatellite loci, exhibiting a strong association of genetic variation with habitat heterogeneity. Genetic distances among populations were best explained as a function of environmental difference, rather than geographical distance. Although the level of genetic divergence among populations was relatively low (F’_ST = 0.073), weak but significant genetic differentiation, as well as the concordance between ecological and genetic landscapes, suggests spatial structuring of genotypes in relation to patchy habitats. These findings not only provided insights into the population dynamics of common reed in changing environments, but also demonstrated the feasibility of using habitat patches in a mosaic landscape as test systems to identify appropriate genetic sources for ecological restoration.     

Fine scale patterns of migration and gene flow in the endangered mound spring snail, <Emphasis Type="Italic">Fonscochlea accepta</Emphasis> (Mollusca:Hydrobiidae) in arid Australia

Naturally patchy ecosystems are models for other systems currently undergoing anthropogenic habitat fragmentation. Understanding patterns of gene flow in these model systems can help us manage species and ecosystems threatened by human impacts. The mound springs of central Australia represent such a natural model ecosystem, supporting a unique aquatic fauna distributed within an inhospitable arid landscape. Moreover, these springs are being impacted by over extraction of groundwater, providing a unique opportunity to look at dispersal in a patchy habitat that is changing. The present study represents the first fine scale analysis of gene flow under different scenarios of habitat connectivity for the endangered mound spring snail, Fonscochlea accepta. Within a single spring group pairwise estimates of F _ST between springs were very low (ave 0.015) with no association found between genetic distance and a series of geographical distance matrices based on the degree of habitat connectivity among the springs: results implying unstructured dispersal and limited population isolation. However, results from Bayesian assignment tests showed that on average approximately 97% of snails were assigned to their spring of origin. In a preliminary analysis at broader geographic scales (among spring groups) the results from F _ST estimates, Mantel correlation analyses and assignment tests all suggest much stronger and geographically correlated population structuring. While varying results from F-statistics and Bayesian analyses stem from the different information they utilise, together they provide data on contemporary and historical estimates of gene flow and the influence of landscape dynamics on the spatial genetic patterning of the springs.     

On the Apportionment of Population Structure

Measures of population differentiation, such as F_ST, are traditionally derived from the partition of diversity within and between populations. However, the emergence of population clusters from multilocus analysis is a function of genetic structure (departures from panmixia) rather than of diversity. If the populations are close to panmixia, slight differences between the mean pairwise distance within and between populations (low F_ST) can manifest as strong separation between the populations, thus population clusters are often evident even when the vast majority of diversity is partitioned within populations rather than between them. For any given F_ST value, clusters can be tighter (more panmictic) or looser (more stratified), and in this respect higher F_ST does not always imply stronger differentiation. In this study we propose a measure for the partition of structure, denoted E_ST, which is more consistent with results from clustering schemes. Crucially, our measure is based on a statistic of the data that is a good measure of internal structure, mimicking the information extracted by unsupervised clustering or dimensionality reduction schemes. To assess the utility of our metric, we ranked various human (HGDP) population pairs based on F_ST and E_ST and found substantial differences in ranking order. E_ST ranking seems more consistent with population clustering and classification and possibly with geographic distance between populations. Thus, E_ST may at times outperform F_ST in identifying evolutionary significant differentiation.     

Environmental and topographic variables shape genetic structure and effective population sizes in the endangered Yosemite toad

Aim Describing the landscape variables that accurately reflect how environmental and topographic variations affect population connectivity and demography is a major goal of landscape genetics and conservation biology. However, few landscape genetics studies have quantified the relationships between landscape variables and effective population size (N_e), although N_e is a key conservation and population genetics parameter. In this study, I estimated genetic structure and effective population sizes in the Yosemite toad (Bufo canorus) and tested for associations with environmental and geographic variables. Location Yosemite National Park, California, USA. Methods I estimated F_ST, D_ps and N_e using 10 microsatellite loci amplified from 781 individuals from 24 populations. I used three landscape variables (environmental variation, topography and slope) to generate geographic distance models and a series of regression analyses to identify the variables that contributed to genetic structure in this species. I also tested for correlations between N_e and a suite of variables, including geographic and genetic isolation, habitat suitability, elevation, temperature and precipitation. Results I found substantial variation in genetic distances between populations (F_ST = 0.004–0.396, D_ps = 0.045–0.839) and in effective population sizes (N_e = 9–52). Environmental variation and slope played important roles in explaining variation in genetic distances, and precipitation variables were significantly correlated with N_e. Main conclusions These results show that environmental and topographic variables are both important for understanding population connectivity in B. canorus and provide some of the first evidence, in any species, for a link between environmental variables and effective population size.