Landscape genetics in the subterranean rodent <Emphasis Type="Italic">Ctenomys</Emphasis> “<Emphasis Type="Italic">chasiquensis</Emphasis>” associated with highly disturbed habitats from the southeastern Pampas region,Argentina

Studies of genetic differentiation in fragmented environments help us to identify those landscape features that most affect gene flow and dispersal patterns. Particularly, the assessment of the relative significance of intrinsic biological and environmental factors affecting the genetic structure of populations becomes crucial. In this work, we assess the current dispersal patterns and population structure of Ctenomys “chasiquensis”, a vulnerable and endemic subterranean rodent distributed on a small area in Central Argentina, using 9 polymorphic microsatellite loci. We use landscape genetics approaches to assess the relationship between genetic connectivity among populations and environmental attributes. Our analyses show that populations of C. “chasiquensis” are moderately to highly structured at a regional level. This pattern is most likely the outcome of substantial gene flow on the more homogeneous sand dune habitat of the Northwest of its distributional range, in conjunction with an important degree of isolation of eastern and southwestern populations, where the optimal habitat is surrounded by a highly fragmented landscape. Landscape genetics analysis suggests that habitat quality and longitude were the environmental factors most strongly associated with genetic differentiation/uniqueness of populations. In conclusion, our results indicate an important genetic structure in this species, even at a small spatial scale, suggesting that contemporary habitat fragmentation increases population differentiation.     

Low genetic diversity and limited gene flow in a dominant mangrove tree species (Rhizophora stylosa) at its northern biogeographical limit across the chain of three Sakishima islands of the Japanese archipelago as revealed by chloroplast and nuclear SSR analysis

We examined the genetic diversity, population structure and gene flow in a dominant mangrove tree (Rhizophora stylosa) at its northern biogeographical limit in Sakishima islands of the Japanese archipelago. Simple sequence repeat (SSR) markers from chloroplast (cpSSR) and nuclear DNA were used to analyze 16 populations recovered from various river basins across the chain of three Sakishima islands—Iriomote, Ishigaki and Miyako. The average number of alleles (1.7–2.7) and observed heterozygosities (0.031–0.216) at nuclear SSR and haploid diversity (0.000–0.489) at cpSSR across the populations suggested low genetic diversity in R. stylosa in Sakishima islands. cpSSR analysis identified two haplotypes, and Bayesian clustering analysis (nuclear SSR) revealed two genetic clusters. Analysis of molecular variance (nuclear SSR) showed significant population differentiations. Pairwise tests consistently revealed significant differentiation between most of the population pairs; however, the degrees of differentiations are generally correspondent to the relative geographical distances as suggested from pairwise F _ST and cpSSR genetic distances. Moreover, Mantel tests showed some signals of correlations between genetic distances (nuclear and chloroplast) and geographical distances. These results suggest that combined contribution of gene flow via pollen and propagule dispersal in R. stylosa mostly occurred between neighboring river basins. The appearances of two cpSSR haplotypes (maternal lineages) as well as two nuclear genetic clusters (putative ancestral lineages) at various river basins support the hypothesis that present-day R. stylosa populations across the Sakishima islands were established from few identical founders; however, significant differentiations among various river basins most likely resulted from the limited gene flow and high inbreeding.     

Landscape Genetic Structure of a Streamside Tree Species Euptelea pleiospermum (Eupteleaceae): Contrasting Roles of River Valley and Mountain Ridge

We used landscape genetics and statistical models to test how landscape features influence connectivity or create barriers to dispersal for a mountain riparian tree species, Euptelea pleiospermum. Young leaves from 1078 individuals belonging to 36 populations at elevations of 900–2000 m along upper reaches of four rivers were genotyped using eight nuclear microsatellite markers. We found no evidence for the unidirectional dispersal hypothesis in E. pleiospermum within each river. The linear dispersal pattern along each river valley is mostly consistent with the “classical metapopulaton” model. Mountain ridges separating rivers were genetic barriers for this wind-pollinated tree species with anemochorous seeds, whereas river valleys provided important corridors for dispersal. Gene flow among populations along elevational gradients within each river prevails over gene flow among populations at similar elevations but from different rivers. This pattern of gene flow is likely to promote elevational range shifts of plant populations and to hinder local adaptation along elevational gradients. This study provides a paradigm to determine which of the two strategies (migration or adaptation) will be adopted by mountain riparian plants under climate warming.     

GENE TREES AND ORGANISMAL HISTORIES: A PHYLOGENETIC APPROACH TO POPULATION BIOLOGY

A “gene tree” is the phylogeny of alleles or haplotypes for any specified stretch of DNA. Gene trees are components of population trees or species trees; their analysis entails a shift in perspective from many of the familiar models and concepts of population genetics, which typically deal with frequencies of phylogenetically unordered alleles. Molecular surveys of haplotype diversity in mitochondrial DNA (mtDNA) have provided the first extensive empirical data suitable for estimation of gene trees on a microevolutionary (intraspecific) scale. The relationship between phylogeny and geographic distribution constitutes the phylogeographic pattern for any species. Observed phylogeographic trees can be interpreted in terms of historical demography by comparison to predictions derived from models of gene lineage sorting, such as inbreeding theory and branching-process theory. Results of such analyses for more than 20 vertebrate species strongly suggest that the demographies of populations have been remarkably dynamic and unsettled over space and recent evolutionary time. This conclusion is consistent with ecological observations documenting dramatic population-size fluctuations and range shifts in many contemporary species. By adding an historical perspective to population biology, the gene-lineage approach can help forge links between the disciplines of phylogenetic systematics (and macroevolutionary study) and population genetics (microevolution). Preliminary extensions of the “gene tree” methodology to haplotypes of nuclear genes (such as Adh in Drosophila melanogaster) demonstrate that the phylogenetic perspective can also help to illuminate molecular-genetic processes (such as recombination or gene conversion), as well as contribute to knowledge of the origin, age, and molecular basis of particular adaptations.     

Riverscape genetics in brook lamprey: genetic diversity is less influenced by river fragmentation than by gene flow with the anadromous ecotype

Understanding the effect of human-induced landscape fragmentation on gene flow and evolutionary potential of wild populations has become a major concern. Here, we investigated the effect of riverscape fragmentation on patterns of genetic diversity in the freshwater resident European brook lamprey (Lampetra planeri) that has a low ability to pass obstacles to migration. We tested the hypotheses of (i) asymmetric gene flow following water current and (ii) an effect of gene flow with the closely related anadromous river lamprey (L. fluviatilis) ecotype on L. planeri genetic diversity. We genotyped 2472 individuals, including 225 L. fluviatilis, sampled from 81 sites upstream and downstream barriers to migration, in 29 western European rivers. Linear modelling revealed a strong positive relationship between genetic diversity and the distance from the river source, consistent with expected patterns of decreased gene flow into upstream populations. However, the presence of anthropogenic barriers had a moderate effect on spatial genetic structure. Accordingly, we found evidence for downstream-directed gene flow, supporting the hypothesis that barriers do not limit dispersal mediated by water flow. Downstream L. planeri populations in sympatry with L. fluviatilis displayed consistently higher genetic diversity. We conclude that genetic drift and slight downstream gene flow drive the genetic make-up of upstream L. planeri populations whereas gene flow between ecotypes maintains higher levels of genetic diversity in L. planeri populations sympatric with L. fluviatilis. We discuss the implications of these results for the design of conservation strategies of lamprey, and other freshwater organisms with several ecotypes, in fragmented dendritic river networks.Subject terms: Conservation biology, Ecological genetics, Evolutionary genetics, Genetic variation     

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 urbanization on Song Sparrow (Melospiza melodia) population connectivity

Urbanization may affect genetic differentiation among animal populations because it converts native vegetation to novel land cover types that can affect population connectivity. The effect of land cover change on genetic differentiation may vary among taxa; mobile birds may be least affected. Regardless, genetic differentiation between populations should be best predicted by measures of distance that incorporate the effect of land cover on movement. We studied the relationship between land cover and genetic differentiation in Song Sparrows (Melospiza melodia) at eighteen sites in the Seattle metropolitan region. We generated a series of hypothetical “resistance surfaces” based on land cover and development age, calculated “resistance distances” between pairs of sampling sites, and related them to pairwise genetic differentiation. Genetic differentiation was best described by a multiple regression model where resistance to gene flow (1) linearly increased with age of development and (2) was greater in high- and medium-density urbanization than in native forest land cover types (R ² = 0.15; p = 0.003). The single variable with the highest correlation with genetic differentiation was derived from a linear relationship between development age and resistance (R ² = 0.08; p = 0.007). Our results thus suggested that urban development reduced population connectivity for Song Sparrows. However, the relation of development age to genetic differentiation suggested that equilibrium was not yet reached. Hence, the effects of lost connectivity will increase. Our understanding of the landscape genetics of this recently anthropogenically modified landscape benefited from considering population history.     

Using a genetic network to parameterize a landscape resistance surface for fishers, Martes pennanti

Knowledge of dispersal-related gene flow is important for addressing many basic and applied questions in ecology and evolution. We used landscape genetics to understand the recovery of a recently expanded population of fishers (Martes pennanti) in Ontario, Canada. An important focus of landscape genetics is modelling the effects of landscape features on gene flow. Most often resistance surfaces in landscape genetic studies are built a priori based upon nongenetic field data or expert opinion. The resistance surface that best fits genetic data is then selected and interpreted. Given inherent biases in using expert opinion or movement data to model gene flow, we sought an alternative approach. We used estimates of conditional genetic distance derived from a network of genetic connectivity to parameterize landscape resistance and build a final resistance surface based upon information-theoretic model selection and multi-model averaging. We sampled 657 fishers from 31 landscapes, genotyped them at 16 microsatellite loci, and modelled the effects of snow depth, road density, river density, and coniferous forest on gene flow. Our final model suggested that road density, river density, and snow depth impeded gene flow during the fisher population expansion demonstrating that both human impacts and seasonal habitat variation affect gene flow for fishers. Our approach to building landscape genetic resistance surfaces mitigates many of the problems and caveats associated with using either nongenetic field data or expert opinion to derive resistance surfaces.     

Rangewide landscape genetics of an endemic Pacific northwestern salamander

A species' genetic structure often varies in response to ecological and landscape processes that differ throughout the species' geographic range, yet landscape genetics studies are rarely spatially replicated. The Cope's giant salamander (Dicamptodon copei) is a neotenic, dispersal‐limited amphibian with a restricted geographic range in the Pacific northwestern USA. We investigated which landscape factors affect D. copei gene flow in three regions spanning the species' range, which vary in climate, landcover and degree of anthropogenic disturbance. Least cost paths and Circuitscape resistance analyses revealed that gene flow patterns vary across the species' range, with unique combinations of landscape variables affecting gene flow in different regions. Populations in the northern coastal portions of the range had relatively high gene flow, largely facilitated by stream and river networks. Near the southeastern edge of the species' range, gene flow was more restricted overall, with relatively less facilitation by streams and more limitation by heat load index and fragmented forest cover. These results suggested that the landscape is more difficult for individuals to disperse through at the southeastern edge of the species' range, with terrestrial habitat desiccation factors becoming more limiting to gene flow. We suggest that caution be used when attempting to extrapolate landscape genetic models and conservation measures from one portion of a species' range to another.     

Patterns of gene flow and source‐sink dynamics in high altitude populations of the common toad Bufo bufo (Anura: Bufonidae)

Understanding patterns of genetic structure is fundamental for developing successful management programmes for deme‐structured organisms, such as amphibians. We used five microsatellite loci and DNA sequences of the mitochondrial control region to assess the relative influences of landscape (geographic distance, altitude and rivers as corridors for dispersal) and historical factors on patterns of gene flow in populations of the toad Bufo bufo in Central Spain. We sampled 175 individuals from eight populations distributed along two major river drainages and used maximum‐likelihood and Bayesian approaches to infer patterns of gene flow and population structure. The mitochondrial DNA data show closely‐related haplotypes distributed across the Iberian Peninsula with no geographic structuring, suggesting recent differentiation of haplotypes and extensive gene flow between populations. On the other hand, microsatellites provide finer resolution, showing that high altitude populations (> 2000 m) exchange lower numbers of migrants with other populations. The results of Bayesian estimates for recent migration rates in high altitude populations suggest source‐sink dynamics between ponds that are consistent with independent data from monitoring over the past 20 years. © 2008 The Linnean Society of London, Biological Journal of the Linnean Society, 2008, 95 , 824–839.     

Patterns of weed invasion: evidence from the spatial genetic structure of Raphanus raphanistrum

Knowledge of the pathways of colonization is critical for risk assessment and management of weeds. In this study we adopted a landscape genetics approach to assess the impact of human disturbances and large-scale environmental features on the colonization of a global agricultural weed, Raphanus raphanistrum. We used nuclear microsatellite and chloroplast DNA sequence data to quantify the pattern of genetic diversity in 336 plants collected from 13 sites throughout the Cape Floristic Region, South Africa, one of the world’s recognized global biodiversity hotspots. The lack of strong spatial genetic structure suggests that R. raphanistrum colonized throughout the Cape Floristic Region via both local diffusive spread and long-distance jump dispersal. Furthermore, 47 % of analyzed plants contained Raphanus sativus (cultivated radish) chloroplast genomes, indicating historical and/or contemporary gene flow between wild and cultivated radish populations. The prevalence of high genetic diversity and long-distance gene flow are discussed in the context of ecological risk assessment.     

Watershed‐level brook trout genetic structuring: Evaluation and application of riverscape genetics models

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Relationships between migration rates and landscape resistance assessed using individual-based simulations

Linking landscape effects on gene flow to processes such as dispersal and mating is essential to provide a conceptual foundation for landscape genetics. It is particularly important to determine how classical population genetic models relate to recent individual-based landscape genetic models when assessing individual movement and its influence on population genetic structure. We used classical Wright-Fisher models and spatially explicit, individual-based, landscape genetic models to simulate gene flow via dispersal and mating in a series of landscapes representing two patches of habitat separated by a barrier. We developed a mathematical formula that predicts the relationship between barrier strength (i.e., permeability) and the migration rate (m) across the barrier, thereby linking spatially explicit landscape genetics to classical population genetics theory. We then assessed the reliability of the function by obtaining population genetics parameters (m, F(ST) ) using simulations for both spatially explicit and Wright-Fisher simulation models for a range of gene flow rates. Next, we show that relaxing some of the assumptions of the Wright-Fisher model can substantially change population substructure (i.e., F(ST) ). For example, isolation by distance among individuals on each side of a barrier maintains an F(ST) of ～0.20 regardless of migration rate across the barrier, whereas panmixia on each side of the barrier results in an F(ST) that changes with m as predicted by classical population genetics theory. We suggest that individual-based, spatially explicit modelling provides a general framework to investigate how interactions between movement and landscape resistance drive population genetic patterns and connectivity across complex landscapes.     

Age and sex-dependent effects of landscape cover and trapping on the spatial genetic structure of the stone marten (<Emphasis Type="Italic">Martes foina</Emphasis>)

Maintenance of genetic variation is of critical importance for wild populations since low levels limit the species’ ability to respond to different threats (diseases, predators, environmental changes) in both the long and the short term. Human activities could impact the genetic variation of wild species in multiple ways, including via fragmentation and harvesting. We used an individual-based landscape genetics approach to describe the impact of landscape elements and trapping pressure on the spatial genetic structure of a large sample (n = 370) of the stone marten (Martes foina) in central-eastern France (Bresse). An analysis of isolation-by-resistance using a causal modeling approach showed an influence of landscape cover and/or trapping pressure on gene flow according to age and sex class. Overall, the connectivity in the study area is provided mainly by vegetation cover, while roads and open areas partially impede it. Unexpectedly for this “urban adapter” species, buildings could reduce gene flow. We also emphasized the sex-dependent effect of trapping on gene flow. Genetic differentiation in males was influenced by trapping pressure and landscape structure while only the latter influenced genetic differentiation in females. A stronger isolation by distance in males than in females suggested that at the scale of the study area, males are more exposed to trapping pressure, which reduces effective dispersal. Overall, the combination of both landscape and trapping costs might create an ‘ecological trap’ that could disrupt gene flow, leading to a north–south division in the study area.     

Contemporary and historic factors influence differently genetic differentiation and diversity in a tropical palm

Population genetics theory predicts loss in genetic variability because of drift and inbreeding in isolated plant populations; however, it has been argued that long-distance pollination and seed dispersal may be able to maintain gene flow, even in highly fragmented landscapes. We tested how historical effective population size, historical migration and contemporary landscape structure, such as forest cover, patch isolation and matrix resistance, affect genetic variability and differentiation of seedlings in a tropical palm (Euterpe edulis) in a human-modified rainforest. We sampled 16 sites within five landscapes in the Brazilian Atlantic forest and assessed genetic variability and differentiation using eight microsatellite loci. Using a model selection approach, none of the covariates explained the variation observed in inbreeding coefficients among populations. The variation in genetic diversity among sites was best explained by historical effective population size. Allelic richness was best explained by historical effective population size and matrix resistance, whereas genetic differentiation was explained by matrix resistance. Coalescence analysis revealed high historical migration between sites within landscapes and constant historical population sizes, showing that the genetic differentiation is most likely due to recent changes caused by habitat loss and fragmentation. Overall, recent landscape changes have a greater influence on among-population genetic variation than historical gene flow process. As immediate restoration actions in landscapes with low forest amount, the development of more permeable matrices to allow the movement of pollinators and seed dispersers may be an effective strategy to maintain microevolutionary processes.     

Expert-based versus habitat-suitability models to develop resistance surfaces in landscape genetics

Landscape genetics aims to investigate functional connectivity among wild populations by evaluating the impact of landscape features on gene flow. Genetic distances among populations or individuals are generally better explained by least-cost path (LCP) distances derived from resistance surfaces than by simple Euclidean distances. Resistance surfaces reflect the cost for an organism to move through particular landscape elements. However, determining the effects of landscape types on movements is challenging. Because of a general lack of empirical data on movements, resistance surfaces mostly rely on expert knowledge. Habitat-suitability models potentially provide a more objective method to estimate resistance surfaces than expert opinions, but they have rarely been applied in landscape genetics so far. We compared LCP distances based on expert knowledge with LCP distances derived from habitat-suitability models to evaluate their performance in landscape genetics. We related all LCP distances to genetic distances in linear mixed effect models on an empirical data set of wolves (Canis lupus) from Italy. All LCP distances showed highly significant (P ≤ 0.0001) standardized β coefficients and R ² values, but LCPs from habitat-suitability models generally showed higher values than those resulting from expert knowledge. Moreover, all LCP distances better explained genetic distances than Euclidean distances, irrespective of the approaches used. Considering our results, we encourage researchers in landscape genetics to use resistance surfaces based on habitat suitability which performed better than expert-based LCPs in explaining patterns of gene flow and functional connectivity.     

Landscape genetic connectivity in European wildcat (Felis silvestris silvestris): a matter of food,shelters and demographic status of populations

Understanding landscape impacts on gene flow is necessary to plan comprehensive management and conservation strategies of both the species of interest and its habitat. Nevertheless, only a few studies have focused on the landscape genetic connectivity of the European wildcat, an umbrella species whose conservation allows the preservation of numerous other species and habitat types. We applied population and landscape genetics approaches, using genotypes at 30 microsatellites from 232 genetically-identified wildcats to determine if, and how, landscape impacted gene flow throughout France. Analyses were performed independently within two population patches: the historical north-eastern patch and the central patch considered as the colonization front. Our results showed that gene flow occurred at large spatial scales but also revealed significant spatial genetic structures within population patches. In both population patches, arable areas, pastures and permanent grasslands and lowly fragmented forested areas were permeable to gene flow, suggesting that shelters and dietary resources are among the most important parameters for French wildcat landscape connectivity, while distance to forest had no detectable effect. Anthropized areas appeared highly resistant in the north-eastern patch but highly permeable in the central patch, suggesting that different behaviours can be observed according to the demographic context in which populations are found. In line with this hypothesis, spatial distribution of genetic variability seemed uneven in the north-eastern patch and more clinal in the central patch. Overall, our results highlighted that European wildcat might be a habitat generalist species and also the importance of performing spatial replication in landscape genetics studies.

     

Landscape genetics in a changing world: disentangling historical and contemporary influences and inferring change

Landscape genetics seeks to determine the effect of landscape features on gene flow and genetic structure. Often, such analyses are intended to inform conservation and management. However, depending on the many factors that influence the time to reach equilibrium, genetic structure may more strongly represent past rather than contemporary landscapes. This well‐known lag between current demographic processes and population genetic structure often makes it challenging to interpret how contemporary landscapes and anthropogenic activity shape gene flow. Here, we review the theoretical framework for factors that influence time lags, summarize approaches to address this temporal disconnect in landscape genetic studies, and evaluate ways to make inferences about landscape change and its effects on species using genetic data alone or in combination with other data. Those approaches include comparing correlation of genetic structure with historical versus contemporary landscapes, using molecular markers with different rates of evolution, contrasting metrics of genetic structure and gene flow that reflect population genetic processes operating at different temporal scales, comparing historical and contemporary samples, combining genetic data with contemporary estimates of species distribution or movement, and controlling for phylogeographic history. We recommend using simulated data sets to explore time lags in genetic structure, and argue that time lags should be explicitly considered both when designing and interpreting landscape genetic studies. We conclude that the time lag problem can be exploited to strengthen inferences about recent landscape changes and to establish conservation baselines, particularly when genetic data are combined with other data.     

Isolation by landscape in populations of a prized edible mushroom Tricholoma matsutake

Tricholoma matsutake, a wild edible ectomycorrhizal mushroom, is revered for its distinguished flavor and iconic significance. Here, we test for landscape effects on T. matsutake gene flow and population structure in the Eastern Himalayas. Using single-nucleotide polymorphic (SNP) DNA markers, isolation by distance patterns were tested on eight populations within and between watersheds. We find that high, treeless ridgelines are effective barriers to gene flow, even at distances less than 65 km, whereas populations located within watersheds are structured at greater distances. Mantel tests demonstrated a significant positive correlation between F _st and a “landscape distance” measured as the shortest distance between population pairs below treeline r = 0.574, P = 0.002, whereas strict euclidian distances do not correlate. AMOVA analysis revealed significant partitioning with 91% of the genetic variance found within populations and 7% found between watersheds, indicative of sexually recombining populations with limited gene flow between watersheds. We show that landscape is an important determinant of air-dispersed ectomycorrhizal species population structure in heterogeneous landscapes.     

A conceptual framework for the spatial analysis of landscape genetic data

Understanding how landscape heterogeneity constrains gene flow and the spread of adaptive genetic variation is important for biological conservation given current global change. However, the integration of population genetics, landscape ecology and spatial statistics remains an interdisciplinary challenge at the levels of concepts and methods. We present a conceptual framework to relate the spatial distribution of genetic variation to the processes of gene flow and adaptation as regulated by spatial heterogeneity of the environment, while explicitly considering the spatial and temporal dynamics of landscapes, organisms and their genes. When selecting the appropriate analytical methods, it is necessary to consider the effects of multiple processes and the nature of population genetic data. Our framework relates key landscape genetics questions to four levels of analysis: (i) node-based methods, which model the spatial distribution of alleles at sampling locations (nodes) from local site characteristics; these methods are suitable for modeling adaptive genetic variation while accounting for the presence of spatial autocorrelation. (ii) Link-based methods, which model the probability of gene flow between two patches (link) and relate neutral molecular marker data to landscape heterogeneity; these methods are suitable for modeling neutral genetic variation but are subject to inferential problems, which may be alleviated by reducing links based on a network model of the population. (iii) Neighborhood-based methods, which model the connectivity of a focal patch with all other patches in its local neighborhood; these methods provide a link to metapopulation theory and landscape connectivity modeling and may allow the integration of node- and link-based information, but applications in landscape genetics are still limited. (iv) Boundary-based methods, which delineate genetically homogeneous populations and infer the location of genetic boundaries; these methods are suitable for testing for barrier effects of landscape features in a hypothesis-testing framework. We conclude that the power to detect the effect of landscape heterogeneity on the spatial distribution of genetic variation can be increased by explicit consideration of underlying assumptions and choice of an appropriate analytical approach depending on the research question.