Landscape Genetic Studies Research Articles

Using simulations to evaluate Mantel‐based methods for assessing landscape resistance to gene flow

Mantel‐based tests have been the primary analytical methods for understanding how landscape features influence observed spatial genetic structure. Simulation studies examining Mantel‐based approaches have highlighted major challenges associated with the use of such tests and fueled debate on when the Mantel test is appropriate for landscape genetics studies. We aim to provide some clarity in this debate using spatially explicit, individual‐based, genetic simulations to examine the effects of the following on the performance of Mantel‐based methods: (1) landscape configuration, (2) spatial genetic nonequilibrium, (3) nonlinear relationships between genetic and cost distances, and (4) correlation among cost distances derived from competing resistance models. Under most conditions, Mantel‐based methods performed poorly. Causal modeling identified the true model only 22% of the time. Using relative support and simple Mantel r values boosted performance to approximately 50%. Across all methods, performance increased when landscapes were more fragmented, spatial genetic equilibrium was reached, and the relationship between cost distance and genetic distance was linearized. Performance depended on cost distance correlations among resistance models rather than cell‐wise resistance correlations. Given these results, we suggest that the use of Mantel tests with linearized relationships is appropriate for discriminating among resistance models that have cost distance correlations <0.85 with each other for causal modeling, or <0.95 for relative support or simple Mantel r. Because most alternative parameterizations of resistance for the same landscape variable will result in highly correlated cost distances, the use of Mantel test‐based methods to fine‐tune resistance values will often not be effective.

Reducing bias in population and landscape genetic inferences: the effects of sampling related individuals and multiple life stages

In population or landscape genetics studies, an unbiased sampling scheme is essential for generating accurate results, but logistics may lead to deviations from the sample design. Such deviations may come in the form of sampling multiple life stages. Presently, it is largely unknown what effect sampling different life stages can have on population or landscape genetic inference, or how mixing life stages can affect the parameters being measured. Additionally, the removal of siblings from a data set is considered best-practice, but direct comparisons of inferences made with and without siblings are limited. In this study, we sampled embryos, larvae, and adult Ambystoma maculatum from five ponds in Missouri, and analyzed them at 15 microsatellite loci. We calculated allelic richness, heterozygosity and effective population sizes for each life stage at each pond and tested for genetic differentiation (FST and DC) and isolation-by-distance (IBD) among ponds. We tested for differences in each of these measures between life stages, and in a pooled population of all life stages. All calculations were done with and without sibling pairs to assess the effect of sibling removal. We also assessed the effect of reducing the number of microsatellites used to make inference. No statistically significant differences were found among ponds or life stages for any of the population genetic measures, but patterns of IBD differed among life stages. There was significant IBD when using adult samples, but tests using embryos, larvae, or a combination of the three life stages were not significant. We found that increasing the ratio of larval or embryo samples in the analysis of genetic distance weakened the IBD relationship, and when using DC, the IBD was no longer significant when larvae and embryos exceeded 60% of the population sample. Further, power to detect an IBD relationship was reduced when fewer microsatellites were used in the analysis.

Butterfly dispersal in farmland: a replicated landscape genetics study on the meadow brown butterfly (Maniola jurtina)

Anthropogenic activities readily result in the fragmentation of habitats such that species persistence increasingly depends on their ability to disperse. However, landscape features that enhance or limit individual dispersal are often poorly understood. Landscape genetics has recently provided innovative solutions to evaluate landscape resistance to dispersal. We studied the dispersal of the common meadow brown butterfly, Maniola jurtina, in agricultural landscapes, using a replicated study design and rigorous statistical analyses. Based on existing behavioral and life history research, we hypothesized that the meadow brown would preferentially disperse through its preferred grassy habitats (meadows and road verges) and avoid dispersing through woodlands and the agricultural matrix. Samples were collected in 18 study landscapes of 5 × 5 km in three contrasting agricultural French regions. Using circuit theory, least cost path and transect-based methods, we analyzed the effect of the landscape on gene flow separately for each sex. Analysis of 1681 samples with 6 microsatellites loci revealed that landscape features weakly influence meadow brown butterfly gene flow. Gene flow in both sexes appeared to be weakly limited by forests and arable lands, whereas grasslands and grassy linear elements (road verges) were more likely to enhance gene flow. Our results are consistent with the hypothesis of greater dispersal through landscape elements that are most similar to suitable habitat. Our spatially replicated landscape genetics study allowed us to detect subtle landscape effects on butterfly gene flow, and these findings were reinforced by consistent results across analytical methods.

Navigating the pitfalls and promise of landscape genetics.

The field of landscape genetics has been evolving rapidly since its emergence in the early 2000s. New applications, techniques and criticisms of techniques appear like clockwork with each new journal issue. The developments are an encouraging, and at times bewildering, sign of progress in an exciting new field of study. However, we suggest that the rapid expansion of landscape genetics has belied important flaws in the development of the field, and we add an air of caution to this breakneck pace of expansion. Specifically, landscape genetic studies often lose sight of the fundamental principles and complex consequences of gene flow, instead favouring simplistic interpretations and broad inferences not necessarily warranted by the data. Here, we describe common pitfalls that characterize such studies, and provide practical guidance to improve landscape genetic investigation, with careful consideration of inferential limits, scale, replication, and the ecological and evolutionary context of spatial genetic patterns. Ultimately, the utility of landscape genetics will depend on translating the relationship between gene flow and landscape features into an understanding of long-term population outcomes. We hope the perspective presented here will steer landscape genetics down a more scientifically sound and productive path, garnering a field that is as informative in the future as it is popular now.

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 distance, resistance and/or clusters? Lessons learned from a forest-dwelling carnivore inhabiting a heterogeneous landscape.

Landscape genetics provides a valuable framework to understand how landscape features influence gene flow and to disentangle the factors that lead to discrete and/or clinal population structure. Here, we attempt to differentiate between these processes in a forest-dwelling small carnivore [European pine marten (Martes martes)]. Specifically, we used complementary analytical approaches to quantify the spatially explicit genetic structure and diversity and analyse patterns of gene flow for 140 individuals genotyped at 15 microsatellite loci. We first used spatially explicit and nonspatial Bayesian clustering algorithms to partition the sample into discrete clusters and evaluate hypotheses of 'isolation by barriers' (IBB). We further characterized the relationships between genetic distance and geographical ('isolation by distance', IBD) and ecological distances ('isolation by resistance', IBR) obtained from optimized landscape models. Using a reciprocal causal modelling approach, we competed the IBD, IBR and IBB hypotheses with each other to unravel factors driving population genetic structure. Additionally, we further assessed spatially explicit indices of genetic diversity using sGD across potentially overlapping genetic neighbourhoods that matched the inferred population structure. Our results revealed a complex spatial genetic cline that appears to be driven jointly by IBD and partial barriers to gene flow (IBB) associated with poor habitat and interspecific competition. Habitat loss and fragmentation, in synergy with past overharvesting and possible interspecific competition with sympatric stone marten (Martes foina), are likely the main factors responsible for the spatial genetic structure we observed. These results emphasize the need for a more thorough evaluation of discrete and clinal hypotheses governing gene flow in landscape genetic studies, and the potential influence of different limiting factors affecting genetic structure at different spatial scales.

Ecological connectivity assessment in a strongly structured fire salamander (Salamandra salamandra) population.

Small populations are more prone to extinction if the dispersal among them is not adequately maintained by ecological connections. The degree of isolation between populations could be evaluated measuring their genetic distance, which depends on the respective geographic (isolation by distance, IBD) and/or ecological (isolation by resistance, IBR) distances. The aim of this study was to assess the ecological connectivity of fire salamander Salamandra salamandra populations by means of a landscape genetic approach. The species lives in broad-leaved forest ecosystems and is particularly affected by fragmentation due to its habitat selectivity and low dispersal capability. We analyzed 477 biological samples collected in 47 sampling locations (SLs) in the mainly continuous populations of the Prealpine and Eastern foothill lowland (PEF) and 10 SLs in the fragmented populations of the Western foothill (WF) lowland of Lombardy (northern Italy). Pairwise genetic distances (Chord distance, DC) were estimated from allele frequencies of 16 microsatellites loci. Ecological distances were calculated using one of the most promising methodology in landscape genetics studies, the circuit theory, applied to habitat suitability maps. We realized two habitat suitability models: one without barriers (EcoD) and a second one accounting for the possible barrier effect of main roads (EcoDb). Mantel tests between distance matrices highlighted how the Log-DC in PEF populations was related to log-transformed geographic distance (confirming a prevalence of IBD), while it was explained by the Log-EcoD, and particularly by the Log-EcoDb, in WF populations, even when accounting for the confounding effect of geographic distance (highlighting a prevalence of IBR). Moreover, we also demonstrated how considering the overall population, the effect of Euclidean or ecological distances on genetic distances acting at the level of a single group (PEF or WF populations) could not be detected, when population are strongly structured.

Genetic structure of a montane perennial plant: the influence of landscape and flowering phenology

The way that genetic variation is distributed geographically has important conservation and evolutionary implications. Here, we examined the distribution of genetic variation within and among populations of the montane perennial Ipomopsis aggregata. We sampled plants in western Colorado and examined (1) population genetic structure over a geographic area that spanned 130 km, including genetic variation within disturbed and undisturbed sites; (2) the relationship between genetic differentiation and geographic distance; and (3) the relationship between flowering time and genetic differentiation among plants within and among geographic areas. F IS was significantly higher (t test, P = 0.006), expected heterozygosity was significantly lower (t test, P = 0.04), and allelic richness was marginally significantly lower (t test, P = 0.078) among anthropogenically-disturbed sites compared to undisturbed sites. We found moderate genetic differentiation over the area sampled (average pairwise F ST = 0.04; average pairwise $$F^{\prime}_{ST} = 0.19$$ ), but no association of genetic and geographic distance (Mantel test P values 0.44 for F ST and 0.36 for $$F^{\prime}_{ST}$$ ). We found a strong association of flowering time and genetic differentiation over small and large spatial scales. Genetic differentiation between early and late flowering plants within a focal site was statistically significant (genic test for population differentiation combined P value <0.001; F ST = 0.05). There was a significant correlation between genetic distance ( $$F^{\prime}_{ST}$$ ) and distance in flowering time, when controlling for geographic distance, over the whole geographic area (Partial Mantel test R xy = 0.32, P = 0.013). A multiple regression with randomization further supported the inference that flowering time, but not geographic distance or elevation, predicted $$F^{\prime}_{ST}$$ (geographic distance: β = −0.03, P = 0.89; elevation: β = 0.01, P = 0.96; phenological distance: β = 0.30, P = 0.05), but not F st (geographic distance: β = −0.02, P = 0.92; elevation: β = 0.14, P = 0.38; phenological distance: β = 0.25, P = 0.11), unless elevation was left out of the model (geographic distance: β = −0.03, P = 0.9; phenological distance: β = 0.29, P = 0.03). The association of flowering time and genetic distance despite the lack of isolation by distance provides further evidence for the usefulness of incorporating this variable into plant landscape genetic studies when possible.

Isolation and characterization of microsatellite markers for an endemic tree in East Asia, Quercus variabilis (Fagaceae).

Premise of the study:Microsatellite markers of Quercus variabilis (Fagaceae) were isolated for population genetic and landscape genetic studies.Methods and Results:Roche 454 pyrosequencing combined with the magnetic bead enrichment protocol were used to isolate microsatellite markers for Q. variabilis. A total of 2121 microsatellites were identified from 63,851 individual sequence reads. One hundred microsatellite loci were selected to test primer amplification efficiency among 24 individuals from two wild populations. Among the 100 tested markers, 34 primer pairs were successfully amplified. Of these, 14 yielded polymorphic amplification products, whereas the remaining 20 loci were monomorphic. The number of alleles for polymorphic loci ranged from two to six, and the observed heterozygosity ranged from 0.042 to 0.750.Conclusions:These microsatellite loci will provide useful tools for further population genetic and landscape genetic studies on Q. variabilis.

Nest suitability, fine-scale population structure and male-mediated dispersal of a solitary ground nesting bee in an urban landscape.

Bees are the primary pollinators of flowering plants in almost all ecosystems. Worldwide declines in bee populations have raised awareness about the importance of their ecological role in maintaining ecosystem functioning. The naturally strong philopatric behavior that some bee species show can be detrimental to population viability through increased probability of inbreeding. Furthermore, bee populations found in human-altered landscapes, such as urban areas, can experience lower levels of gene flow and effective population sizes, increasing potential for inbreeding depression in wild bee populations. In this study, we investigated the fine-scale population structure of the solitary bee Colletes inaequalis in an urbanized landscape. First, we developed a predictive spatial model to detect suitable nesting habitat for this ground nesting bee and to inform our field search for nests. We genotyped 18 microsatellites in 548 female individuals collected from nest aggregations throughout the study area. Genetic relatedness estimates revealed that genetic similarity among individuals was slightly greater within nest aggregations than among randomly chosen individuals. However, genetic structure among nest aggregations was low (Nei’s GST = 0.011). Reconstruction of parental genotypes revealed greater genetic relatedness among females than among males within nest aggregations, suggesting male-mediated dispersal as a potentially important mechanism of population connectivity and inbreeding avoidance. Size of nesting patch was positively correlated with effective population size, but not with other estimators of genetic diversity. We detected a positive trend between geographic distance and genetic differentiation between nest aggregations. Our landscape genetic models suggest that increased urbanization is likely associated with higher levels of inbreeding. Overall, these findings emphasize the importance of density and distribution of suitable nesting patches for enhancing bee population abundance and connectivity in human dominated habitats and highlights the critical contribution of landscape genetic studies for enhanced conservation and management of native pollinators.

Ecological strategies predict associations between aquatic and genetic connectivity for dryland amphibians.

The study of how population genetic structure is shaped by attributes of the environment is a central scientific pursuit in ecology and conservation. But limited resources may prohibit landscape genetics studies for many threatened species, particularly given the pace of current environmental change. Understanding the extent to which species' ecological strategies--their life histories, biology, and behavior-predict patterns and drivers of population connectivity is a critical step in evaluating the potential of multi-taxa inference in landscape genetics. We present results of a landscape genetic study of three dryland amphibians: the canyon treefrog (Hyla arenicolor), red-spotted toad (Anaxyrus punctatus), and Mexican spadefoot (Spea multiplicata). These species characterize a range of ecological strategies, driven primarily by different water dependencies, enabling amphibian survival in arid and semiarid environments. We examined a suite of hypothesized relationships between genetic connectivity and landscape connectivity across species. We found a positive relationship between population differentiation and water dependency, e.g., longer larval development periods and site fidelity for reliable water sources. We also found that aquatic connectivity is important for all species, particularly when considered with topography (slope). The effect of spatial scale varied by species, with canyon treefrogs and Mexican spadefoots characterized by relatively consistent results at different scales in contrast to the stark differences in results for red-spotted toads at different scales. Using ecological information to predict relationships between genetic and landscape connectivity is a promising approach for multi-taxa inference and may help inform conservation efforts where single-species genetic studies are not possible.

Characterisation of sixteen additional polymorphic microsatellite loci for the spreading but locally rare European butterfly, Brenthis ino (Lepidoptera: Nymphalidae)

Whilst the overall geographic range of the lesser marbled fritillary, Brenthis ino (Rottemburg, 1775), is currently expanding, this species is patchily distributed at a local spatial scale due to its use of flower rich semi-natural meadows and the aggregated distribution of its host plant. Therefore, understanding the dispersal patterns of this butterfly and the effect of increasing fragmentation of the landscapes in central and Western Europe on its population dynamics is key to determining whether this patchy distribution can lead to metapopulation structuring and dynamics. One way to determine the degree to which local populations are isolated from one another is to use high resolution molecular genetic markers and thence quantify gene flow and genetic drift. Eleven microsatellite loci have previously been developed for this species, but six showed evidence of null alleles, effectively violating key assumptions of the models used to infer gene flow. We therefore developed a set of new primer pairs to amplify a suite of 16 highly polymorphic microsatellite loci (number of alleles ranged from 2-30) of which nine were found to conform to the Hardy-Weinberg's expectations, whilst at the same time not showing any clear signature for the presence of null alleles. We further describe how these primers were optimized for landscape and metapopulation genetics studies in Belgian Ardenne.

Spatial heterogeneity in landscape structure influences dispersal and genetic structure: empirical evidence from a grasshopper in an agricultural landscape.

Dispersal may be strongly influenced by landscape and habitat characteristics that could either enhance or restrict movements of organisms. Therefore, spatial heterogeneity in landscape structure could influence gene flow and the spatial structure of populations. In the past decades, agricultural intensification has led to the reduction in grassland surfaces, their fragmentation and intensification. As these changes are not homogeneously distributed in landscapes, they have resulted in spatial heterogeneity with generally less intensified hedged farmland areas remaining alongside streams and rivers. In this study, we assessed spatial pattern of abundance and population genetic structure of a flightless grasshopper species, Pezotettix giornae, based on the surveys of 363 grasslands in a 430-km² agricultural landscape of western France. Data were analysed using geostatistics and landscape genetics based on microsatellites markers and computer simulations. Results suggested that small-scale intense dispersal allows this species to survive in intensive agricultural landscapes. A complex spatial genetic structure related to landscape and habitat characteristics was also detected. Two P.giornae genetic clusters bisected by a linear hedged farmland were inferred from clustering analyses. This linear hedged farmland was characterized by high hedgerow and grassland density as well as higher grassland temporal stability that were suspected to slow down dispersal. Computer simulations demonstrated that a linear-shaped landscape feature limiting dispersal could be detected as a barrier to gene flow and generate the observed genetic pattern. This study illustrates the relevance of using computer simulations to test hypotheses in landscape genetics studies.

Dispersal strength determines meta‐community structure in a dendritic riverine network

AbstractAimMeta‐community structure is a function of both local (site‐specific) and regional (landscape‐level) ecological factors, and the relative importance of each may be mediated by the dispersal ability of organisms. Here, we used aquatic invertebrate communities to investigate the relationship between local and regional factors in explaining distance decay relationships (DDRs) in fragmented dendritic stream networks.LocationDryland streams distributed within a 400‐km2 section of the San Pedro River basin, south‐eastern Arizona, USA.MethodsWe combined fine‐scale local information (flow and habitat characteristics) with regional‐scale information to explain DDR patterns in community composition of aquatic invertebrate species with a wide range of dispersal abilities. We used a novel application of a landscape resistance modelling approach (originally developed for landscape genetic studies) that simultaneously assessed the importance of local and regional ecological factors as well as dispersal ability of organisms.ResultsWe found evidence that both local and regional factors influenced aquatic invertebrate DDRs in dryland stream networks, and the importance of each factor depended on the dispersal capacities of the organisms. Local and weak dispersers were more affected by site‐specific factors, intermediate dispersers by landscape‐level factors, and strong dispersers showed no discernable pattern. This resulted in a strongly hump‐shaped relationship between dispersal ability and landscape‐level factors, where only moderate dispersers showed evidence of DDRs. Unlike most other studies of dendritic networks, our results suggest that overland pathways, using perennial refugia as stepping‐stones, might be the main dispersal route in fragmented stream networks.Main conclusionsWe suggest that using a combination of landscape and local distance measures can help to unravel meta‐community patterns in dendritic systems. Our findings have important conservation implications, such as the need to manage river systems for organisms that span a wide variety of dispersal abilities and local ecological requirements. Our results also highlight the need to preserve perennial refugia in fragmented networks, as they may ensure the viability of aquatic meta‐communities by facilitating dispersal.

How to make landscape genetics beneficial for conservation management?

Many landscape genetic studies promise results that can be applied in conservation management. However, only few landscape genetic studies have been used by practitioners. Here, we identified scientific topics in landscape genetics that need to be addressed before results can more successfully be applied in conservation management. For each topic, weaknesses of common practice in landscape genetic analysis are described by presenting examples from current studies and further recommendations for improvements are outlined. First, we suggest matching the extent of the study area with those of conservation management units and the study species’ dispersal potential when designing landscape genetic studies. Second, the quality of the underlying statistical models should be optimised, and models should include variables that are useful for management implementation. Third, to further improve the applicability of landscape genetic studies, thresholds for landscape effects on gene flow should be identified. Fourth, landscape genetic models could be used for the development of conservation planning tools, which ideally also incorporate the above described thresholds. Fifth and as discussed in earlier studies, the use of multiple species and replication at the landscape scale is recommended. Although it appears that only few landscape genetic studies have been applied in practical management until now, examples presented in this article show that landscape genetic methods can provide important information to formulate concrete management implications. Thus, addressing the above-mentioned scientific topics in landscape genetic studies would enhance the benefits of their results for practitioners.

Isolation by environment.

The interactions between organisms and their environments can shape distributions of spatial genetic variation, resulting in patterns of isolation by environment (IBE) in which genetic and environmental distances are positively correlated, independent of geographic distance. IBE represents one of the most important patterns that results from the ways in which landscape heterogeneity influences gene flow and population connectivity, but it has only recently been examined in studies of ecological and landscape genetics. Nevertheless, the study of IBE presents valuable opportunities to investigate how spatial heterogeneity in ecological processes, agents of selection and environmental variables contributes to genetic divergence in nature. New and increasingly sophisticated studies of IBE in natural systems are poised to make significant contributions to our understanding of the role of ecology in genetic divergence and of modes of differentiation both within and between species. Here, we describe the underlying ecological processes that can generate patterns of IBE, examine its implications for a wide variety of disciplines and outline several areas of future research that can answer pressing questions about the ecological basis of genetic diversity.

Comparative landscape genetics of two river frog species occurring at different elevations on Mount Kilimanjaro.

Estimating population connectivity and species' abilities to disperse across the landscape is crucial for understanding the long-term persistence of species in changing environments. Surprisingly, few landscape genetic studies focused on tropical regions despite the alarming extinction rates within these ecosystems. Here, we compared the influence of landscape features on the distribution of genetic variation of an Afromontane frog, Amietia wittei, with that of its more broadly distributed lowland congener, Amietia angolensis, on Mt. Kilimanjaro, Tanzania. We predicted high gene flow in the montane species with movements enhanced through terrestrial habitats of the continuous rainforest. In contrast, dispersal might be restricted to aquatic corridors and reduced by anthropogenic disturbance in the lowland species. We found high gene flow in A. wittei relative to other montane amphibians. Nonetheless, gene flow was lower than in the lowland species which showed little population structure. Least-cost path analysis suggested that dispersal is facilitated by stream networks in both species, but different landscape features were identified to influence connectivity among populations. Contrary to a previous study, gene flow in the lowland species was negatively correlated with the presence of human settlements. Also, genetic subdivision in A. wittei did not coincide with specific physical barriers as in other landscape genetic studies, suggesting that factors other than topography may contribute to population divergence. Overall, these results highlight the importance of a comparative landscape genetic approach for assessing the influence of the landscape matrix on population connectivity, particularly because nonintuitive results can alter the course of conservation and management.

Comparative landscape genetics of three closely related sympatric Hesperid butterflies with diverging ecological traits.

To understand how landscape characteristics affect gene flow in species with diverging ecological traits, it is important to analyze taxonomically related sympatric species in the same landscape using identical methods. Here, we present such a comparative landscape genetic study involving three closely related Hesperid butterflies of the genus Thymelicus that represent a gradient of diverging ecological traits. We analyzed landscape effects on their gene flow by deriving inter-population connectivity estimates based on different species distribution models (SDMs), which were calculated from multiple landscape parameters. We then used SDM output maps to calculate circuit-theoretic connectivity estimates and statistically compared these estimates to actual genetic differentiation in each species. We based our inferences on two different analytical methods and two metrics of genetic differentiation. Results indicate that land use patterns influence population connectivity in the least mobile specialist T. acteon. In contrast, populations of the highly mobile generalist T. lineola were panmictic, lacking any landscape related effect on genetic differentiation. In the species with ecological traits in between those of the congeners, T. sylvestris, climate has a strong impact on inter-population connectivity. However, the relative importance of different landscape factors for connectivity varies when using different metrics of genetic differentiation in this species. Our results show that closely related species representing a gradient of ecological traits also show genetic structures and landscape genetic relationships that gradually change from a geographical macro- to micro-scale. Thus, the type and magnitude of landscape effects on gene flow can differ strongly even among closely related species inhabiting the same landscape, and depend on their relative degree of specialization. In addition, the use of different genetic differentiation metrics makes it possible to detect recent changes in the relative importance of landscape factors affecting gene flow, which likely change as a result of contemporary habitat alterations.

A practical toolbox for design and analysis of landscape genetics studies

Landscape genetics integrates theory and analytical methods of population genetics and landscape ecology. Research in this area has increased in recent decades, creating a plethora of options for study design and analysis. Here we present a practical toolbox for the design and analysis of landscape genetics studies following a seven-step framework: (1) define the study objectives, (2) consider the spatial and temporal scale of the study, (3) design a sampling regime, (4) select a genetic marker, (5) generate genetic input data, (6) generate spatial input data, and (7) choose an analytical method that integrates genetic and spatial data. Study design considerations discussed include choices of spatial and temporal scale, sample size and spatial distribution, and genetic marker selection. We present analytical methods suitable for achieving different study objectives. As emerging technologies generate genetic and spatial data sets of increasing size, complexity, and resolution, landscape geneticists are challenged to execute hypothesis-driven research that combines empirical data and simulation modeling. The landscape genetics framework presented here can accommodate new design considerations and analyses, and facilitate integration of genetic and spatial data by guiding new landscape geneticists through study design, implementation, and analysis.

Seventeen novel microsatellite markers for the southern hemisphere fish Galaxias maculatus

Galaxias maculatus is a widely distributed fish with diadromous and resident populations throughout Gondwanan regions. We present 17 novel microsatellite markers that were tested on 44 individuals from one lacustrine population in Patagonia. We found ten poly- morphic markers and seven monomorphic markers in the population under analysis. The number of alleles in the polymorphic loci ranged from 3 to 10. The observed het- erozygosities ranged from 0.11364 to 0.65909, and the expected heterozygosities ranged from 0.15204 to 0.63898. These microsatellite markers are currently being used in landscape genetic studies of G. maculatus from Patagonia.