Landscape Genetic Studies Research Articles

Development and characterization of 15 novel microsatellite markers for the freshwater fish Galaxias platei

Galaxias platei is a fish species restricted to lakes and rivers from Patagonia. In this study, 15 novel microsatellite loci were developed and characterized for 64 individuals of G. platei collected from a Patagonian lake. Eight loci were polymorphic and seven were monomorphic. The number of alleles in the polymorphic loci ranged from 3 to 6, and the expected and observed heterozygosities ranged from 0.08 to 0.68, and 0.08 to 0.62, respectively. These new markers are being used in an ongoing landscape genetics study on G. platei.

SDMtoolbox: a python‐based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses

Summary Species distribution models (SDMs) are broadly used in ecological and evolutionary studies. Almost all SDM methods require extensive data preparation in a geographic information system (GIS) prior to model building. Often, this step is cumbersome and, if not properly done, can lead to poorly parameterized models or in some cases, if too difficult, prevents the realization of SDMs. Further, for many studies, the creation of SDMs is not the final result and the post‐modelling processing can be equally arduous as other steps. SDMtoolbox is designed to facilitate many complicated pre‐ and post‐processing steps commonly required for species distribution modelling and other geospatial analyses. SDMtoolbox consists of 59 Python script‐based GIS tools developed and compiled into a single interface. A large set of the tools were created to complement SDMs generated in Maxent or to improve the predictive performance of SDMs created in Maxent. However, SDMtoolbox is not limited to analyses of Maxent models, and many tools are also available for additional analyses or general geospatial processing: for example, assessing landscape connectivity of haplotype networks (using least‐cost corridors or least‐cost paths); correcting SDM over‐prediction; quantifying distributional changes between current and future SDMs; or for calculating several biodiversity metrics, such as corrected weighted endemism. SDMtoolbox is a free comprehensive python‐based toolbox for macroecology, landscape genetic and evolutionary studies to be used in ArcGIS 10.1 (or higher) with the Spatial Analyst extension. The toolkit simplifies many GIS analyses required for species distribution modelling and other analyses, alleviating the need for repetitive and time‐consuming climate data pre‐processing and post‐SDM analyses.

Life history influences how fire affects genetic diversity in two lizard species.

'Fire mosaics' are often maintained in landscapes to promote successional diversity in vegetation with little understanding of how this will affect ecological processes in animal populations such as dispersal, social organization and re-establishment. To investigate these processes, we conducted a replicated, spatiotemporal landscape genetics study of two Australian woodland lizard species [Amphibolurus norrisi (Agamidae) and Ctenotus atlas (Scincidae)]. Agamids have a more complex social and territory structure than skinks, so fire might have a greater impact on their population structure and thus genetic diversity. Genetic diversity increased with time since fire in C. atlas and decreased with time since fire in A. norrisi. For C. atlas, this might reflect its increasing population size after fire, but we could not detect increased gene flow that would reduce the loss of genetic diversity through genetic drift. Using landscape resistance analyses, we found no evidence that postfire habitat succession or topography affected gene flow in either species and we were unable to distinguish between survival and immigration as modes of postfire re-establishment. In A. norrisi, we detected female-biased dispersal, likely reflecting its territorial social structure and polygynous mating system. The increased genetic diversity in A. norrisi in recently burnt habitat might reflect a temporary disruption of its territoriality and increased male dispersal, a hypothesis that was supported with a simulation experiment. Our results suggest that the effects of disturbance on genetic diversity will be stronger for species with territorial social organization.

A multiscale analysis of gene flow for the New England cottontail, an imperiled habitat specialist in a fragmented landscape.

Landscape features of anthropogenic or natural origin can influence organisms' dispersal patterns and the connectivity of populations. Understanding these relationships is of broad interest in ecology and evolutionary biology and provides key insights for habitat conservation planning at the landscape scale. This knowledge is germane to restoration efforts for the New England cottontail (Sylvilagus transitionalis), an early successional habitat specialist of conservation concern. We evaluated local population structure and measures of genetic diversity of a geographically isolated population of cottontails in the northeastern United States. We also conducted a multiscale landscape genetic analysis, in which we assessed genetic discontinuities relative to the landscape and developed several resistance models to test hypotheses about landscape features that promote or inhibit cottontail dispersal within and across the local populations. Bayesian clustering identified four genetically distinct populations, with very little migration among them, and additional substructure within one of those populations. These populations had private alleles, low genetic diversity, critically low effective population sizes (3.2–36.7), and evidence of recent genetic bottlenecks. Major highways and a river were found to limit cottontail dispersal and to separate populations. The habitat along roadsides, railroad beds, and utility corridors, on the other hand, was found to facilitate cottontail movement among patches. The relative importance of dispersal barriers and facilitators on gene flow varied among populations in relation to landscape composition, demonstrating the complexity and context dependency of factors influencing gene flow and highlighting the importance of replication and scale in landscape genetic studies. Our findings provide information for the design of restoration landscapes for the New England cottontail and also highlight the dual influence of roads, as both barriers and facilitators of dispersal for an early successional habitat specialist in a fragmented landscape.

New insights into the genetic structure of Araucaria araucana forests based on molecular and historic evidences

The conservation of genetic resources is a prerequisite for the maintenance of long-lived forest species. Araucaria araucana (Mol.) K. Koch is one of the oldest conifers in South America and a representative symbol of Chilean forest due to its endemicity and longevity. The aim of this study was to evaluate the genetic structure of the current A. araucana populations in Chile, to verify the possible genetic divergence between Coastal and Andean populations and to assess whether bottleneck events have influenced habitat fragmentation and threaten the genetic resources and evolutionary potential of the species. Twelve natural populations, nine from the Andes Cordillera and three from the Coast Cordillera were analysed by means of eight genomic microsatellite markers developed in A. araucana. Results of analysis of molecular variance (AMOVA) highlighted significant differentiation between Coastal and Andean populations (16 %; P = 0.004), detecting one significant barrier that separated populations from both Cordilleras as maximally differentiated areas. At local scale, both ranges revealed significant inter-population differentiation, with higher values for Coastal populations compared with Andean populations. These results suggested the presence of four gene pools (three in the Andes and one in the Coast Cordilleras) and one population (VIL) in the Coast Cordillera that differed to the rest. The differentiation between the Andean and Coastal populations may provide important baseline data that should allow further studies of landscape genetics in the species and that can contribute to develop conservation strategies for its genetic resources.

A plea for simultaneously considering matrix quality and local environmental conditions when analysing landscape impacts on effective dispersal

Landscape genetics has tremendous potential for enhancing our understanding about landscape effects on effective dispersal and resulting genetic structures. However, the vast majority of landscape genetic studies focus on effects of the landscape among sampling locations on dispersal (i.e. matrix quality), while effects of local environmental conditions are rather neglected. Such local environmental conditions include patch size, habitat type or resource availability and are commonly used in (meta-) population ecology and population genetics. In our opinion, landscape genetic studies would greatly benefit from simultaneously incorporating both matrix quality and local environmental conditions when assessing landscape effects on effective dispersal. To illustrate this point, we first outline the various ways in which environmental heterogeneity can influence different stages of the dispersal process. We then propose a three-step approach for assessing local and matrix effects on effective dispersal and review how both types of effects can be considered in landscape genetic analyses. Using simulated data, we show that it is possible to correctly disentangle the relative importance of matrix quality vs. local environmental conditions for effective dispersal. We argue that differentiating local and matrix effects in such a way is crucial for predicting future species distribution and persistence, and for optimal conservation decisions that are based on landscape genetics. In sum, we think it is timely to move beyond purely statistical, pattern-oriented analyses in landscape genetics and towards process-oriented approaches that consider the full range of possible landscape effects on dispersal behaviour and resulting gene flow.

Circuit theory emphasizes the importance of edge-crossing decisions in dispersal-scale movements of a forest passerine

Measuring landscape connectivity in ways that reflect an animal’s propensity or reluctance to move across a given landscape is key for planning effective conservation strategies. Resistance distance, based on circuit theory, is one such measure relevant for modeling how broad-scale animal movements over long time periods may lead to gene flow across the landscape. Despite the success of circuit theory in landscape genetic studies, its applicability to model finer-scale processes such as the movement patterns of individual animals within their breeding grounds (e.g., while prospecting for territories) has yet to be tested. Here, we applied both circuit models and least-cost models to understand the relationship between landscape connectivity and return time of Ovenbirds (Seiurus aurocapilla) that had been translocated at least 20 km from their home territory near Quebec City, Canada. Using an iterative optimization process, we derived resistance values for three cover types (forest, edge, and open) that resulted in resistance distance values that best explained Ovenbird return times. We also identified the cover-type resistance values that yielded length of least-cost path estimates that best explained return times of the translocated birds. The circuit theory and least-cost path methods were equally supported by the data despite being based on different sets of resistance values. The optimal resistance values for calculating resistance distance indicated that for Ovenbirds, traversing a given distance of edge habitat presented a substantially greater resistance than that of open areas. On the other hand, optimized resistances of edge and open were very similar for calculating length of least-cost path. The circuit theory approach suggested that for an Ovenbird moving through fragmented habitat, the number of forest-open transitions (i.e., edge-crossings) that an individual must make is critical to understanding return times after translocation. The least-cost path approach, on the other hand, suggested that the birds strongly avoid all open areas, regardless of size. Circuit theory offers an important new approach for understanding landscapes from the perspective of individuals moving within their breeding range, at finer spatial scales and shorter time scales than have been previously considered.

Landscape effects on gene flow for a climate‐sensitive montane species, theAmerican pika

Climate change is arguably the greatest challenge to conservation of our time. Most vulnerability assessments rely on past and current species distributions to predict future persistence but ignore species' abilities to disperse through landscapes, which may be particularly important in fragmented habitats and crucial for long-term persistence in changing environments. Landscape genetic approaches explore the interactions between landscape features and gene flow and can clarify how organisms move among suitable habitats, but have suffered from methodological uncertainties. We used a landscape genetic approach to determine how landscape and climate-related features influence gene flow for American pikas (Ochotona princeps) in Crater Lake National Park. Pikas are heat intolerant and restricted to cool microclimates; thus, range contractions have been predicted as climate changes. We evaluated the correlation between landscape variables and genetic distance using partial Mantel tests in a causal modelling framework, and used spatially explicit simulations to evaluate methods of model optimization including a novel approach based on relative support and reciprocal causal modelling. We found that gene flow was primarily restricted by topographic relief, water and west-facing aspects, suggesting that physical restrictions related to small body size and mode of locomotion, as well as exposure to relatively high temperatures, limit pika dispersal in this alpine habitat. Our model optimization successfully identified landscape features influencing resistance in the simulated data for this landscape, but underestimated the magnitude of resistance. This is the first landscape genetic study to address the fundamental question of what limits dispersal and gene flow in the American pika.

Microsatellite markers for Bokermannohyla species (Anura, Hylidae) from the Brazilian Cerrado and Atlantic Forest domains

We characterized 22 polymorphic microsatellite markers for the Brazilian treefrog Bokermannohyla ibitiguara and tested their cross-amplification in B. alvarengai, B. circumdata and B. hylax. Our focal species occurs in protected and disturbed Brazilian Cerrado landscapes, a highly threatened savanna in central Brazil. Fourteen markers successfully cross-amplified for at least one congener. These microsatellites will be useful for studies of mating systems, relatedness and landscape genetics of Cerrado populations under various deforestation levels. Moreover, variable markers for B. circumdata and B. hylax will also be useful for landscape genetic studies of taxa typical of the threatened Atlantic Forest domain.

Métodos de análisis genéticos, espaciales y de conectividad en genética del paisaje

Landscape genetics focuses on evaluating the interaction between landscape features (e.g., mountains, corridors) and environmental variables like temperature or humidity with microevolutionary processes like gene flow, genetic drift or selection. For this, landscape genetics uses different methods of analysis from other areas like population genetics, landscape ecology and spatial statistics, together with some of its own. In the present we explain what is landscpae genetics and, in accordance with the objective of the review, we include an integration of the theoretical basis, assumptions, advantages and limitations of the most frequent methods used in landscape genetics, which we exemplify with diverse case studies. Based on such integration, we propose that the design of analyses in a landscape genetics study should be developed following 5 steps, for each of which we explain its conceptual basis, the most adequate methods and the most commonly software used to evaluate: 1) the genetic variation and structure patterns, 2) the spatially-genetic structure patterns, 3) the gene flow (functional connectivity), 4) the landscape quality (structural connectivity), and 5) the correlation between genetic patterns and landscape features. We end by highlighting the advances we consider are more urgently needed regarding methods of analyses for landscape genetics.

Hierarchical population structure and genetic diversity of lake trout (Salvelinus namaycush) in a dendritic system in Northern Labrador

Summary Freshwater systems are ideal for landscape genetics studies; they generally exhibit asymmetry in gene flow with populations arranged in a hierarchical, dendritic fashion. Such gene flow asymmetry has the potential to influence the distribution of genetic variation, with downstream populations typically exhibiting higher genetic diversity than headwater populations. Lake trout (Salvelinus namaycush) are widely distributed throughout temperate North America. We examined the relationship between landscape attributes, molecular genetic diversity and differentiation among lake trout populations inhabiting a hierarchically structured freshwater system in northern Labrador (the Kogaluk River drainage). Lake trout (N = 567) collected from ten lakes in this drainage were examined for polymorphism at 12 microsatellite loci. The lakes differed in connectivity, size, elevation and position within the Kogaluk catchment. We observed relatively high levels of population structure and little migration among lakes. Waterfalls were identified as a factor contributing to the observed differentiation. Although a preliminary analysis suggested an isolation‐by‐distance pattern, a subsequent decomposed pairwise regression analysis allowed the identification of outlier lakes. Removal of these outlier lakes and of one other headwater lake, isolated from the rest by several waterfalls, led to the disappearance of the isolation‐by‐distance pattern, suggesting very little or no migration among lakes despite migration being physically possible. Estimates of effective population size correlated with lake area but did not differ between headwater and downstream populations, nor was there a relationship with elevation, a result consistent with the evidence of very little to zero gene flow among lakes. Our study is the first to describe patterns of genetic diversity among lake trout populations inhabiting a spatially fragmented system in an ecologically pristine and sensitive area of northern Canada, the barren grounds of northern Labrador.

SPATIO-TEMPORAL CHANGES IN THE STRUCTURE OF AN AUSTRALIAN FROG HYBRID ZONE: A 40-YEAR PERSPECTIVE

Spatio-temporal studies of hybrid zones provide an opportunity to test evolutionary hypotheses of hybrid zone maintenance and movement. We conducted a landscape genetics study on a classic hybrid zone of the south-eastern Australian frogs, Litoria ewingii and Litoria paraewingi. This hybrid zone has been comprehensively studied since the 1960s, providing the unique opportunity to directly assess changes in hybrid zone structure across time. We compared both mtDNA and male advertisement call data from two time periods (present and 1960s). Clinal analysis of the coincidence (same center) and concordance (same width) of these traits indicated that the center of the hybrid zone has shifted 1 km south over the last 40 years, although the width of the zone and the rate of introgression remained unchanged. The low frequency of hybrids, the strong concordance of clines within a time period, and the small but significant movement across the study period despite significant anthropogenic changes through the region, suggest the hybrid zone is a tension zone located within a low-density trough. Hybrid zone movement has not been considered common in the past but our findings highlight that it should be considered a crucial component to our understanding of evolution.

Limited effects of suburbanization on the genetic structure of an abundant vernal pool-breeding amphibian

Habitat fragmentation and degradation associated with suburbanization can have negative consequences on population persistence through the reduction of dispersal and concomitant gene flow. Using eight polymorphic microsatellite loci, we assessed the effects of forest fragmentation, water quality and hydroperiod on the genetic structure of a vernal pool-breeding amphibian, the wood frog (Lithobates sylvaticus), across 20 ponds in an unfragmented, forested landscape and 45 ponds in a landscape fragmented by moderate suburban development. Analyses were performed at the broad scale of the study area and at a fine scale, with spatially independent clusters of ponds selected within each landscape. Bayesian clustering approaches and AMOVA identified little population structure at the scale of the study area. At the fine scale, genetic structure was correlated with geographic distance and the presence of roads in two of the three fragmented clusters. Spatial autocorrelation analyses detected positive spatial genetic structure and restricted dispersal in one of the clusters in the fragmented landscape. We identified barriers associated with roads and suburban development in the fragmented landscape and with large bodies of water and elevation in the unfragmented landscape. Lastly, we found no biologically meaningful effects of water quality or hydroperiod on genetic variation. The results of this study indicate that wood frog populations are well connected, with high gene flow, across the landscape of southeastern New Hampshire, and that fragmenting features of suburbanization to date have a small but detectable impact on fine-scale genetic structure. The potential exists for greater impacts with higher levels of development or longer time scales. Our findings also highlight the importance of replication in landscape genetic studies, as the genetic response we detected varied with a gradient of fragmentation.

Unravelling landscape variables with multiple approaches to overcome scarce species knowledge: a landscape genetic study of the slow worm

Landscape genetics was developed to detect landscape elements shaping genetic population structure, including the effects of fragmentation. Multifarious environmental variables can influence gene flow in different ways and expert knowledge is frequently used to construct friction maps. However, the extent of the migration and the movement of single individuals are frequently unknown, especially for non-model species, and friction maps only based on expert knowledge can be misleading. In this study, we used three different methods: isolation by distance (IBD), least-cost modelling and a strip-based approach to disentangle the human implication in the fragmentation process in the slow worm (Anguis fragilis), as well as the specific landscape elements shaping the genetic structure in a highly anthropized 16 km2 area in Switzerland. Friction maps were constructed using expert opinion, but also based on the combination of all possible weightings for all landscape elements. The IBD indicated a significant effect of geographic distance on genetic differentiation. Further approaches demonstrated that highways and railways were the most important elements impeding the gene flow in this area. Surprisingly, we also found that agricultural areas and dense forests seemed to be used as dispersal corridors. These results confirmed that the slow worm has relatively unspecific habitat requirements. Finally, we showed that our models based on expert knowledge performed poorly compared to cautious analysis of each variable. This study demonstrated that landscape genetic analyses should take expert knowledge with caution and exhaustive analyses of each landscape element without a priori knowledge and different methods can be recommended.

Spatial scale affects landscape genetic analysis of a wetland grasshopper

Most landscape genetic studies assess the impact of landscape elements on species' dispersal and gene flow. Many of these studies perform their analysis on all possible population pairs in a study area and do not explicitly consider the effects of spatial scale and population network topology on their results. Here, we examined the effects of spatial scale and population network topology on the outcome of a landscape genetic analysis. Additionally, we tested whether the relevant spatial scale of landscape genetic analysis could be defined by population network topology or by isolation-by-distance (IBD) patterns. A data set of the wetland grasshopper Stethophyma grossum, collected in a fragmented agricultural landscape, was used to analyse population network topology, IBD patterns and dispersal habitats, using least-cost transect analysis. Landscape genetic analyses neglecting spatial scale and population network topology resulted in models with low fits, with which a most likely dispersal habitat could not be identified. In contrast, analyses considering spatial scale and population network topology resulted in high model fits by restricting landscape genetic analysis to smaller scales (0-3 km) and neighbouring populations, as represented by a Gabriel graph. These models also successfully identified a likely dispersal habitat of S. grossum. The above results suggest that spatial scale and potentially population network topology should be more explicitly considered in future landscape genetic analyses.

Circuit Theory and Model-Based Inference for Landscape Connectivity

Circuit theory has seen extensive recent use in the field of ecology, where it is often applied to study functional connectivity. The landscape is typically represented by a network of nodes and resistors, with the resistance between nodes a function of landscape characteristics. The effective distance between two locations on a landscape is represented by the resistance distance between the nodes in the network. Circuit theory has been applied to many other scientific fields for exploratory analyses, but parametric models for circuits are not common in the scientific literature. To model circuits explicitly, we demonstrate a link between Gaussian Markov random fields and contemporary circuit theory using a covariance structure that induces the necessary resistance distance. This provides a parametric model for second-order observations from such a system. In the landscape ecology setting, the proposed model provides a simple framework where inference can be obtained for effects that landscape features have on functional connectivity. We illustrate the approach through a landscape genetics study linking gene flow in alpine chamois (Rupicapra rupicapra) to the underlying landscape.

Seascape Genetics: Populations, Individuals, and Genes Marooned and Adrift

AbstractSeascape genetics is the study of how spatially variable structural and environmental features influence genetic patterns of marine organisms. Seascape genetics is conceptually linked to landscape genetics and this likeness frequently allows investigators to use similar theoretical and analytical methods for both seascape genetics and landscape genetics. But, the physical and environmental attributes of the ocean and biological attributes of organisms that live in the sea, especially the large spatial scales of seascape features and the high dispersal ability of many marine organisms, differ from those of terrestrial organisms that have typified landscape genetic studies. This paper reviews notable papers in the emerging field of seascape genetics, highlighting pervasive themes and biological attributes of species and seascape features that affect spatial genetic patterns in the sea. Similarities to, and differences from, (terrestrial) landscape genetics are discussed, and future directions are recommended.

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

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

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.

Adaptive Genetic Variation on the Landscape: Methods and Cases

There is a growing interest in identifying ecological factors that influence adaptive genetic diversity patterns in both model and nonmodel species. The emergence of large genomic and environmental data sets, as well as the increasing sophistication of population genetics methods, provides an opportunity to characterize these patterns in relation to the environment. Landscape genetics has emerged as a flexible analytical framework that connects patterns of adaptive genetic variation to environmental heterogeneity in a spatially explicit context. Recent growth in this field has led to the development of numerous spatial statistical methods, prompting a discussion of the current benefits and limitations of these approaches. Here we provide a review of the design of landscape genetics studies, the different statistical tools, some important case studies, and perspectives on how future advances in this field are likely to shed light on important processes in evolution and ecology.