Effect of landscape features on genetic structure of the goitered gazelle (<Emphasis Type="Italic">Gazella subgutturosa</Emphasis>) in Central Iran

The populations of goitered gazelle suffered significant decline due to natural and anthropogenic factors over the last century. Investigating the effects of barriers on gene flow among the remaining populations is vital for conservation planning. Here we adopted a landscape genetics approach to evaluate the genetic structure of the goitered gazelle in Central Iran and the effects of landscape features on gene flow using 15 polymorphic microsatellite loci. Spatial autocorrelation, isolation by distance (IBD) and isolation by resistance (IBR) models were used to elucidate the effects of landscape features on the genetic structure. Ecological modeling was used to construct landscape permeability and resistance map using 12 ecogeographical variables. Bayesian algorithms revealed three genetically homogeneous groups and restricted dispersal pattern in the six populations. The IBD and spatial autocorrelation revealed a pattern of decreasing relatedness with increasing distance. The distribution of potential habitats was strongly correlated with bioclimatic factors, vegetation type, and elevation. Resistance distances and graph theory were significantly related with variation in genetic structure, suggesting that gazelles are affected by landscape composition. The IBD showed greater impact on genetic structure than IBR. The Mantel and partial Mantel tests indicated low but non-significant effects of anthropogenic barriers on observed genetic structure. We concluded that a combination of geographic distance, landscape resistance, and anthropogenic factors are affecting the genetic structure and gene flow of populations. Future road construction might impede connectivity and gene exchange of populations. Conservation measures on this vulnerable species should consider some isolated population as separate management units.     

Genetic discontinuities and disequilibria in recently established populations of the plant pathogenic fungus Mycosphaerella fijiensis

Dispersal processes of fungal plant pathogens can be inferred from analysis of spatial genetic structures resulting from recent range expansion. The relative importance of long‐distance dispersal (LDD) events vs. gradual dispersal in shaping population structures depends on the geographical scale considered. The fungus Mycosphaerella fijiensis, pathogenic on banana, is an example of a recent worldwide epidemic. Founder effects in this species were detected at both global and continental scale, suggesting stochastic spread of the disease through LDD events. In this study, we analysed the structure of M. fijiensis populations in two recently (∼1979–1980) colonized areas in Costa Rica and Cameroon. Isolates collected in 10–15 sites distributed along a ∼250‐ to 300‐ km‐long transect in each country were analysed using 19 microsatellite markers. We detected low‐to‐moderate genetic differentiation among populations in both countries and isolation by distance in Cameroon. Combined with historical data, these observations suggest continuous range expansion at the scale of banana‐production area through gradual dispersal of spores. However, both countries displayed specific additional signatures of colonization: a sharp discontinuity in gene frequencies was observed along the Cameroon transect, while the Costa Rican populations seemed not yet to have reached genetic equilibrium. These differences in the genetic characteristics of M. fijiensis populations in two recently colonized areas are discussed in the light of historical data on disease spread and ecological data on landscape features.     

A meta‐analysis of isolation by distance: relic or reference standard for landscape genetics?

Isolation by distance (IBD) has been a common measure of genetic structure among populations and is based on Euclidean distances among populations. Whereas IBD does not incorporate geographic complexity (e.g. dispersal barriers, corridors) that may better predict genetic structure, a new approach (landscape genetics) joins landscape ecology with population genetics to better model genetic structure. Should IBD be set aside or should it persist as the most simple model in landscape genetics? We evaluated the status of IBD by collecting and analyzing results of 240 IBD data sets among diverse taxa and study systems. IBD typically represented a low proportion of variance in genetic structure (mean r²=0.22) in part because many studies included relatively few populations (mean=11). The number of populations studied (N) was asymptotically related to IBD significance; a study with 9 populations has only 50% probability of significance, while one with >23 populations will have 90% probability of significance. Surprisingly, ectothermic animals were significantly (p=0.0018) more likely to have significant IBD than endotherms, which suggests a metabolic basis underlying gene flow rates. We also observed marginally significant effects on IBD significance for a) taxa in general and b) dispersal modes within actively‐dispersing endotherms. Other factors analyzed (genetic markers, genetic distances, habitats, active or passive dispersal, plant growth form) did not significantly affect IBD, likely related to typical N. For multiple reasons we conclude that IBD should continue as the simplest reference standard against which all other, more complex models should be compared in landscape genetics research.     

Founder effects and stochastic dispersal at the continental scale of the fungal pathogen of bananas Mycosphaerella fijiensis

The worldwide destructive epidemic of the fungus Mycosphaerella fijiensis on banana started recently, spreading from South-East Asia. The founder effects detected in the global population structure of M. fijiensis reflected rare migration events among continents through movements of infected plant material. The main objective of this work was to infer gene flow and dispersal processes of M. fijiensis at the continental scale from population structure analysis in recently invaded regions. Samples of isolates were collected from banana plantations in 13 countries in Latin America and the Caribbean and in Africa. The isolates were analysed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and microsatellite molecular markers. The results indicate that a high level of genetic diversity was maintained at the plantation and the plant scales. The loci were at gametic equilibrium in most of the samples analysed, supporting the hypothesis of the existence of random-mating populations of M. fijiensis, even at the plant scale. A low level of gene diversity was observed in some populations from the Africa and Latin America-Caribbean regions. Nearly half the populations analysed showed a significant deviation from mutation-drift equilibrium with gene diversity excess. Finally, a high level of genetic differentiation was detected between populations from Africa (FST = 0.19) and from the Latin America-Caribbean region (FST = 0.30). These results show that founder effects accompanied the recent invasion of M. fijiensis in both regions, suggesting stochastic spread of the disease at the continental scale. This spread might be caused by either the limited dispersal of ascospores or by movements of infected plant material.     

The gravity of pollination: integrating at‐site features into spatial analysis of contemporary pollen movement

Pollen‐mediated gene flow is a major driver of spatial genetic structure in plant populations. Both individual plant characteristics and site‐specific features of the landscape can modify the perceived attractiveness of plants to their pollinators and thus play an important role in shaping spatial genetic variation. Most studies of landscape‐level genetic connectivity in plants have focused on the effects of interindividual distance using spatial and increasingly ecological separation, yet have not incorporated individual plant characteristics or other at‐site ecological variables. Using spatially explicit simulations, we first tested the extent to which the inclusion of at‐site variables influencing local pollination success improved the statistical characterization of genetic connectivity based upon examination of pollen pool genetic structure. The addition of at‐site characteristics provided better models than those that only considered interindividual spatial distance (e.g. IBD). Models parameterized using conditional genetic covariance (e.g. population graphs) also outperformed those assuming panmixia. In a natural population of Cornus florida L. (Cornaceae), we showed that the addition of at‐site characteristics (clumping of primary canopy opening above each maternal tree and maternal tree floral output) provided significantly better models describing gene flow than models including only between‐site spatial (IBD) and ecological (isolation by resistance) variables. Overall, our results show that including interindividual and local ecological variation greatly aids in characterizing landscape‐level measures of contemporary gene flow.     

NONSTATIONARY PATTERNS OF ISOLATION‐BY‐DISTANCE: INFERRING MEASURES OF LOCAL GENETIC DIFFERENTIATION WITH BAYESIAN KRIGING

Patterns of isolation‐by‐distance (IBD) arise when population differentiation increases with increasing geographic distances. Patterns of IBD are usually caused by local spatial dispersal, which explains why differences of allele frequencies between populations accumulate with distance. However, spatial variations of demographic parameters such as migration rate or population density can generate nonstationary patterns of IBD where the rate at which genetic differentiation accumulates varies across space. To characterize nonstationary patterns of IBD, we infer local genetic differentiation based on Bayesian kriging. Local genetic differentiation for a sampled population is defined as the average genetic differentiation between the sampled population and fictive neighboring populations. To avoid defining populations in advance, the method can also be applied at the scale of individuals making it relevant for landscape genetics. Inference of local genetic differentiation relies on a matrix of pairwise similarity or dissimilarity between populations or individuals such as matrices of between pairs of populations. Simulation studies show that maps of local genetic differentiation can reveal barriers to gene flow but also other patterns such as continuous variations of gene flow across habitat. The potential of the method is illustrated with two datasets: single nucleotide polymorphisms from human Swedish populations and dominant markers for alpine plant species.     

Landscape genetics of plants

Landscape genetics is the amalgamation of landscape ecology and population genetics to help with understanding microevolutionary processes such as gene flow and adaptation. In this review, we examine why landscape genetics of plants lags behind that of animals, both in number of studies and consideration of landscape elements. The classical landscape distance/resistance approach to study gene flow is challenging in plants, whereas boundary detection and the assessment of contemporary gene flow are more feasible. By contrast, the new field of landscape genetics of adaptive genetic variation, establishing the relationship between adaptive genomic regions and environmental factors in natural populations, is prominent in plant studies. Landscape genetics is ideally suited to study processes such as migration and adaptation under global change.     

The influence of landscape on gene flow in the eastern massasauga rattlesnake (Sistrurus c. catenatus): insight from computer simulations

Understanding how gene flow shapes contemporary population structure requires the explicit consideration of landscape composition and configuration. New landscape genetic approaches allow us to link such heterogeneity to gene flow within and among populations. However, the attribution of cause is difficult when landscape features are spatially correlated, or when genetic patterns reflect past events. We use spatial Bayesian clustering and landscape resistance analysis to identify the landscape features that influence gene flow across two regional populations of the eastern massasauga rattlesnake, Sistrurus c. catenatus. Based on spatially explicit simulations, we inferred how habitat distribution modulates gene flow and attempted to disentangle the effects of spatially confounded landscape features. We found genetic clustering across one regional landscape but not the other, and also local differences in the effect of landscape on gene flow. Beyond the effects of isolation‐by‐distance, water bodies appear to underlie genetic differentiation among individuals in one regional population. Significant effects of roads were additionally detected locally, but these effects are possibly confounded with the signal of water bodies. In contrast, we found no signal of isolation‐by‐distance or landscape effects on genetic structure in the other regional population. Our simulations imply that these local differences have arisen as a result of differences in population density or tendencies for juvenile rather than adult dispersal. Importantly, our simulations also demonstrate that the ability to detect the consequences of contemporary anthropogenic landscape features (e.g. roads) on gene flow may be compromised when long‐standing natural features (e.g. water bodies) co‐exist on the landscape.     

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.     

Landscape genetics of a pollinator longhorn beetle [Typocerus v. velutinus (Olivier)] on a continuous habitat surface

Landscape connectivity, the degree to which the landscape structure facilitates or impedes organismal movement and gene flow, is increasingly important to conservationists and land managers. Metrics for describing the undulating shape of continuous habitat surfaces can expand the usefulness of continuous gradient surfaces that describe habitat and predict the flow of organisms and genes. We adopted a landscape gradient model of habitat and used surface metrics of connectivity to model the genetic continuity between populations of the banded longhorn beetle [Typocerus v. velutinus (Olivier)] collected at 17 sites across a fragmentation gradient in Indiana, USA. We tested the hypothesis that greater habitat connectivity facilitates gene flow between beetle populations against a null model of isolation by distance (IBD). We used next‐generation sequencing to develop 10 polymorphic microsatellite loci and genotype the individual beetles to assess the population genetic structure. Isolation by distance did not explain the population genetic structure. The surface metrics model of habitat connectivity explained the variance in genetic dissimilarities 30 times better than the IBD model. We conclude that surface metrology of habitat maps is a powerful extension of landscape genetics in heterogeneous landscapes.     

Genetic Structure Is Associated with Phenotypic Divergence in Floral Traits and Reproductive Investment in a High-Altitude Orchid from the Iron Quadrangle,Southeastern Brazil

Knowledge of the role of Neotropical montane landscapes in shaping genetic connectivity and local adaptation is essential for understanding the evolutionary processes that have shaped the extraordinary species diversity in these regions. In the present study, we examined the landscape genetics, estimated genetic diversity, and explored genetic relationships with morphological variability and reproductive strategies in seven natural populations of Cattleya liliputana (Orchidaceae). Nuclear microsatellite markers were used for genetic analyses. Spatial Bayesian clustering and population-based analyses revealed significant genetic structuring and high genetic diversity (He = 0.733 ± 0.03). Strong differentiation was found between populations over short spatial scales (FST = 0.138, p < 0.001), reflecting the landscape discontinuity and isolation. Monmonier´s maximum difference algorithm, Bayesian analysis on STRUCTURE and principal component analysis identified one major genetic discontinuity between populations. Divergent genetic groups showed phenotypic divergence in flower traits and reproductive strategies. Increased sexual reproductive effort was associated with rock outcrop type and may be a response to adverse conditions for growth and vegetative reproduction. Here we discuss the effect of restricted gene flow, local adaptation and phenotypic plasticity as drivers of population differentiation in Neotropical montane rock outcrops.     

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.     

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.     

植物景观遗传学研究进展

植物景观遗传学是新兴的景观遗传学交叉学科的一个重要研究方向。目前植物景观遗传学的研究虽落后于动物,但其在生物多样性保护方面具有的巨大潜力不可忽视。从景观特征对遗传结构、环境因素对适应性遗传变异影响两个方面,系统综述了近十年来国际上植物景观遗传学的研究焦点和研究进展,比较了植物景观遗传学与动物景观遗传学研究在研究设计和研究方法上的异同,并基于将来植物景观遗传学由对空间遗传结构的描述发展为对景观遗传效应的量化分析及预测的发展框架,具体针对目前景观特征与遗传结构研究设计的系统性差、遗传结构与景观格局在时间上的误配、适应性位点与环境变量的模糊匹配、中性遗传变异与适应性遗传变异研究的分隔、景观与遗传关系分析方法的局限等五个方面提出了研究对策。     

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.     

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.     

Isolation-by-distance in landscapes: considerations for landscape genetics

In landscape genetics, isolation-by-distance (IBD) is regarded as a baseline pattern that is obtained without additional effects of landscape elements on gene flow. However, the configuration of suitable habitat patches determines deme topology, which in turn should affect rates of gene flow. IBD patterns can be characterized either by monotonically increasing pairwise genetic differentiation (for example, F_ST) with increasing interdeme geographic distance (case-I pattern) or by monotonically increasing pairwise genetic differentiation up to a certain geographical distance beyond which no correlation is detectable anymore (case-IV pattern). We investigated if landscape configuration influenced the rate at which a case-IV pattern changed to a case-I pattern. We also determined at what interdeme distance the highest correlation was measured between genetic differentiation and geographic distance and whether this distance corresponded to the maximum migration distance. We set up a population genetic simulation study and assessed the development of IBD patterns for several habitat configurations and maximum migration distances. We show that the rate and likelihood of the transition of case-IV to case-I F_ST–distance relationships was strongly influenced by habitat configuration and maximum migration distance. We also found that the maximum correlation between genetic differentiation and geographic distance was not related to the maximum migration distance and was measured across all deme pairs in a case-I pattern and, for a case-IV pattern, at the distance where the F_ST–distance curve flattens out. We argue that in landscape genetics, separate analyses should be performed to either assess IBD or the landscape effects on gene flow.     

The walk is never random: subtle landscape effects shape gene flow in a continuous white-tailed deer population in the Midwestern United States

One of the pervasive challenges in landscape genetics is detecting gene flow patterns within continuous populations of highly mobile wildlife. Understanding population genetic structure within a continuous population can give insights into social structure, movement across the landscape and contact between populations, which influence ecological interactions, reproductive dynamics or pathogen transmission. We investigated the genetic structure of a large population of deer spanning the area of Wisconsin and Illinois, USA, affected by chronic wasting disease. We combined multiscale investigation, landscape genetic techniques and spatial statistical modelling to address the complex questions of landscape factors influencing population structure. We sampled over 2000 deer and used spatial autocorrelation and a spatial principal components analysis to describe the population genetic structure. We evaluated landscape effects on this pattern using a spatial autoregressive model within a model selection framework to test alternative hypotheses about gene flow. We found high levels of genetic connectivity, with gradients of variation across the large continuous population of white-tailed deer. At the fine scale, spatial clustering of related animals was correlated with the amount and arrangement of forested habitat. At the broader scale, impediments to dispersal were important to shaping genetic connectivity within the population. We found significant barrier effects of individual state and interstate highways and rivers. Our results offer an important understanding of deer biology and movement that will help inform the management of this species in an area where overabundance and disease spread are primary concerns.     

Population structure and landscape genetics in the endangered subterranean rodent Ctenomys porteousi

In order to devise adequate conservation and management strategies for endangered species, it is important to incorporate a reliable understanding of its spatial population structure, detecting the existence of demographic partitions throughout its geographical range and characterizing the distribution of its genetic diversity. Moreover, in species that occupy fragmented habitats it is essential to know how landscape characteristics may affect the genetic connectivity among populations. In this study we use eight microsatellite markers to analyze population structure and gene flow patterns in the complete geographic range of the endangered rodent Ctenomys porteousi. Also, we use landscape genetics approaches to evaluate the effects of landscape configuration on the genetic connectivity among populations. In spite of geographical proximity of the sampling sites (8–27 km between the nearest sites) and the absence of marked barriers to individual movement, strong population structure and low values of gene flow were observed. Genetic differentiation among sampling sites was consistent with a simple model of isolation by distance, where peripheral areas showed higher population differentiation than those sites located in the central area of the species’ distribution. Landscape genetics analysis suggested that habitat fragmentation at regional level has affected the distribution of genetic variation among populations. The distance of sampling sites to areas of the landscape having higher habitat connectivity was the environmental factor most strongly related to population genetic structure. In general, our results indicate strong genetic structure in C. porteousi, even at a small spatial scale, and suggest that habitat fragmentation could increase the population differentiation.