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.     

Performance of partial statistics in individual‐based landscape genetics

Individual‐based landscape genetic methods have become increasingly popular for quantifying fine‐scale landscape influences on gene flow. One complication for individual‐based methods is that gene flow and landscape variables are often correlated with geography. Partial statistics, particularly Mantel tests, are often employed to control for these inherent correlations by removing the effects of geography while simultaneously correlating measures of genetic differentiation and landscape variables of interest. Concerns about the reliability of Mantel tests prompted this study, in which we use simulated landscapes to evaluate the performance of partial Mantel tests and two ordination methods, distance‐based redundancy analysis (dbRDA) and redundancy analysis (RDA), for detecting isolation by distance (IBD) and isolation by landscape resistance (IBR). Specifically, we described the effects of suitable habitat amount, fragmentation and resistance strength on metrics of accuracy (frequency of correct results, type I/II errors and strength of IBR according to underlying landscape and resistance strength) for each test using realistic individual‐based gene flow simulations. Mantel tests were very effective for detecting IBD, but exhibited higher error rates when detecting IBR. Ordination methods were overall more accurate in detecting IBR, but had high type I errors compared to partial Mantel tests. Thus, no one test outperformed another completely. A combination of statistical tests, for example partial Mantel tests to detect IBD paired with appropriate ordination techniques for IBR detection, provides the best characterization of fine‐scale landscape genetic structure. Realistic simulations of empirical data sets will further increase power to distinguish among putative mechanisms of differentiation.     

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.     

The influence of landscape configuration and environment on population genetic structure in a sedentary passerine: insights from loci located in different genomic regions

The study of the factors structuring genetic variation can help to infer the neutral and adaptive processes shaping the demographic and evolutionary trajectories of natural populations. Here, we analyse the role of isolation by distance (IBD), isolation by resistance (IBR, defined by landscape composition) and isolation by environment (IBE, estimated as habitat and elevation dissimilarity) in structuring genetic variation in 25 blue tit (Cyanistes caeruleus) populations. We typed 1385 individuals at 26 microsatellite loci classified into two groups by considering whether they are located into genomic regions that are actively (TL; 12 loci) or not (NTL; 14 loci) transcribed to RNA. Population genetic differentiation was mostly detected using the panel of NTL. Landscape genetic analyses showed a pattern of IBD for all loci and the panel of NTL, but genetic differentiation estimated at TL was only explained by IBR models considering high resistance for natural vegetation and low resistance for agricultural lands. Finally, the absence for IBE suggests a lack of divergent selection pressures associated with differences in habitat and elevation. Overall, our study shows that markers located in different genomic regions can yield contrasting inferences on landscape‐level patterns of realized gene flow in natural populations.     

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.     

Adaptation with gene flow across the landscape in a dune sunflower

Isolation by adaptation increases divergence at neutral loci when natural selection against immigrants reduces the rate of gene flow between different habitats. This can occur early in the process of adaptive divergence and is a key feature of ecological speciation. Despite the ability of isolation by distance (IBD) and other forms of landscape resistance to produce similar patterns of neutral divergence within species, few studies have used landscape genetics to control for these other forces. We have studied the divergence of Helianthus petiolaris ecotypes living in active sand dunes and adjacent non-dune habitat, using landscape genetics approaches, such as circuit theory and multiple regression of distance matrices, in addition to coalescent modelling. Divergence between habitats was significant, but not strong, and was shaped by IBD. We expected that increased resistance owing to patchy and unfavourable habitat in the dunes would contribute to divergence. Instead, we found that landscape resistance models with lower resistance in the dunes performed well as predictors of genetic distances among subpopulations. Nevertheless, habitat class remained a strong predictor of genetic distance when controlling for isolation by resistance and IBD. We also measured environmental variables at each site and confirmed that specific variables, especially soil nitrogen and vegetation cover, explained a greater proportion of variance in genetic distance than did landscape or the habitat classification alone. Asymmetry in effective population sizes and numbers of migrants per generation was detected using coalescent modelling with Bayesian inference, which is consistent with incipient ecological speciation being driven by the dune habitat.     

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

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

ResDisMapper: An r package for fine‐scale mapping of resistance to dispersal

Management of biological invasions and conservation activity in the fight against habitat fragmentation both require information on how ongoing dispersal of organisms is affected by the environment. However, there are few landscape genetic computer programs that map resistance to dispersal at small spatiotemporal scales. To facilitate such analyses, we present an r package named ResDisMapper for the mapping of resistance to dispersal at small spatiotemporal scales, without the need for prior knowledge on environmental features or intensive computation. Based on the concept of isolation by distance (IBD), ResDisMapper calculates resistance using deviations of each pair of samples from the general IBD trend (IBD residuals). The IBD residuals are projected onto the studied area, which allows construction and visualization of a fine‐scale map of resistance based on spatial accumulation of positive or negative IBD residuals. In this study, we tested ResDisMapper with both simulated and empirical data sets and compared its performance with two other popular landscape genetic programs. Overall, we found that ResDisMapper can map resistance with relatively high accuracy. The latest version of the package and associated documentation are available on Github ( https://github.com/takfung/ResDisMapper ).     

Drivers of genetic differentiation in a generalist insect‐pollinated herb across spatial scales

The isolation‐by‐distance model (IBD) predicts that genetic differentiation among populations increases with geographic distance. Yet, empirical studies show that a variety of ecological, topographic and historical factors may override the effect of geographic distance on genetic variation. This may particularly apply to species with narrow but highly heterogeneous distribution ranges, such as those occurring along elevational gradients. Using nine SSR markers, we study the genetic differentiation of the montane pollination‐generalist herb, Erysimum mediohispanicum. Because the effects of any given factor may depend on the geographic scale considered, we investigate the contribution of different environmental and historical factors at three different spatial scales. We evaluate five competing models that put forward the role of geographic distance, local environmental factors [biotic interactions (IBEb) and climatic variables (IBEa)], landscape resistance (IBR) and phylogeographic patterns (IBP), respectively. We find significant IBD regardless of the spatial scale and the genetic distance estimator considered. However, IBEa and IBP also play a prominent role in shaping genetic differentiation patterns at the larger spatial scales, and IBR is significant at the fine spatial scale. Overall, our results highlight the importance of combining different estimators, statistical approaches and spatial scales to disentangle the relative importance of the various ecological factors contributing to the shaping of genetic divergence patterns in natural populations.     

Effects of landscape and history on diversification of a montane, stream-breeding amphibian

Aim The aim of this study was to understand the roles of landscape features in shaping patterns of contemporary and historical genetic diversification among populations of the Andean tree frog (Hypsiboas andinus) across spatial scales. Location Andes mountains, north‐western Argentina, South America. Methods Mitochondrial DNA control region sequences were utilized to assess genetic differentiation among populations and calculate population pair‐wise genetic distances. Three models of movement, namely traditional straight‐line distance and two effective distances based on habitat classification, were examined to determine which of these explained the most variation in pair‐wise population genetic differentiation. The two habitat classifications were based on digital vegetation and hydrology layers that were generated from a 90‐m resolution digital elevation model (DEM) and known relationships between elevation and habitat. Mantel tests were conducted to test for correlations between geographic and genetic distance matrices and to estimate the percentage variation explained by each type of geographic distance. To investigate the location of possible barriers to gene flow, we used Monmonier’s maximum difference algorithm as implemented in barrier 2.2. Results At both geographic scales, effective distances explained more variation in genetic differentiation than did straight‐line distance. The least‐cost distances based on the simple classification performed better than the more detailed habitat classification. We controlled for the effects of historical range fragmentation determined from previous nested clade analyses, and therefore evaluated the effect of different distances on the genetic variation attributable to more recent factors. Effective distances identified populations that were highly divergent as a result of isolation in unsuitable habitats. The proposed locations of barriers to gene flow identified using Monmonier’s maximum difference algorithm corresponded well with earlier analyses and supported findings from our partial Mantel tests. Main conclusions Our results indicate that landscape features have been important in both historical and contemporary genetic structuring of populations of H. andinus at both large and small spatial scales. A landscape genetic perspective offers novel insights not provided by traditional phylogeographic studies: (1) effective distances can better explain patterns of differentiation in populations, especially in heterogeneous landscapes where barriers to dispersal may be common; and (2) least‐cost path analysis can help to identify corridors of movement between populations that are biologically more realistic.     

Why replication is important in landscape genetics: American black bear in the Rocky Mountains

We investigated how landscape features influence gene flow of black bears by testing the relative support for 36 alternative landscape resistance hypotheses, including isolation by distance (IBD) in each of 12 study areas in the north central U.S. Rocky Mountains. The study areas all contained the same basic elements, but differed in extent of forest fragmentation, altitude, variation in elevation and road coverage. In all but one of the study areas, isolation by landscape resistance was more supported than IBD suggesting gene flow is likely influenced by elevation, forest cover, and roads. However, the landscape features influencing gene flow varied among study areas. Using subsets of loci usually gave models with the very similar landscape features influencing gene flow as with all loci, suggesting the landscape features influencing gene flow were correctly identified. To test if the cause of the variability of supported landscape features in study areas resulted from landscape differences among study areas, we conducted a limiting factor analysis. We found that features were supported in landscape models only when the features were highly variable. This is perhaps not surprising but suggests an important cautionary note - that if landscape features are not found to influence gene flow, researchers should not automatically conclude that the features are unimportant to the species' movement and gene flow. Failure to investigate multiple study areas that have a range of variability in landscape features could cause misleading inferences about which landscape features generally limit gene flow. This could lead to potentially erroneous identification of corridors and barriers if models are transferred between areas with different landscape characteristics.     

Effect of anthropogenic landscape features on population genetic differentiation of Przewalski's gazelle: main role of human settlement

Anthropogenic landscapes influence evolutionary processes such as population genetic differentiation, however, not every type of landscape features exert the same effect on a species, hence it is necessary to estimate their relative effect for species management and conservation. Przewalski's gazelle (Procapra przewalskii), which inhabits a human-altered area on Qinghai-Tibet Plateau, is one of the most endangered antelope species in the world. Here, we report a landscape genetic study on Przewalski's gazelle. We used skin and fecal samples of 169 wild gazelles collected from nine populations and thirteen microsatellite markers to assess the genetic effect of anthropogenic landscape features on this species. For comparison, the genetic effect of geographical distance and topography were also evaluated. We found significant genetic differentiation, six genetic groups and restricted dispersal pattern in Przewalski's gazelle. Topography, human settlement and road appear to be responsible for observed genetic differentiation as they were significantly correlated with both genetic distance measures [F(ST)/(1-F(ST)) and F'(ST)/(1-F'(ST))] in Mantel tests. IBD (isolation by distance) was also inferred as a significant factor in Mantel tests when genetic distance was measured as F(ST)/(1-F(ST)). However, using partial Mantel tests, AIC(c) calculations, causal modeling and AMOVA analysis, we found that human settlement was the main factor shaping current genetic differentiation among those tested. Altogether, our results reveal the relative influence of geographical distance, topography and three anthropogenic landscape-type on population genetic differentiation of Przewalski's gazelle and provide useful information for conservation measures on this endangered species.     

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

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

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.     

Using isolation‐by‐distance‐based approaches to assess the barrier effect of linear landscape elements on badger (Meles meles) dispersal

As the European badger (Meles meles) can be of conservation or management concern, it is important to have a good understanding of the species’ dispersal ability. In particular, knowledge of landscape elements that affect dispersal can contribute to devising effective management strategies. However, the standard approach of using Bayesian clustering methods to correlate genetic discontinuities with landscape elements cannot easily be applied to this problem, as badger populations are often characterized by a strong confounding isolation‐by‐distance (IBD) pattern. We therefore developed a two‐step method that compares the location of pairs of related badgers relative to a putative barrier and utilizes the expected spatial genetic structure characterized by IBD as a null model to test for the presence of a barrier. If a linear feature disrupts dispersal, the IBD pattern characterising pairs of individuals located on different sides of a putative barrier should differ significantly from the pattern obtained with pairs of individuals located on the same side. We used our new approach to assess the impact of rivers and roads of different sizes on badger dispersal in western England. We show that a large, wide river represented a barrier to badger dispersal and found evidence that a motorway may also restrict badger movement. Conversely, we did not find any evidence for small rivers and roads interfering with badger movement. One of the advantages of our approach is that potentially it can detect features that disrupt gene flow locally, without necessarily creating distinct identifiable genetic units.     

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.     

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

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

北京市近二十年景观破碎化格局的时空变化

基于1993—2013年3期时间序列的遥感影像获得的一、二级景观类型的土地覆盖数据,利用移动窗口法和空间主成分分析法研究景观破碎度空间分布格局和破碎化过程。结果表明:北京市正处于快速城市化阶段,20年间其建设用地面积增加了1000.8 km~2,增长47.14%,而耕地面积减少21.86%;全市破碎化程度增加,其中,景观斑块总数增加了15.26%,而景观斑块的平均面积缩小了15.35%,景观形状指数(LSI)从88.426增加到98.897;北京市景观破碎化格局的空间异质性较大,但没有方向性偏好,却表现了"两极化"发展趋势,其中,高破碎化区域和低破碎化区域的面积增加,中等破碎化的区域面积减少,核心大城区和山区的景观破碎度降低,而新兴城区和郊区的景观破碎度增大;北京市景观破碎化格局的距离效应显著,呈现倒"U"型二次函数关系,其中,2013年的破碎度距离函数为:Y_3=0.1767+0.02898X_3-0.0005167X_3~2,距城市中心20—35 km处的城郊交错区景观破碎化程度最高。景观破碎化格局的分析有助于了解大城市快速发展阶段的景观格局演变规律,为城市生物多样性保护、绿地廊道维护和生态文明城市建设提供理论依据。     

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.     

大兴安岭林区道路网络对景观格局的影响

在明确大兴安岭呼中林业局道路网络系统组成特征的基础上,利用主成分分析法,将林业局内17个林场作为分析单元,以该林业局1989年景观为例,对有、无道路情况下的景观格局分别进行定量分析,探讨了道路对森林景观格局的影响.结果表明：呼中林业局内包括运材主、支路在内的常年运材路密度为2.3 m·hm^-2,在各个林场内分布均匀,基本沿着河流水系深入到各个采伐区.道路的出现使景观水平上的森林格局发生了显著变化：所有林场中,平均斑块面积减少、数量增多、斑块间距离增大,均表现出不同程度的破碎化,但破碎化程度与道路密度之间没有显著的相关性;道路网络对景观破碎程度的影响比对空间聚合程度的影响更强烈.