Population structure of spotted salamanders (Ambystoma maculatum) in a fragmented landscape

Understanding the impacts of landscape-level processes on the population biology of amphibians is critical, especially for species inhabiting anthropogenically modified landscapes. Many pond-breeding amphibians are presumed to exist as metapopulations, but few studies demonstrate the extent and consequences of this metapopulation structure. Gene flow measures may facilitate the construction of more realistic models of population structure than direct measures of migration. This is especially true for species that are cryptic, such as many amphibians. We used eight polymorphic microsatellite loci to determine the genetic population structure of spotted salamanders ( Ambystoma maculatum ) breeding at 17 ponds in northeastern Ohio, a landscape fragmented by roads, agriculture, urban areas and the Cuyahoga River. Using a variety of analyses (Bayesian clustering, F -statistics, AMOVA) we generated a model of salamander population genetic structure. Our data revealed patterns of genetic connectivity that were not predicted by geographical distances between ponds (no isolation by distance). We also tested for a relationship between population structure and several indices of landscape resistance, but found no effect of potential barriers to dispersal on genetic connectivity. Strong overall connectivity among ponds, despite the hostile habitat matrix, may be facilitated by a network of riparian corridors associated with the Cuyahoga River; however, high gene flow in this system may indicate a general ability to disperse and colonize beyond particular corridors.     

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

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

Urban landscape genetics: canopy cover predicts gene flow between white-footed mouse (Peromyscus leucopus) populations in New York City

In this study, I examine the influence of urban canopy cover on gene flow between 15 white-footed mouse (Peromyscus leucopus) populations in New York City parklands. Parks in the urban core are often highly fragmented, leading to rapid genetic differentiation of relatively nonvagile species. However, a diverse array of 'green' spaces may provide dispersal corridors through 'grey' urban infrastructure. I identify urban landscape features that promote genetic connectivity in an urban environment and compare the success of two different landscape connectivity approaches at explaining gene flow. Gene flow was associated with 'effective distances' between populations that were calculated based on per cent tree canopy cover using two different approaches: (i) isolation by effective distance (IED) that calculates the single best pathway to minimize passage through high-resistance (i.e. low canopy cover) areas, and (ii) isolation by resistance (IBR), an implementation of circuit theory that identifies all low-resistance paths through the landscape. IBR, but not IED, models were significantly associated with three measures of gene flow (Nm from F(ST) , BayesAss+ and Migrate-n) after factoring out the influence of isolation by distance using partial Mantel tests. Predicted corridors for gene flow between city parks were largely narrow, linear parklands or vegetated spaces that are not managed for wildlife, such as cemeteries and roadway medians. These results have implications for understanding the impacts of urbanization trends on native wildlife, as well as for urban reforestation efforts that aim to improve urban ecosystem processes.     

Landscape connectivity of Cercidiphyllum japonicum,an endangered species and its implications for conservation

Cercidiphyllum japonicum, a Tertiary relict, recolonized areas north of the Yangtze River after the last glacial; however, little is known about its specific colonization corridors. Together with distribution models, the least cost path (LCP) analysis has been used to reveal the landscape connectivity of species. In this study, we utilized the categorical LCP method, combining the species distribution with genetic data from cpDNA and nuclear markers, to identify the possible dispersal routes of C. japonicum after the LGM. Across time periods and genetic markers, the results revealed that the species generally spread from the western edge of the Sichuan Basin, while the highest degree of dispersal potential corresponds with the year 2080 and the cpDNA haplotype. Furthermore, shifts in the species' range and the indication of an area of low genetic divergence further support the existence of a dispersal corridor. Overall, we believe that a dispersal route from the western edge of the Sichuan Basin through the Qinling Mountains and further to the northeast could exist, and therefore, the results are an important supplement to the evolutionary history of C. japonicum. In the future, we believe species distribution models (SDM) and connectivity assessment in relation to climate change will provide increasingly useful information and new implications for prioritizing the conservation of the endangered species.     

Connectivity and gene flow among Eastern Tiger Salamander (Ambystoma tigrinum) populations in highly modified anthropogenic landscapes

Fragmented landscapes resulting from anthropogenic habitat modification can have significant impacts on dispersal, gene flow, and persistence of wildlife populations. Therefore, quantifying population connectivity across a mosaic of habitats in highly modified landscapes is critical for the development of conservation management plans for threatened populations. Endangered populations of the eastern tiger salamander (Ambystoma tigrinum) in New York and New Jersey are at the northern edge of the species’ range and remaining populations persist in highly developed landscapes in both states. We used landscape genetic approaches to examine regional genetic population structure and potential barriers to migration among remaining populations. Despite the post-glacial demographic processes that have shaped genetic diversity in tiger salamander populations at the northern extent of their range, we found that populations in each state belong to distinct genetic clusters, consistent with the large geographic distance that separates them. We detected overall low genetic diversity and high relatedness within populations, likely due to recent range expansion, isolation, and relatively small population sizes. Nonetheless, landscape connectivity analyses reveal habitat corridors among remaining breeding ponds. Furthermore, molecular estimates of population connectivity among ponds indicate that gene flow still occurs at regional scales. Further fragmentation of remaining habitat will potentially restrict dispersal among breeding ponds, cause the erosion of genetic diversity, and exacerbate already high levels of inbreeding. We recommend the continued management and maintenance of habitat corridors to ensure long-term viability of these endangered populations.     

Effects of structural connectivity on fine scale population genetic structure of muskrat,Ondatra zibethicus

In heterogeneous landscapes, physical barriers and loss of structural connectivity have been shown to reduce gene flow and therefore lead to population structuring. In this study, we assessed the influence of landscape features on population genetic structure and gene flow of a semiaquatic species, the muskrat. A total of 97 muskrats were sampled from three watersheds near Sudbury, Ontario, Canada. We estimated population genetic structure using 11 microsatellite loci and identified a single genetic cluster and no genetic differences were found among the watersheds as a result of high levels of gene flow. At finer scales, we assessed the correlation between individual pairwise genetic distances and Euclidean distance as well as different models of least cost path (LCP). We used a range of cost values for the landscape types in order to build our LCP models. We found a positive relationship between genetic distance and least cost distance when we considered roads as corridors for movements. Open landscapes and urban areas seemed to restrict but not prevent gene flow within the study area. Our study underlines the high‐dispersal ability of generalist species in their use of landscape and highlights how landscape features often considered barriers to animal movements are corridors for other species.     

Seascape genetics: a coupled oceanographic-genetic model predicts population structure of Caribbean corals

Population genetics is a powerful tool for measuring important larval connections between marine populations [1-4]. Similarly, oceanographic models based on environmental data can simulate particle movements in ocean currents and make quantitative estimates of larval connections between populations possible [5-9]. However, these two powerful approaches have remained disconnected because no general models currently provide a means of directly comparing dispersal predictions with empirical genetic data (except, see [10]). In addition, previous genetic models have considered relatively simple dispersal scenarios that are often unrealistic for marine larvae [11-15], and recent landscape genetic models have yet to be applied in a marine context [16-20]. We have developed a genetic model that uses connectivity estimates from oceanographic models to predict genetic patterns resulting from larval dispersal in a Caribbean coral. We then compare the predictions to empirical data for threatened staghorn corals. Our coupled oceanographic-genetic model predicts many of the patterns observed in this and other empirical datasets; such patterns include the isolation of the Bahamas and an east-west divergence near Puerto Rico [3, 21-23]. This new approach provides both a valuable tool for predicting genetic structure in marine populations and a means of explicitly testing these predictions with empirical data.     

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.     

Landscape genetics of alpine Sierra Nevada salamanders reveal extreme population subdivision in space and time

Quantifying the influence of the landscape on the genetic structure of natural populations remains an important empirical challenge, particularly for poorly studied, ecologically cryptic species. We conducted an extensive microsatellite analysis to examine the population genetics of the southern long‐toed salamander (Ambystoma macrodactylum sigillatum) in a naturally complex landscape. Using spatially explicit modelling, we investigated the influence of the Sierra Nevada topography on potential dispersal corridors between sampled populations. Our results indicate very high‐genetic divergence among populations, high within‐deme relatedness, and little evidence of recent migration or population admixture. We also discovered unexpectedly high between‐year genetic differentiation (F_ST) for breeding sites, suggesting that breeding groups vary over localized space and time. While environmental factors associated with high‐elevation montane habitats apparently play an important role in shaping population differentiation, additional, species‐specific biological processes must also be operating to account for observed deviations from temporal, among‐year panmixia. Our study emphasizes the population‐level insights that can be gained from high‐density sampling in space and time, and the highly substructured population biology that may characterize amphibians in extreme montane habitats.     

Landscape genetic analyses reveal fine‐scale effects of forest fragmentation in an insular tropical bird

Within the framework of landscape genetics, resistance surface modelling is particularly relevant to explicitly test competing hypotheses about landscape effects on gene flow. To investigate how fragmentation of tropical forest affects population connectivity in a forest specialist bird species, we optimized resistance surfaces without a priori specification, using least‐cost (LCP) or resistance (IBR) distances. We implemented a two‐step procedure in order (i) to objectively define the landscape thematic resolution (level of detail in classification scheme to describe landscape variables) and spatial extent (area within the landscape boundaries) and then (ii) to test the relative role of several landscape features (elevation, roads, land cover) in genetic differentiation in the Plumbeous Warbler (Setophaga plumbea). We detected a small‐scale reduction of gene flow mainly driven by land cover, with a negative impact of the nonforest matrix on landscape functional connectivity. However, matrix components did not equally constrain gene flow, as their conductivity increased with increasing structural similarity with forest habitat: urban areas and meadows had the highest resistance values whereas agricultural areas had intermediate resistance values. Our results revealed a higher performance of IBR compared to LCP in explaining gene flow, reflecting suboptimal movements across this human‐modified landscape, challenging the common use of LCP to design habitat corridors and advocating for a broader use of circuit theory modelling. Finally, our results emphasize the need for an objective definition of landscape scales (landscape extent and thematic resolution) and highlight potential pitfalls associated with parameterization of resistance surfaces.     

Scale‐dependent genetic structure of the Idaho giant salamander (Dicamptodon aterrimus) in stream networks

The network architecture of streams and rivers constrains evolutionary, demographic and ecological processes of freshwater organisms. This consistent architecture also makes stream networks useful for testing general models of population genetic structure and the scaling of gene flow. We examined genetic structure and gene flow in the facultatively paedomorphic Idaho giant salamander, Dicamptodon aterrimus, in stream networks of Idaho and Montana, USA. We used microsatellite data to test population structure models by (i) examining hierarchical partitioning of genetic variation in stream networks; and (ii) testing for genetic isolation by distance along stream corridors vs. overland pathways. Replicated sampling of streams within catchments within three river basins revealed that hierarchical scale had strong effects on genetic structure and gene flow. amova identified significant structure at all hierarchical scales (among streams, among catchments, among basins), but divergence among catchments had the greatest structural influence. Isolation by distance was detected within catchments, and in‐stream distance was a strong predictor of genetic divergence. Patterns of genetic divergence suggest that differentiation among streams within catchments was driven by limited migration, consistent with a stream hierarchy model of population structure. However, there was no evidence of migration among catchments within basins, or among basins, indicating that gene flow only counters the effects of genetic drift at smaller scales (within rather than among catchments). These results show the strong influence of stream networks on population structure and genetic divergence of a salamander, with contrasting effects at different hierarchical scales.     

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.     

Combining the least cost path method with population genetic data and species distribution models to identify landscape connectivity during the late Quaternary in Himalayan hemlock

Himalayan hemlock (Tsuga dumosa) experienced a recolonization event during the Quaternary period; however, the specific dispersal routes are remain unknown. Recently, the least cost path (LCP) calculation coupled with population genetic data and species distribution models has been applied to reveal the landscape connectivity. In this study, we utilized the categorical LCP method, combining species distribution of three periods (the last interglacial, the last glacial maximum, and the current period) and locality with shared chloroplast, mitochondrial, and nuclear haplotypes, to identify the possible dispersal routes of T. dumosa in the late Quaternary. Then, both a coalescent estimate of migration rates among regional groups and establishment of genetic divergence pattern were conducted. After those analyses, we found that the species generally migrated along the southern slope of Himalaya across time periods and genomic makers, and higher degree of dispersal was in the present and mtDNA haplotype. Furthermore, the direction of range shifts and strong level of gene flow also imply the existence of Himalayan dispersal path, and low area of genetic divergence pattern suggests that there are not any obvious barriers against the dispersal pathway. Above all, we inferred that a dispersal route along the Himalaya Mountains could exist, which is an important supplement for the evolutionary history of T. dumosa. Finally, we believed that this integrative genetic and geospatial method would bring new implications for the evolutionary process and conservation priority of species in the Tibetan Plateau.     

Using resistance distance from circuit theory to model dispersal through habitat corridors

Aims Resistance distance (RD), based on circuit theory, is a promising metric for modelling effects of landscape configuration on dispersal of organisms and the resulting population and community patterns. The values of RD reflect the likelihood of a random walker to reach from a source to a certain destination in the landscape. Although it has successfully been used to model genetic structures of animal populations, where it most often outperforms other isolation metrics, there are hardly any applications to plants and, in particular, to plant community data. Our aims were to test if RD was a suitable metric for studying dispersal processes of plants in narrow habitat corridors (linear landscape elements [LLE]). This would be the case, if dispersal processes (seed dispersal and migration) resembled random walks. Further, we compared the model performance of RD against least-cost distance (LCD) and Euclidean distance (ED). Finally, we tested the suitability of different cost surfaces for calculations of LCD and RD.Methods We used data from 50 vegetation plots located on semi-natural LLE (field margins, ditches, road verges) in eight agricultural landscapes of Northwest Germany. We mapped LLE, including hedges and tree rows, from aerial images in a Geographic Information System, converted the maps into raster layers, and assigned resistance values to the raster cells, where all cells outside of LLE received infinite resistance and, thus, represented barriers to dispersal. For all pairs of plots within study areas, we calculated Jaccard similarity assuming that it was a proxy (or correlate) of dispersal events between plots. Further, we calculated RD and LCD of the network of LLE and ED between the plots. We modelled the effects of distance metrics on community similarity using binomial generalized linear mixed models.Important findings ED was clearly the least suitable isolation metrics. Further, we found that RD performed better than LCD at modelling Jaccard similarity. Predictions varied markedly between the two distance metrics suggesting that RD comprises additional information about the landscape beyond spatial distance, such as the possible presence of multiple pathways between plots. Cost surfaces with equal cell-level resistances for all types of LLE performed better than more complex ones with habitat-specific resistances. We conclude that RD is a highly suitable measure of isolation or, inversely, connectivity for studying dispersal processes of plants within habitat corridors. It is likely also suitable for assessing landscape permeability in other landscape types with areal habitats instead of narrow corridors. RD holds the potential to improve assessments of isolation (or connectivity) for models of regional population and meta-community dynamics.     

Developing approaches for linear mixed modeling in landscape genetics through landscape‐directed dispersal simulations

Dispersal can impact population dynamics and geographic variation, and thus, genetic approaches that can establish which landscape factors influence population connectivity have ecological and evolutionary importance. Mixed models that account for the error structure of pairwise datasets are increasingly used to compare models relating genetic differentiation to pairwise measures of landscape resistance. A model selection framework based on information criteria metrics or explained variance may help disentangle the ecological and landscape factors influencing genetic structure, yet there are currently no consensus for the best protocols. Here, we develop landscape‐directed simulations and test a series of replicates that emulate independent empirical datasets of two species with different life history characteristics (greater sage‐grouse; eastern foxsnake). We determined that in our simulated scenarios, AIC and BIC were the best model selection indices and that marginal R² values were biased toward more complex models. The model coefficients for landscape variables generally reflected the underlying dispersal model with confidence intervals that did not overlap with zero across the entire model set. When we controlled for geographic distance, variables not in the underlying dispersal models (i.e., nontrue) typically overlapped zero. Our study helps establish methods for using linear mixed models to identify the features underlying patterns of dispersal across a variety of landscapes.     

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.     

Influence of life-history variation on the genetic structure of two sympatric salamander taxa

Life-history characteristics are an important determinant of a species' dispersal abilities. We predict that variation in life history can influence population-level genetic patterns. To test this prediction, we estimate population-level genetic structure for two sympatric species of stream-breeding salamander. The Cope's giant salamander ( Dicamptodon copei ) rarely metamorphoses into a terrestrial adult, thereby limiting overland dispersal and potentially gene flow. In contrast, the Pacific giant salamander ( D. tenebrosus ) commonly metamorphoses, which is expected to facilitate overland dispersal and gene flow. Three sets of analyses based on microsatellite data support these hypotheses, showing that D . tenebrosus displays minimal population-level genetic structuring and no pattern of isolation by distance, whereas D . copei displays a high degree of population-level genetic structure and significant isolation by distance. Specifically, nearly all pairwise F _ST values were significantly different from 0 between populations of D. copei , with fewer than half the pairwise F _ST values significant from 0 in D. tenebrosus . Additionally, S tructure analyses indicated eight genetic clusters for D. copei but only one genetic cluster for D. tenebrosus . Finally, Mantel tests showed significant correlations between stream and overland distance with genetic distance for D. copei but no significant correlations of either landscape feature for D. tenebrosus at the scale of the study. These results provide a case study of the link between life-history variation and population genetic patterns while controlling for phylogeny and environmental variation.     

Simulation modeling reveals the evolutionary role of landscape shape and species dispersal on genetic variation within a metapopulation

Different shapes of landscape boundaries can affect the habitat networks within them and consequently the spatial genetic-patterns of a metapopulation. In this study, we used a mechanistic framework to evaluate the effects of landscape shape, through watershed elongation, on genetic divergence among populations at the metapopulation scale. Empirical genetic data from four, sympatric stream-macroinvertebrates having aerial adults were collected from streams in Japan to determine the roles of species-specific dispersal strategies on metapopulation genetics. Simulation results indicated that watershed elongation allows the formation of river networks with fewer branches and larger topographic constraints. This results in decreased interpopulation connectivity but a lower level of spatial isolation of distal populations (e.g. those found in headwaters) occurring in the landscapes examined. Distal populations had higher genetic divergence when their downstream-biased dispersal (relative to upstream- and/or overland-biased dispersal) was high. This underscores the importance of distal populations influencing genetic divergence at the metapopulation scale for species having downstream-biased dispersal. In turn, lower genetic divergence was observed under watershed elongation when the genetic isolation of distal populations was decreased in such species. This strong association between landscape shape and evolutionary processes highlights the importance of natural, spatial architecture in assessing the effectiveness of conservation and management strategies.     

Population connectivity and genetic diversity of American marten (Martes americana) in the United States northern Rocky Mountains in a climate change context

Climate change is likely to alter population connectivity, particularly for species associated with higher elevation environments. The goal of this study is to predict the potential effects of future climate change on population connectivity and genetic diversity of American marten populations across a 30.2 million hectare region of the in the US northern Rocky Mountains. We use a landscape resistance model validated from empirical landscape genetics modeling to predict the current and expected future extent and fragmentation of American marten dispersal habitat under five climate change scenarios, corresponding to climatic warming of between 0.7 and 3.3 °C, consistent with expected climate change by year 2080. We predict the regions of the current and future landscapes where gene flow is expected to be governed by isolation by distance and the regions where population fragmentation is expected to limit gene flow. Finally, we predict changes in the strength and location of predicted movement corridors, fracture zones and the location of dispersal barriers across the study area in each scenario. We found that under the current climate, gene flow is predicted to be limited primarily by distance (isolation), and landscape structure does not significantly limit gene flow, resulting in very high genetic diversity over most of the study area. Projected climatic warming substantially reduces the extent and increases the fragmentation of marten populations in the western and northwestern parts of the study area. In contrast, climate change is not predicted to fragment the extensive higher elevation mountain massifs in central Idaho, the northern U.S. continental divide, and Greater Yellowstone Ecosystem. In addition, we show locations in the study area that are important corridors in the current landscape that remain intact across the climate change scenarios.     

Tracking climate change in a dispersal-limited species: reduced spatial and genetic connectivity in a montane salamander

Tropical montane taxa are often locally adapted to very specific climatic conditions, contributing to their lower dispersal potential across complex landscapes. Climate and landscape features in montane regions affect population genetic structure in predictable ways, yet few empirical studies quantify the effects of both factors in shaping genetic structure of montane-adapted taxa. Here, we considered temporal and spatial variability in climate to explain contemporary genetic differentiation between populations of the montane salamander, Pseudoeurycea leprosa. Specifically, we used ecological niche modelling (ENM) and measured spatial connectivity and gene flow (using both mtDNA and microsatellite markers) across extant populations of P. leprosa in the Trans-Mexican Volcanic Belt (TVB). Our results indicate significant spatial and genetic isolation among populations, but we cannot distinguish between isolation by distance over time or current landscape barriers as mechanisms shaping population genetic divergences. Combining ecological niche modelling, spatial connectivity analyses, and historical and contemporary genetic signatures from different classes of genetic markers allows for inference of historical evolutionary processes and predictions of the impacts future climate change will have on the genetic diversity of montane taxa with low dispersal rates. Pseudoeurycea leprosa is one montane species among many endemic to this region and thus is a case study for the continued persistence of spatially and genetically isolated populations in the highly biodiverse TVB of central Mexico.