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.     

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 slope and riparian habitat connectivity on gene flow in an endangered Panamanian frog, Atelopus varius

Aim Understanding how heterogeneous landscapes shape genetic structure not only sheds light on processes involved in population divergence and speciation, but can also guide management strategies to promote and maintain genetic connectivity of populations of endangered species. This study aimed to (1) identify barriers and corridors for gene flow among populations of the endangered frog, Atelopus varius and (2) assess the relative contributions of alternative landscape factors to patterns of genetic variation among these populations in a hypothesis testing framework. Location This study took place in western Panama and included all nine of the remaining known populations of A. varius at the time of study. Methods The influence of landscape variables on gene flow among populations was examined by testing for correlations between alternative landscape‐resistance scenarios and genetic distance. Fifteen alternative hypotheses about the influence of (1) riparian habitat corridors, (2) steep slopes, and (3) climatic suitability on patterns of genetic structure were tested in a causal modelling framework, using Mantel and partial‐Mantel tests, along with an analysis of molecular variation. Results Only the hypothesis attributing resistance to dispersal across steep slopes (genetic isolation by slope distance) was fully supported by the causal modelling approach. However, the analysis of molecular variance and the paths of least‐slope among populations suggest that riparian habitat connectivity may influence genetic structure as well. Main conclusions These results suggest that patterns of genetic variation among A. varius populations are affected by the slope of the landscape such that areas with steep slopes act as barriers to gene flow. In contrast, areas of low slope, such as streams and mountain ridges, appear to be important corridors for gene flow, especially among high elevation populations. These results engender important considerations for the management of this critically endangered species.     

Landscape resistance and habitat combine to provide an optimal model of genetic structure and connectivity at the range margin of a small mammal

We evaluated the effect of habitat and landscape characteristics on the population genetic structure of the white‐footed mouse. We develop a new approach that uses numerical optimization to define a model that combines site differences and landscape resistance to explain the genetic differentiation between mouse populations inhabiting forest patches in southern Québec. We used ecological distance computed from resistance surfaces with Circuitscape to infer the effect of the landscape matrix on gene flow. We calculated site differences using a site index of habitat characteristics. A model that combined site differences and resistance distances explained a high proportion of the variance in genetic differentiation and outperformed models that used geographical distance alone. Urban and agriculture‐related land uses were, respectively, the most and the least resistant landscape features influencing gene flow. Our method detected the effect of rivers and highways as highly resistant linear barriers. The density of grass and shrubs on the ground best explained the variation in the site index of habitat characteristics. Our model indicates that movement of white‐footed mouse in this region is constrained along routes of low resistance. Our approach can generate models that may improve predictions of future northward range expansion of this small mammal.     

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

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

Geographic variation of flower traits in Narcissus papyraceus (Amaryllidaceae): do pollinators matter?

Aim The geographic clinal variation of traits in organisms can indicate the possible causes of phenotypic evolution. We studied the correlates of flower trait variation in populations of a style‐dimorphic plant, Narcissus papyraceus Ker‐Gawl., within a region of high biogeographical significance, the Strait of Gibraltar. This species shows a geographic gradient in the style‐morph ratio, suggested to be driven by pollinator shifts. We tested whether parallel geographic variation of perianth traits also exists, concomitant with vegetative trait variation or genetic similarity of plant populations. Location The Strait of Gibraltar region (SG hereafter, including both south‐western Iberian Peninsula and north‐western Morocco). Methods We used univariate and multivariate analyses of flower and vegetative traits in 23 populations. We applied Mantel tests and partial Mantel correlations on vegetative and flower traits and geographic locations of populations to test for spatial effects. We used Moran’s autocorrelation analyses to explore the spatial structure within the range, and performed the analyses with and without the Moroccan samples to test for the effects of the SG on spatial patterns. Amplified fragment length polymorphism data were used to estimate the genetic distance between populations and to ascertain its relationship with morphometric distance. Results There was high variation between and within populations in both flower and vegetative traits. Mantel correlations between geographic and morphometric distances were not significant, but the exclusion of Moroccan populations revealed some distance effect. Partial Mantel correlation did not detect a significant correlation between flower and vegetative morphometric distances after controlling for geographic distance. There were opposite trends in spatial autocorrelograms of flower and vegetative traits. The genetic distance between pairs of populations was directly correlated with geographic distance; however, flower morphometric and genetic distances were not significantly correlated. Main conclusions The SG had some influence on phenotypes, although the causes remain to be determined. The opposite trend of variation in flower and vegetative traits, and the lack of correlation between genetic distance and dissimilarity of flower phenotypes favour the hypothesis of pollinator‐mediated selection on flower morphology, although this may affect only particular traits and populations rather than overall phenotypes. Although stochastic population processes may have a small effect, other factors may account for the high flower variation within and between populations.     

Habitat fragmentation in coastal southern California disrupts genetic connectivity in the cactus wren (Campylorhynchus brunneicapillus)

Achieving long‐term persistence of species in urbanized landscapes requires characterizing population genetic structure to understand and manage the effects of anthropogenic disturbance on connectivity. Urbanization over the past century in coastal southern California has caused both precipitous loss of coastal sage scrub habitat and declines in populations of the cactus wren (Campylorhynchus brunneicapillus). Using 22 microsatellite loci, we found that remnant cactus wren aggregations in coastal southern California comprised 20 populations based on strict exact tests for population differentiation, and 12 genetic clusters with hierarchical Bayesian clustering analyses. Genetic structure patterns largely mirrored underlying habitat availability, with cluster and population boundaries coinciding with fragmentation caused primarily by urbanization. Using a habitat model we developed, we detected stronger associations between habitat‐based distances and genetic distances than Euclidean geographic distance. Within populations, we detected a positive association between available local habitat and allelic richness and a negative association with relatedness. Isolation‐by‐distance patterns varied over the study area, which we attribute to temporal differences in anthropogenic landscape development. We also found that genetic bottleneck signals were associated with wildfire frequency. These results indicate that habitat fragmentation and alterations have reduced genetic connectivity and diversity of cactus wren populations in coastal southern California. Management efforts focused on improving connectivity among remaining populations may help to ensure population persistence.     

Landscape heterogeneity predicts gene flow in a widespread polymorphic bumble bee, Bombus bifarius (Hymenoptera: Apidae)

Bombus bifarius is a widespread bumble bee that occurs in montane regions of western North America. This species has several major color pattern polymorphisms and shows evidence of genetic structuring among regional populations, and the taxonomic status of regional populations has repeatedly been debated. We test whether observed structure is evidence for discrete gene flow barriers that might indicate isolation or instead reflects clinal variation associated with spatially limited dispersal in a complex landscape. We first consider color pattern variation and identify geographical patterns of B. bifarius color variation using cluster analysis. We then use climate data and a comprehensive set of B. bifarius natural history records with an existing genetic data set to model the distribution of environmentally suitable habitat in western North America and predict pathways of potential gene flow using circuit theory. Resistance distances among populations that incorporate environmental suitability information predict patterns of genetic structure much better than geographic distance or Bayesian clustering alone. Results suggest that there may not be barriers to gene flow warranting further taxonomic considerations, but rather that the arrangement of suitable habitat at broad scales limits dispersal sufficiently to explain observed levels of population differentiation in B. bifarius.     

Dispersal ability and habitat requirements determine landscape‐level genetic patterns in desert aquatic insects

Species occupying the same geographic range can exhibit remarkably different population structures across the landscape, ranging from highly diversified to panmictic. Given limitations on collecting population‐level data for large numbers of species, ecologists seek to identify proximate organismal traits—such as dispersal ability, habitat preference and life history—that are strong predictors of realized population structure. We examined how dispersal ability and habitat structure affect the regional balance of gene flow and genetic drift within three aquatic insects that represent the range of dispersal abilities and habitat requirements observed in desert stream insect communities. For each species, we tested for linear relationships between genetic distances and geographic distances using Euclidean and landscape‐based metrics of resistance. We found that the moderate‐disperser Mesocapnia arizonensis (Plecoptera: Capniidae) has a strong isolation‐by‐distance pattern, suggesting migration–drift equilibrium. By contrast, population structure in the flightless Abedus herberti (Hemiptera: Belostomatidae) is influenced by genetic drift, while gene flow is the dominant force in the strong‐flying Boreonectes aequinoctialis (Coleoptera: Dytiscidae). The best‐fitting landscape model for M. arizonensis was based on Euclidean distance. Analyses also identified a strong spatial scale‐dependence, where landscape genetic methods only performed well for species that were intermediate in dispersal ability. Our results highlight the fact that when either gene flow or genetic drift dominates in shaping population structure, no detectable relationship between genetic and geographic distances is expected at certain spatial scales. This study provides insight into how gene flow and drift interact at the regional scale for these insects as well as the organisms that share similar habitats and dispersal abilities.     

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.     

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.     

Micro-spatial genetic structure in song sparrows (<Emphasis Type="Italic">Melospiza melodia</Emphasis>)

The spatial genetic structure of populations is strongly influenced by current and historical patterns of gene flow and drift, which in the simplest case, is limited by geographic distance. We examined the microspatial genetic structure within 33 populations of song sparrows (Melospiza melodia) which included eight subspecies located across coastal areas in southern British Columbia (BC) and California. We also examined the effect of water barriers and local density estimates on genetic structuring. Across both regions, positive genetic structure was detectable at distances of less than 10 km. Genetic divergence was highest in Californian subspecies, perhaps due to reduced gene flow across sub-specific contact zones. In BC, populations distributed across islands displayed greater genetic structuring over similar spatial scales than those across mainland sites, supporting the prediction that water barriers reduce gene flow in this species. Our results confirm both the expectation for fine-scale genetic structure in these generally sedentary subspecies, and the role of landscape features in generating geographic variation in genetic structure.     

Resistance is futile: effects of landscape features on gene flow of the northern bobwhite

Habitat for the northern bobwhite (Colinus virginianus) has declined and changed drastically in spatial structure throughout the last century. Undoubtedly such changes have impacted bobwhite and may have altered their ability to access available habitat. We investigated whether landscape resistance, geographic distance, or interstate highway barriers were related to dispersal and gene flow of bobwhite in central and southern Illinois. Landscape resistance was determined from two empirically informed models depicting habitat suitability for bobwhite. During 2007–2008, hunters submitted bobwhite tissue samples from which we amplified 11 microsatellites. The relationship between individual genetic distances and spatial variables was analyzed with Mantel tests and causal modeling was used to verify the spatial variables influencing gene flow. Genetic distance was correlated with geographic distance but showed no relationship with interstate highway barriers. Habitat suitability did not enhance gene flow, and was inversely related in some partial Mantel tests. We suggest that bobwhite dispersal from suitable habitat patches may be less frequent than from suboptimal habitats. Bobwhite may be able to access suitable habitat across gaps of unsuitable habitat but distance limits their dispersal. Because available habitat for bobwhites may have a greater likelihood of being colonized when closer to occupied habitat, we suggest that lands closer to occupied habitat should be targeted for conservation or habitat improvement efforts.     

Genetic differentiation in relation to marine landscape in a broadcast-spawning bivalve mollusc (Placopecten magellanicus)

Marine bivalves are sessile or sedentary as adults but have planktonic larvae which can potentially disperse over large distances. Consequently larval transport is expected to play a prominent role in facilitating gene flow and determining population structure. The sea scallop (Placopecten magellanicus) is a dioecious species with high fecundity, broadcast spawning and a c. 30-day planktonic larval stage, yet it forms discrete populations or 'beds' which have significantly different dynamics and characteristics. We analysed variation at six microsatellite loci in 12 locations throughout the geographic range of the species from Newfoundland, Canada, to New Jersey, USA. Significant differentiation was present and the maximum pairwise theta value, between one of the Newfoundland samples in the north and a sample from the southern portion of the range, was high at 0.061. Other proximate pairs of samples had no detectable genetic differentiation. Mantel tests indicated a significant isolation by distance, but only when one of the populations was excluded. A landscape genetic approach was used to detect areas of low gene flow using a joint analysis of spatial and genetic information. The two major putative barriers inferred by Monmonier's algorithm were then used to define regions for an analysis of molecular variance (amova). That analysis showed a significant but low percentage (1.2%) of the variation to be partitioned among regions, negligible variation among populations within regions, and the majority of the variance distributed between individuals within populations. Prominent currents were concordant with the demarcation of the regions, while a novel approach of using particle tracking software to mimic scallop larval dispersal was employed to interpret within-region genetic patterns.     

Streams over mountains: influence of riparian connectivity on gene flow in the Pacific jumping mouse (Zapus trinotatus)

In species affiliated with heterogeneous habitat, we expect gene flow to be restricted due to constraints placed on individual movement by habitat boundaries. This is likely to impact both individual dispersal and connectivity between populations. In this study, a GIS-based landscape genetics approach was used, in combination with fine-scale spatial autocorrelation analysis and the estimation of recent intersubpopulation migration rates, to infer patterns of dispersal and migration in the riparian-affiliated Pacific jumping mouse (Zapus trinotatus). A total of 228 individuals were sampled from nine subpopulations across a system of three rivers and genotyped at eight microsatellite loci. Significant spatial autocorrelation among individuals revealed a pattern of fine-scale spatial genetic structure indicative of limited dispersal. Geographical distances between pairwise subpopulations were defined following four criteria: (i) Euclidean distance, and three landscape-specific distances, (ii) river distance (distance travelled along the river only), (iii) overland distance (similar to Euclidean, but includes elevation), and (iv) habitat-path distance (a least-cost path distance that models movement along habitat pathways). Pairwise Mantel tests were used to test for a correlation between genetic distance and each of the geographical distances. Significant correlations were found between genetic distance and both the overland and habitat-path distances; however, the correlation with habitat-path distance was stronger. Lastly, estimates of recent migration rates revealed that migration occurs not only within drainages but also across large topographic barriers. These results suggest that patterns of dispersal and migration in Pacific jumping mice are largely determined by habitat connectivity.     

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.     

Quantifying the lag time to detect barriers in landscape genetics

Understanding how spatial genetic patterns respond to landscape change is crucial for advancing the emerging field of landscape genetics. We quantified the number of generations for new landscape barrier signatures to become detectable and for old signatures to disappear after barrier removal. We used spatially explicit, individual‐based simulations to examine the ability of an individual‐based statistic [Mantel’s r using the proportion of shared alleles’ statistic (Dps)] and population‐based statistic (F_ST) to detect barriers. We simulated a range of movement strategies including nearest neighbour dispersal, long‐distance dispersal and panmixia. The lag time for the signal of a new barrier to become established is short using Mantel’s r (1–15 generations). F_ST required approximately 200 generations to reach 50% of its equilibrium maximum, although G’_ST performed much like Mantel’s r. In strong contrast, F_ST and Mantel’s r perform similarly following the removal of a barrier formerly dividing a population. Also, given neighbour mating and very short‐distance dispersal strategies, historical discontinuities from more than 100 generations ago might still be detectable with either method. This suggests that historical events and landscapes could have long‐term effects that confound inferences about the impacts of current landscape features on gene flow for species with very little long‐distance dispersal. Nonetheless, populations of organisms with relatively large dispersal distances will lose the signal of a former barrier within less than 15 generations, suggesting that individual‐based landscape genetic approaches can improve our ability to measure effects of existing landscape features on genetic structure and connectivity.     

Low genetic diversity and local adaptive divergence of Dracaena cambodiana (Liliaceae) populations associated with historical population bottlenecks and natural selection: an endangered long‐lived tree endemic to Hainan Island,China

Historical population bottlenecks and natural selection have important effects on the current genetic diversity and structure of long‐lived trees. Dracaena cambodiana is an endangered, long‐lived tree endemic to Hainan Island, China. Our field investigations showed that only 10 populations remain on Hainan Island and that almost all have been seriously isolated and grow in distinct habitats. A considerable amount of genetic variation at the species level, but little variation at the population level, and a high level of genetic differentiation among the populations with limited gene flow in D. cambodiana were detected using inter‐simple sequence repeat (ISSR) and random amplified polymorphic DNA (RAPD) analyses. No significant correlation was found between genetic diversity and actual population size, as the genetic diversities were similar regardless of population size. The Mantel test revealed that there was no correlation between genetic and geographic distances among the 10 populations. The UPGMA, PCoA and Bayesian analyses showed that local adaptive divergence has occurred among the D. cambodiana populations, which was further supported by habitat‐private fragments. We suggest that the current genetic diversity and population differentiation of D. cambodiana resulted from historical population bottlenecks and natural selection followed by historical isolation. However, the lack of natural regeneration of D. cambodiana indicates that former local adaptations with low genetic diversity may have been genetically weak and are unable to adapt to the current ecological environments.