If FST does not measure neutral genetic differentiation,then comparing it with QST is misleading. Or is it?

The comparison between neutral genetic differentiation (F(ST) ) and quantitative genetic differentiation (Q(ST) ) is commonly used to test for signatures of selection in population divergence. However, there is an ongoing discussion about what F(ST) actually measures, even resulting in some alternative metrics to express neutral genetic differentiation. If there is a problem with F(ST) , this could have repercussions for its comparison with Q(ST) as well. We show that as the mutation rate of the neutral marker increases, F(ST) decreases: a higher within-population heterozygosity (He) yields a lower F(ST) value. However, the same is true for Q(ST) : a higher mutation rate for the underlying QTL also results in a lower Q(ST) estimate. The effect of mutation rate is equivalent in Q(ST) and F(ST) . Hence, the comparison between Q(ST) and F(ST) remains valid, if one uses neutral markers whose mutation rates are not too high compared to those of quantitative traits. Usage of highly variable neutral markers such as hypervariable microsatellites can lead to serious biases and the incorrect inference that divergent selection has acted on populations. Much of the discussion on F(ST) seems to stem from the misunderstanding that it measures the differentiation of populations, whereas it actually measures the fixation of alleles. In their capacity as measures of population differentiation, Hedrick's G'(ST) and Jost's D reach their maximum value of 1 when populations do not share alleles even when there remains variation within populations, which invalidates them for comparisons with Q(ST) .     

Measuring population differentiation using GST or D? A simulation study with microsatellite DNA markers under a finite island model and nonequilibrium conditions

The genetic differentiation of populations is a key parameter in population genetic investigations. Wright's F(ST) (and its relatives such as G(ST) ) has been a standard measure of differentiation. However, the deficiencies of these indexes have been increasingly realized in recent years, leading to some new measures being proposed, such as Jost's D (Molecular Ecology, 2008; 17, 4015). The existence of these new metrics has stimulated considerable debate and induced some confusion on which statistics should be used for estimating population differentiation. Here, we report a simulation study with neutral microsatellite DNA loci under a finite island model to compare the performance of G(ST) and D, particularly under nonequilibrium conditions. Our results suggest that there exist fundamental differences between the two statistics, and neither G(ST) nor D operates satisfactorily in all situations for quantifying differentiation. D is very sensitive to mutation models but G(ST) noticeably less so, which limits D's utility in population parameter estimation and comparisons across genetic markers. Also, the initial heterozygosity of the starting populations has some important effects on both the individual behaviours of G(ST) and D and their relative behaviours in early differentiation, and this effect is much greater for D than G(ST) . In the early stages of differentiation, when initial heterozygosity is relatively low (<0.5, if the number of subpopulations is large), G(ST) increases faster than D; the opposite is true when initial heterozygosity is high. Therefore, the state of the ancestral population appears to have some lasting impacts on population differentiation. In general, G(ST) can measure differentiation fairly well when heterozygosity is low whatever the causes; however, when heterozygosity is high (e.g. as a result of either high mutation rate or high initial heterozygosity) and gene flow is moderate to strong, G(ST) fails to measure differentiation. Interestingly, when population size is not very small (e.g. N ≥ 1000), G(ST) measures differentiation quite linearly with time over a long duration when gene flow is absent or very weak even if mutation rate is not low (e.g. μ = 0.001). In contrast, D, as a differentiation measure, performs rather robustly in all these situations. In practice, both indexes should be calculated and the relative levels of heterozygosities (especially H(S) ) and gene flow taken into account. We suggest that a comparison of the two indexes can generate useful insights into the evolutionary processes that influence population differentiation.     

Assessing population structure: F(ST) and related measures

Although F(ST) is widely used as a measure of population structure, it has been criticized recently because of its dependency on within-population diversity. This dependency can lead to difficulties in interpretation and in the comparison of estimates among species or among loci and has led to the development of two replacement statistics, F'(ST) and D. F'(ST) is the normal F(ST) standardized by the maximum value it can obtain, given the observed within-population diversity. D uses a multiplicative partitioning of diversity, based on the effective number of alleles rather than on the expected heterozygosity. In this study, we review the relationships between the three classes of statistics (F(ST), F'(ST) and D), their estimation and their properties. We illustrate the relationships between the statistics using a data set of estimates from 84 species taken from the last 4 years of Molecular Ecology. As with F(ST), unbiased estimators are available for the two new statistics D and F'(ST). Here, we develop a new unbiased F'(ST) estimator based on G(ST), which we call G'(ST). However, F'(ST) can be calculated using any F(ST) estimator for which the maximum value can be obtained. As all three statistics have their advantages and their drawbacks, we recommend continued use of F(ST) in combination with either F'(ST) or D. In most cases, F'(ST) would be the best choice among the latter two as it is most suited for inferences of the influence of demographic processes such as genetic drift and migration on genetic population structure.     

Microsatellite allele sizes: a simple test to assess their significance on genetic differentiation

The mutation process at microsatellite loci typically occurs at high rates and with stepwise changes in allele sizes, features that may introduce bias when using classical measures of population differentiation based on allele identity (e.g., F(ST), Nei's Ds genetic distance). Allele size-based measures of differentiation, assuming a stepwise mutation process [e.g., Slatkin's R(ST), Goldstein et al.'s (deltamu)(2)], may better reflect differentiation at microsatellite loci, but they suffer high sampling variance. The relative efficiency of allele size- vs. allele identity-based statistics depends on the relative contributions of mutations vs. drift to population differentiation. We present a simple test based on a randomization procedure of allele sizes to determine whether stepwise-like mutations contributed to genetic differentiation. This test can be applied to any microsatellite data set designed to assess population differentiation and can be interpreted as testing whether F(ST) = R(ST). Computer simulations show that the test efficiently identifies which of F(ST) or R(ST) estimates has the lowest mean square error. A significant test, implying that R(ST) performs better than F(ST), is obtained when the mutation rate, mu, for a stepwise mutation process is (a) >/= m in an island model (m being the migration rate among populations) or (b) >/= 1/t in the case of isolated populations (t being the number of generations since population divergence). The test also informs on the efficiency of other statistics used in phylogenetical reconstruction [e.g., Ds and (deltamu)(2)], a nonsignificant test meaning that allele identity-based statistics perform better than allele size-based ones. This test can also provide insights into the evolutionary history of populations, revealing, for example, phylogeographic patterns, as illustrated by applying it on three published data sets.     

A program to compare genetic differentiation statistics across loci using resampling of individuals and loci

Comparisons of genetic differentiation across populations based on different loci can provide insight into the evolutionary patterns acting on various regions of genomes. Here, we develop a program to statistically compare population genetic differentiation statistics (F(ST) or G'(ST) ) calculated from different loci. The program employs a routine that resamples either or both of individuals and loci and calculates a bootstrap confidence interval in the statistics. Resampling individuals is important when fewer than 25 individuals are sampled per population and when confidence intervals are required for individual loci. Resampling loci provides confidence intervals for sets of loci, such as a set presumed to be neutral, but can be anticonservative if fewer than 20 loci are analysed. We demonstrate the program using previously published data on the genetic differentiation at a major histocompatibility complex locus and at microsatellite loci across 10 populations of the guppy (Poecilia reticulata).     

Effects of metapopulation processes on measures of genetic diversity

Many species persist as a metapopulation under a balance between the local extinction of subpopulations or demes and their recolonization through dispersal from occupied patches. Here we review the growing body of literature dealing with the genetic consequences of such population turnover. We focus our attention principally on theoretical studies of a classical metapopulation with a 'finite-island' model of population structure, rather than on 'continent-island' models or 'source-sink' models. In particular, we concern ourselves with the subset of geographically subdivided population models in which it is assumed that all demes are liable to extinction from time to time and that all demes receive immigrants. Early studies of the genetic effects of population turnover focused on population differentiation, such as measured by F(ST). A key advantage of F(ST) over absolute measures of diversity is its relative independence of the mutation process, so that different genes in the same species may be compared. Another advantage is that F(ST) will usually equilibrate more quickly following perturbations than will absolute levels of diversity. However, because F(ST) is a ratio of between-population differentiation to total diversity, the genetic effects of metapopulation processes may be difficult to interpret in terms of F(ST) on its own, so that the analysis of absolute measures of diversity in addition is likely to be informative. While population turnover may either increase or decrease F(ST), depending on the mode of colonization, recurrent extinction and recolonization is expected always to reduce levels of both within-population and species-wide diversity (piS and piT, respectively). One corollary of this is that piS cannot be used as an unbiased estimate of the scaled mutation rate, theta, as it can, with some assumptions about the migration process, in species whose demes do not fluctuate in size. The reduction of piT in response to population turnover reflects shortened mean coalescent times, although the distribution of coalescence times under extinction colonization equilibrium is not yet known. Finally, we review current understanding of the effect of metapopulation dynamics on the effective population size.     

Comparisons between QST and FST—how wrong have we been?

The comparison between quantitative genetic divergence (Q(ST) ) and neutral genetic divergence (F(ST) ) among populations has become the standard test for historical signatures of selection on quantitative traits. However, when the mutation rate of neutral markers is relatively high in comparison with gene flow, estimates of F(ST) will decrease, resulting in upwardly biased comparisons of Q(ST) vs. F(ST) . Reviewing empirical studies, the difference between Q(ST) and F(ST) is positively related to marker heterozygosity. After refuting alternative explanations for this pattern, we conclude that marker mutation rate indeed has had a biasing effect on published Q(ST) -F(ST) comparisons. Hence, it is no longer clear that populations have commonly diverged in response to divergent selection. We present and discuss potential solutions to this bias. Comparing Q(ST) with recent indices of neutral divergence that statistically correct for marker heterozygosity (Hedrick's G'st and Jost's D) is not advised, because these indices are not theoretically equivalent to Q(ST) . One valid solution is to estimate F(ST) from neutral markers with mutation rates comparable to those of the loci underlying quantitative traits (e.g. SNPs). Q(ST) can also be compared to Φ(ST) (Phi(ST) ) of amova, as long as the genetic distance among allelic variants used to estimate Φ(ST) reflects evolutionary history: in that case, neutral divergence is independent of mutation rate. In contrast to their common usage in comparisons of Q(ST) and F(ST) , microsatellites typically have high mutation rates and do not evolve according to a simple evolutionary model, so are best avoided in Q(ST) -F(ST) comparisons.     

Relationships between migration rates and landscape resistance assessed using individual-based simulations

Linking landscape effects on gene flow to processes such as dispersal and mating is essential to provide a conceptual foundation for landscape genetics. It is particularly important to determine how classical population genetic models relate to recent individual-based landscape genetic models when assessing individual movement and its influence on population genetic structure. We used classical Wright-Fisher models and spatially explicit, individual-based, landscape genetic models to simulate gene flow via dispersal and mating in a series of landscapes representing two patches of habitat separated by a barrier. We developed a mathematical formula that predicts the relationship between barrier strength (i.e., permeability) and the migration rate (m) across the barrier, thereby linking spatially explicit landscape genetics to classical population genetics theory. We then assessed the reliability of the function by obtaining population genetics parameters (m, F(ST) ) using simulations for both spatially explicit and Wright-Fisher simulation models for a range of gene flow rates. Next, we show that relaxing some of the assumptions of the Wright-Fisher model can substantially change population substructure (i.e., F(ST) ). For example, isolation by distance among individuals on each side of a barrier maintains an F(ST) of ～0.20 regardless of migration rate across the barrier, whereas panmixia on each side of the barrier results in an F(ST) that changes with m as predicted by classical population genetics theory. We suggest that individual-based, spatially explicit modelling provides a general framework to investigate how interactions between movement and landscape resistance drive population genetic patterns and connectivity across complex landscapes.     

Patterns of differentiation in a colour polymorphism and in neutral markers reveal rapid genetic changes in natural damselfly populations

The existence and mode of selection operating on heritable adaptive traits can be inferred by comparing population differentiation in neutral genetic variation between populations (often using F(ST) values) with the corresponding estimates for adaptive traits. Such comparisons indicate if selection acts in a diversifying way between populations, in which case differentiation in selected traits is expected to exceed differentiation in neutral markers [F(ST )(selected) > F(ST )(neutral)], or if negative frequency-dependent selection maintains genetic polymorphisms and pulls populations towards a common stable equilibrium [F(ST) (selected) < F(ST) (neutral)]. Here, we compared F(ST) values for putatively neutral data (obtained using amplified fragment length polymorphism) with estimates of differentiation in morph frequencies in the colour-polymorphic damselfly Ischnura elegans. We found that in the first year (2000), population differentiation in morph frequencies was significantly greater than differentiation in neutral loci, while in 2002 (only 2 years and 2 generations later), population differentiation in morph frequencies had decreased to a level significantly lower than differentiation in neutral loci. Genetic drift as an explanation for population differentiation in morph frequencies could thus be rejected in both years. These results indicate that the type and/or strength of selection on morph frequencies in this system can change substantially between years. We suggest that an approach to a common equilibrium morph frequency across all populations, driven by negative frequency-dependent selection, is the cause of these temporal changes. We conclude that inferences about selection obtained by comparing F(ST) values from neutral and adaptive genetic variation are most useful when spatial and temporal data are available from several populations and time points and when such information is combined with other ecological sources of data.     

Population structure within and between subspecies of the Mediterranean triplefin fish Tripterygion delaisi revealed by highly polymorphic microsatellite loci

Although F(ST) values are widely used to elucidate population relationships, in some cases, when employing highly polymorphic loci, they should be regarded with caution, particularly when subspecies are under consideration. Tripterygion delaisi presents two subspecies that were investigated here, using 10 microsatellite loci. A Bayesian approach allowed us to clearly identify both subspecies as two different evolutionary significant units. However, low F(ST) values were found between subspecies as a consequence of the large number of alleles per locus, while homoplasy could be disregarded as indicated by the standardized genetic distance G'(ST). Heterozygosity saturation was observed in highly polymorphic loci containing more than 15 alleles, and this threshold was used to define two loci pools. The less variable loci pool revealed higher genetic variance between subspecies, while the more variable pool showed higher genetic variance between populations. Furthermore, higher differentiation was also observed between populations using G'(ST) with the more variable loci. Nonetheless, a more reliable population structure within subspecies was obtained when all loci were included in the analyses. In T. d. xanthosoma, isolation by distance was detected between the eight analysed populations, and six genetically homogeneous clusters were inferred by Bayesian analyses that are in accordance with F(ST) values. The neighbourhood-size method also indicated rather small dispersal capabilities. In conclusion, in fish with limited adult and larval dispersal capabilities, continuous rocky habitat seems to allow contact between populations and prevent genetic differentiation, while large discontinuities of sand or deep-water channels seems to reduce gene flow.     

Statistical properties of population differentiation estimators under stepwise mutation in a finite island model

Microsatellite loci mutate at an extremely high rate and are generally thought to evolve through a stepwise mutation model. Several differentiation statistics taking into account the particular mutation scheme of the microsatellite have been proposed. The most commonly used is R(ST) which is independent of the mutation rate under a generalized stepwise mutation model. F(ST) and R(ST) are commonly reported in the literature, but often differ widely. Here we compare their statistical performances using individual-based simulations of a finite island model. The simulations were run under different levels of gene flow, mutation rates, population number and sizes. In addition to the per locus statistical properties, we compare two ways of combining R(ST) over loci. Our simulations show that even under a strict stepwise mutation model, no statistic is best overall. All estimators suffer to different extents from large bias and variance. While R(ST) better reflects population differentiation in populations characterized by very low gene-exchange, F(ST) gives better estimates in cases of high levels of gene flow. The number of loci sampled (12, 24, or 96) has only a minor effect on the relative performance of the estimators under study. For all estimators there is a striking effect of the number of samples, with the differentiation estimates showing very odd distributions for two samples.     

Theoretical limits to the correlation between pelagic larval duration and population genetic structure

Increasing dispersal duration should result in increasing dispersal distance, facilitating higher gene flow among populations. As such, it has long been predicted that genetic structure (e.g. F(ST) ) among populations of marine species should be strongly correlated with pelagic larval duration (PLD). However, previous studies have repeatedly shown a surprisingly poor correspondence. This result has been frequently interpreted as evidence for larval behaviours or physical oceanographic processes that result in larvae failing to reach their dispersal potential, or error inherent in estimating PLD and F(ST) . This study employed a computer modelling approach to explore the impacts of various uncertainties on the correlation between measures of genetic differentiation such as F(ST) and PLD. Results indicate that variation resulting from PLD estimation error had minor impacts on the correlation between genetic structure and PLD. However, variation in effective population size between species, errors in F(ST) estimation and non-equilibrium F(ST) values all had major impacts, resulting in dramatically weaker correlations between PLD and F(ST) . These results suggest that poor correlations between PLD and F(ST) may result from variation and uncertainty in the terms associated with the calculation of F(ST) values. As such, PLD may be a much stronger determinant of realized larval dispersal than suggested by the weak-to-moderate correlations between PLD and F(ST) reported in empirical studies.     

Inference of selection based on temporal genetic differentiation in the study of highly polymorphic multigene families

The co-evolutionary arms race between host immune genes and parasite virulence genes is known as Red Queen dynamics. Temporal fluctuations in allele frequencies, or the 'turnover' of alleles at immune genes, are concordant with predictions of the Red Queen hypothesis. Such observations are often taken as evidence of host-parasite co-evolution. Here, we use computer simulations of the Major Histocompatibility Complex (MHC) of guppies (Poecilia reticulata) to study the turnover rate of alleles (temporal genetic differentiation, G'(ST)). Temporal fluctuations in MHC allele frequencies can be ≥≤order of magnitude larger than changes observed at neutral loci. Although such large fluctuations in the MHC are consistent with Red Queen dynamics, simulations show that other demographic and population genetic processes can account for this observation, these include: (1) overdominant selection, (2) fluctuating population size within a metapopulation, and (3) the number of novel MHC alleles introduced by immigrants when there are multiple duplicated genes. Synergy between these forces combined with migration rate and the effective population size can drive the rapid turnover in MHC alleles. We posit that rapid allelic turnover is an inherent property of highly polymorphic multigene families and that it cannot be taken as evidence of Red Queen dynamics. Furthermore, combining temporal samples in spatial F(ST) outlier analysis may obscure the signal of selection.     

Population genetics of complex life-cycle parasites: an illustration with trematodes

Accurate inferences on population genetics data require a sound underlying theoretical null model. Organisms alternating sexual and asexual reproduction during their life-cycle have been largely neglected in theoretical population genetic models, thus limiting the biological interpretation of population genetics parameters measured in natural populations. In this article, we derive the expectations of those parameters for the life-cycle of monoecious trematodes, a group comprising several important human and livestock parasites that obligatorily alternate sexual and asexual reproduction during their life-cycle. We model how migration rates between hosts, sexual and asexual mutation rates, adult selfing rate and the variance in reproductive success of parasites during the clonal phase affect the amount of neutral genetic diversity of the parasite (effective population size) and its apportionment within and between definitive hosts (using F-statistics). We demonstrate, in particular, that variance in reproductive success of clones, a parameter that has been completely overlooked in previous population genetics models, is very important in shaping the distribution of the genetic variability both within and among definitive hosts. Within definitive hosts, the parameter F(IS) (a measure of the deviation from random mating) is decreased by high variance in clonal reproductive success of larvae but increased by high adult self-fertilisation rates. Both clonal multiplication and selfing have similar effects on between-host genetic differentiation (F(ST)). Migration occurring before and after asexual reproduction can have different effects on the patterns of F(IS), depending on values of the other parameters such as the mutation rate. While the model applies to any hermaphroditic organism alternating sexual and clonal reproduction (e.g. many plants), the results are specifically discussed in the light of the limited population genetic data on monoecious trematodes available to date and their previous interpretation. We hope that our model will encourage more empirical population genetics studies on monoecious trematodes and other organisms with similar life-cycles.     

Microsatellite null alleles and estimation of population differentiation

Microsatellite null alleles are commonly encountered in population genetics studies, yet little is known about their impact on the estimation of population differentiation. Computer simulations based on the coalescent were used to investigate the evolutionary dynamics of null alleles, their impact on F(ST) and genetic distances, and the efficiency of estimators of null allele frequency. Further, we explored how the existing method for correcting genotype data for null alleles performed in estimating F(ST) and genetic distances, and we compared this method with a new method proposed here (for F(ST) only). Null alleles were likely to be encountered in populations with a large effective size, with an unusually high mutation rate in the flanking regions, and that have diverged from the population from which the cloned allele state was drawn and the primers designed. When populations were significantly differentiated, F(ST) and genetic distances were overestimated in the presence of null alleles. Frequency of null alleles was estimated precisely with the algorithm presented in Dempster et al. (1977). The conventional method for correcting genotype data for null alleles did not provide an accurate estimate of F(ST) and genetic distances. However, the use of the genetic distance of Cavalli-Sforza and Edwards (1967) corrected by the conventional method gave better estimates than those obtained without correction. F(ST) estimation from corrected genotype frequencies performed well when restricted to visible allele sizes. Both the proposed method and the traditional correction method have been implemented in a program that is available free of charge at http://www.montpellier.inra.fr/URLB/. We used 2 published microsatellite data sets based on original and redesigned pairs of primers to empirically confirm our simulation results.     

Differential threshold effects of habitat fragmentation on gene flow in two widespread species of bush crickets

Effects of habitat fragmentation on genetic diversity vary among species. This may be attributed to the interacting effects of species traits and landscape structure. While widely distributed and abundant species are often considered less susceptible to fragmentation, this may be different if they are small sized and show limited dispersal. Under intensive land use, habitat fragmentation may reach thresholds at which gene flow among populations of small-sized and dispersal-limited species becomes disrupted. Here, we studied the genetic diversity of two abundant and widespread bush crickets along a gradient of habitat fragmentation in an agricultural landscape. We applied traditional (G(ST), θ) and recently developed (G'ST', D) estimators of genetic differentiation on microsatellite data from each of twelve populations of the grassland species Metrioptera roeselii and the forest-edge species Pholidoptera griseoaptera to identify thresholds of habitat fragmentation below which genetic population structure is affected. Whereas the grassland species exhibited a uniform genetic structuring (G(ST) = 0.020-0.033; D = 0.085-0.149) along the whole fragmentation gradient, the forest-edge species' genetic differentiation increased significantly from D < 0.063 (G(ST) < 0.018) to D = 0.166 (G(ST) = 0.074), once the amount of suitable habitat dropped below a threshold of 20% and its proximity decreased substantially at the landscape scale. The influence of fragmentation on genetic differentiation was qualitatively unaffected by the choice of estimators of genetic differentiation but quantitatively underestimated by the traditional estimators. These results indicate that even for widespread species in modern agricultural landscapes fragmentation thresholds exist at which gene flow among suitable habitat patches becomes restricted.     

Molecular and quantitative genetic differentiation across Europe in yellow dung flies

Relating geographic variation in quantitative traits to underlying population structure is crucial for understanding processes driving population differentiation, isolation and ultimately speciation. Our study represents a comprehensive population genetic survey of the yellow dung fly Scathophaga stercoraria, an important model organism for evolutionary and ecological studies, over a broad geographic scale across Europe (10 populations from the Swiss Alps to Iceland). We simultaneously assessed differentiation in five quantitative traits (body size, development time, growth rate, proportion of diapausing individuals and duration of diapause), to compare differentiation in neutral marker loci (F(ST)) to that of quantitative traits (Q(ST)). Despite long distances and uninhabitable areas between sampled populations, population structuring was very low but significant (F(ST) = 0.007, 13 microsatellite markers; F(ST) = 0.012, three allozyme markers; F(ST) = 0.007, markers combined). However, only two populations (Iceland and Sweden) showed significant allelic differentiation to all other populations. We estimated high levels of gene flow [effective number of migrants (Nm) = 6.2], there was no isolation by distance, and no indication of past genetic bottlenecks (i.e. founder events) and associated loss of genetic diversity in any northern or island population. In contrast to the low population structure, quantitative traits were strongly genetically differentiated among populations, following latitudinal clines, suggesting that selection is responsible for life history differentiation in yellow dung flies across Europe.     

Patterns of genetic diversity and migration in increasingly fragmented and declining orang-utan (Pongo pygmaeus) populations from Sabah, Malaysia

We investigated the genetic structure within and among Bornean orang-utans (Pongo pygmaeus) in forest fragments of the Lower Kinabatangan flood plain in Sabah, Malaysia. DNA was extracted from hair and faecal samples for 200 wild individuals collected during boat surveys on the Kinabatangan River. Fourteen microsatellite loci were used to characterize patterns of genetic diversity. We found that genetic diversity was high in the set of samples (mean H(E) = 0.74) and that genetic differentiation was significant between the samples (average F(ST) = 0.04, P < 0.001) with F(ST) values ranging from low (0.01) to moderately large (0.12) values. Pairwise F(ST) values were significantly higher across the Kinabatangan River than between samples from the same river side, thereby confirming the role of the river as a natural barrier to gene flow. The correlation between genetic and geographical distance was tested by means of a series of Mantel tests based on different measures of geographical distance. We used a Bayesian method to estimate immigration rates. The results indicate that migration is unlikely across the river but cannot be completely ruled out because of the limited F(ST) values. Assignment tests confirm the overall picture that gene flow is limited across the river. We found that migration between samples from the same side of the river had a high probability indicating that orang-utans used to move relatively freely between neighbouring areas. This strongly suggests that there is a need to maintain migration between isolated forest fragments. This could be done by restoring forest corridors alongside the river banks and between patches.     

Equilibrium between genetic drift and migration at various mutation rates: simulation analysis

Rates of approach to equilibrium values of F(ST)/R(ST) at various mutation rates and using different mutation models (K-allele model KAM and stepwise model SMM) were analyzed numerically for the finite island model and the one-dimensional stepping stone models of migration, using simulation. In the island model of migration and the KAM mutation model, the rate of approach to the equilibrium F(ST) value was appreciably higher and the equilibrium value was almost twofold lower at micro (mutation rate) = m (migration rate) than at micro < m. In the one-dimensional stepping stone model of migration and the KAM model of mutation, the mutation rate significantly affected both the rate of approaching F(ST) equilibrium and the equilibrium value. In both island and one-dimensional stepping stone models and SMM, R(ST) was not influenced by various mutation rates. The rate of approach to the equilibrium values of both F(ST) and R(ST) was lower for the stepping stone model than to the island model. RST was rather resistant to deviations from the SMM mutation model.     

Genetic structure in the coral-reef-associated Banggai cardinalfish, Pterapogon kauderni

In this study, we used 11 polymorphic microsatellite loci to show that oceanic distances as small as 2-5 km are sufficient to produce high levels of population genetic structure (multilocus F(ST) as high as 0.22) in the Banggai cardinalfish (Pterapogon kauderni), a heavily exploited reef fish lacking a pelagic larval dispersal phase. Global F(ST) among all populations, separated by a maximum distance of 203 km, was 0.18 (R(ST) = 0.35). Moreover, two lines of evidence suggest that estimates of F(ST) may actually underestimate the true level of genetic structure. First, within-locus F(ST) values were consistently close to the theoretical maximum set by the average within-population heterozygosity. Second, the allele size permutation test showed that R(ST) values were significantly larger than F(ST) values, indicating that populations have been isolated long enough for mutation to have played a role in generating allelic variation among populations. The high level of microspatial structure observed in this marine fish indicates that life history traits such as lack of pelagic larval phase and a good homing ability do indeed play a role in shaping population genetic structure in the marine realm.