New interpretations of fine-scale spatial genetic structure

Recent methodological advances permit refined inferences of evolutionary processes from the fine-scale spatial genetic structure of plant populations. In this issue of Molecular Ecology, Born et al. (2008) exploit the full power of these methods by examining effects of ancient and recent landscape histories in an African rainforest tree species. The authors first detected admixture of distinct gene pools that may have formed in Pleistocene forest refuges. Then, comparing across six study populations in Gabon, the authors found similar patterns of fine-scale spatial genetic structure despite natural and anthropogenic variation in population density. The latter results suggest that enhanced gene dispersal may compensate for low population densities in fragmented landscapes.     

A heterogeneity test for fine-scale genetic structure

For organisms with limited vagility and/or occupying patchy habitats, we often encounter nonrandom patterns of genetic affinity over relatively small spatial scales, labelled fine-scale genetic structure. Both the extent and decay rate of that pattern can be expected to depend on numerous interesting demographic, ecological, historical, and mating system factors, and it would be useful to be able to compare different situations. There is, however, no heterogeneity test currently available for fine-scale genetic structure that would provide us with any guidance on whether the differences we encounter are statistically credible. Here, we develop a general nonparametric heterogeneity test, elaborating on standard autocorrelation methods for pairs of individuals. We first develop a 'pooled within-population' correlogram, where the distance classes (lags) can be defined as functions of distance. Using that pooled correlogram as our null-hypothesis reference frame, we then develop a heterogeneity test of the autocorrelations among different populations, lag-by-lag. From these single-lag tests, we construct an analogous test of heterogeneity for multilag correlograms. We illustrate with a pair of biological examples, one involving the Australian bush rat, the other involving toadshade trillium. The Australian bush rat has limited vagility, and sometimes occupies patchy habitat. We show that the autocorrelation pattern diverges somewhat between continuous and patchy habitat types. For toadshade trillium, clonal replication in Piedmont populations substantially increases autocorrelation for short lags, but clonal replication is less pronounced in mountain populations. Removal of clonal replicates reduces the autocorrelation for short lags and reverses the sign of the difference between mountain and Piedmont correlograms.     

Effect of sampling strategy on estimation of fine-scale spatial genetic structure in Androsace tapete (Primulaceae), an alpine plant endemic to Qinghai-Tibetan Plateau

The fine-scale spatial genetic structure (SGS) of alpine plants is receiving increasing attention, from which seed and pollen dispersal can be inferred. However, estimation of SGS may depend strongly on the sampling strategy,including the sample size and spatial sampling scheme. Here, we examined the effects of sample size and three spatial schemes, simple-random, line-transect, and random-cluster sampling, on the estimation of SGS in Androsace tapete, an alpine cushion plant endemic to Qinghai-Tibetan Plateau. Using both real data and simulated data of dominant molecular markers, we show that: (i) SGS is highly sensitive to sample strategy especially when the sample size is small (e.g., below 100); (ii) the commonly used SGS parameter (the intercept of the autocorrelogram) is more susceptible to sample error than a newly developed Sp statistic; and (iii) the random-cluster scheme is susceptible to obvious bias in parameter estimation even when the sample size is relatively large (e.g., above 200). Overall,the line-transect scheme is recommendable, in that it performs slightly better than the simple-random scheme in parameter estimation and is more efficient to encompass broad spatial scales. The consistency between simulated data and real data implies that these findings might hold true in other alpine plants and more species should be examined in future work.     

Spatial correlations at different spatial scales are themselves highly correlated in isolation by distance processes

Although many properties of spatial autocorrelation statistics are well characterized, virtually nothing is known about possible correlations among values at different spatial scales, which ultimately would influence how inferences about spatial genetics are made at multiple spatial scales. This article reports the results of stochastic space-time simulations of isolation by distance processes, having a very wide range of amounts of dispersal for plants or animals, and analyses of the correlations among Moran's I-statistics for different mutually exclusive distance classes. In general, the stochastic correlations are extremely large (>0.90); however, the correlations bear a complex relationship with level of dispersal, spatial scale and spatial lag between distance classes. The correlations are so large that any existing or conceived statistical method that employs more than one distance class (or spatial scale) should not ignore them. This result also suggests that gains in statistical power via increasing sample size are limited, and that increasing numbers of assayed loci generally should be preferred. To the extent that sampling error for real data sets can be treated as white noise, it should be possible to account for stochastic correlations in formulating more precise statistical methods. Further, while the current results are for isolation by distance processes, they provide some guidance for some more complex stochastic space-time processes of landscape genetics. Moreover, the results hold for several popular measures other than Moran's I. In addition, in the results, the signal to noise ratios strongly decreased with distance, which also has several implications for optimal statistical methods using correlations at multiple spatial scales.     

Comparative analysis of the within-population genetic structure in wild cherry (Prunus avium L.) at the self-incompatibility locus and nuclear microsatellites

Gametophytic self-incompatibility (SI) systems in plants exhibit high polymorphism at the SI controlling S-locus because individuals with rare alleles have a higher probability to successfully pollinate other plants than individuals with more frequent alleles. This process, referred to as frequency-dependent selection, is expected to shape number, frequency distribution, and spatial distribution of self-incompatibility alleles in natural populations. We investigated the genetic diversity and the spatial genetic structure within a Prunus avium population at two contrasting gene loci: nuclear microsatellites and the S-locus. The S-locus revealed a higher diversity (15 alleles) than the eight microsatellites (4-12 alleles). Although the frequency distribution of S-alleles differed significantly from the expected equal distribution, the S-locus showed a higher evenness than the microsatellites (Shannon's evenness index for the S-locus: E = 0.91; for the microsatellites: E = 0.48-0.83). Also, highly significant deviations from neutrality were found for the S-locus whereas only minor deviations were found for two of eight microsatellites. A comparison of the frequency distribution of S-alleles in three age-cohorts revealed no significant differences, suggesting that different levels of selection acting on the S-locus or on S-linked sites might also affect the distribution and dynamics of S-alleles. Autocorrelation analysis revealed a weak but significant spatial genetic structure for the multilocus average of the microsatellites and for the S-locus, but could not ascertain differences in the extent of spatial genetic structure between these locus types. An indirect estimate of gene dispersal, which was obtained to explain this spatial genetic pattern, indicated high levels of gene dispersal within our population (sigma(g) = 106 m). This high gene dispersal, which may be partly due to the self-incompatibility system itself, aids the effective gene flow of the microsatellites, thereby decreasing the contrast between the neutral microsatellites and the S-locus.     

Analysis of spatial genetic structure in an expanding Pinus halepensis population reveals development of fine-scale genetic clustering over time

We analysed the change of spatial genetic structure (SGS) of reproductive individuals over time in an expanding Pinus halepensis population. To our knowledge, this is the first empirical study to analyse the temporal component of SGS by following the dynamics of successive cohorts of the same population over time, rather than analysing different age cohorts at a single time. SGS is influenced by various factors including restricted gene dispersal, microenvironmental selection, mating patterns and the spatial pattern of reproductive individuals. Several factors that affect SGS are expected to vary over time and as adult density increases. Using air photo analysis, tree-ring dating and molecular marker analysis we reconstructed the spread of reproductive individuals over 30 years beginning from five initial individuals. In the early stages, genotypes were distributed randomly in space. Over time and with increasing density, fine-scale (< 20 m) SGS developed and the magnitude of genetic clustering increased. The SGS was strongly affected by the initial spatial distribution and genetic variation of the founding individuals. The development of SGS may be explained by fine-scale environmental heterogeneity and possibly microenvironmental selection. Inbreeding and variation in reproductive success may have enhanced SGS magnitude over time.     

Inferring population history from fine-scale spatial genetic analysis in Oryza rufipogon (Poaceae)

Determining the genetic structure of an in situ conserved population can provide insight into the dynamics of population genetic processes associated with successful plant conservation. We used 21 microsatellite loci to analyse the genetic relationships among individuals (n = 813) collected from a small Oryza rufipogon population conserved since 1993 in Hunan Province of China. The analysis revealed four distinct genetic subpopulations (F(ST) = 0.145) without geographic isolation. One subpopulation was composed of possible introgressed individuals, two subpopulations were composed of seed recruits and their descendants, and the fourth subpopulation consisted of reintroduced individuals, seed recruits and their descendants. Positive spatial genetic structures were detected by spatial autocorrelation statistics at the population (c. 63 m) and subpopulation levels (11-30 m), but the degree of autocorrelation was stronger at the population level. These results showed that prejudging the cryptic structure is important before autocorrelation analysis for the entire population. Our study suggests that population history can be a significant determinant on population structure for plant restoration projects.     

Small-scale spatial genetic structure in the Central African rainforest tree species Aucoumea klaineana: a stepwise approach to infer the impact of limited gene dispersal, population history and habitat fragmentation

Under the isolation-by-distance model, the strength of spatial genetic structure (SGS) depends on seed and pollen dispersal and genetic drift, which in turn depends on local demographic structure. SGS can also be influenced by historical events such as admixture of differentiated gene pools. We analysed the fine-scale SGS in six populations of a pioneer tree species endemic to Central Africa, Aucoumea klaineana. To infer the impacts of limited gene dispersal, population history and habitat fragmentation on isolation by distance, we followed a stepwise approach consisting of a Bayesian clustering method to detect differentiated gene pools followed by the analysis of kinship-distance curves. Interestingly, despite considerable variation in density, the five populations situated under continuous forest cover displayed very similar extent of SGS. This is likely due to an increase in dispersal distance with decreased tree density. Admixture between two gene pools was detected in one of these five populations creating a distinctive pattern of SGS. In the last population sampled in open habitat, the genetic diversity was in the same range as in the other populations despite a recent habitat fragmentation. This result may due to the increase of gene dispersal compensating the effect of the disturbance as suggested by the reduced extent of SGS estimated in this population. Thus, in A. klaineana, the balance between drift and dispersal may facilitate the maintenance of genetic diversity. Finally, from the strength of the SGS and population density, an indirect estimate of gene dispersal distances was obtained for one site: the quadratic mean parent-offspring distance, sigma(g), ranged between 210 m and 570 m.     

Fine-scale genetic structure and dispersal in cooperatively breeding apostlebirds

In cooperatively breeding species, restricted dispersal of offspring leads to clustering of closely related individuals, increasing the potential both for indirect genetic benefits and inbreeding costs. In apostlebirds (Struthidea cinerea), philopatry by both sexes results in the formation of large (up to 17 birds), predominantly sedentary breeding groups that remain stable throughout the year. We examined patterns of relatedness and fine-scale genetic structure within a population of apostlebirds using six polymorphic microsatellite loci. We found evidence of fine-scale genetic structure within the study population that is consistent with behavioural observations of short-distance dispersal, natal philopatry by both sexes and restricted movement of breeding groups between seasons. Global F(ST) values among breeding groups were significantly positive, and the average level of pairwise relatedness was significantly higher for individuals within groups than between groups. For individuals from different breeding groups, geographical distance was negatively correlated with pairwise relatedness and positively correlated with pairwise F(ST). However, when each sex was examined separately, this pattern was significant only among males, suggesting that females may disperse over longer distances. We discuss the potential for kin selection to influence the evolution and maintenance of cooperative breeding in apostlebirds. Our results demonstrate that spatial genetic structural analysis offers a useful alternative to field observations in examining dispersal patterns of cooperative breeders.