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.     

Plant dispersal, neighbourhood size and isolation by distance

A theoretical relationship between isolation by distance or spatial genetic structure (SGS) and seed and pollen dispersal is tested using extensive spatial-temporal simulations. Although for animals Wright's neighbourhood size N(e) = 4pisigma(2)(t) has been ascertained also, where sigma(2)(t) is the axial variance of distances between parents and offspring, and it was recently confirmed that N(e) = 4pi(sigma(2)(f) + sigma(2)(m))/2 when dispersal of females and males differ, the situation for plants had not been established. This article shows that for a very wide range of conditions, neighbourhood size defined by Crawford's formula N(e) = 4pi(sigma(2)(s) + sigma(2)(p)/2) fully determines SGS, even when dispersal variances of seed (sigma(2)(s)) and pollen sigma(2)(p)) differ strongly. Further, self-fertilization with rate s acts as zero-distance pollen dispersal, and N(e) = 4pi[sigma(2)(s) + sigma(2)(p)(1 - s)/2] fully determines SGS, for most cases where there are both likely parameter values and substantial SGS. Moreover, for most cases, there is a loglinear relationship, I(1) = 0.587 - 0.117 ln(N(e)), between SGS, as measured by I(1), Moran's coefficient for adjacent individuals, and N(e). However, there are several biologically significant exceptions, namely for very low or large N(e), SGS exceeds the loglinear values. There are also important exceptions to Crawford's formula. First, plants with low seed dispersal, high outcross pollen dispersal and high selfing rate show larger SGS than predicted. Second, in plants with very low (near zero) seed dispersal, selfing decreases SGS, opposite expectations. Finally, in some cases seed dispersal is more critical than pollen dispersal, in a manner inconsistent with Crawford's formula.     

A powerful regression-based method for admixture mapping of isolation across the genome of hybrids

We propose a novel method that uses natural admixture between divergent lineages (hybridization) to investigate the genetic architecture of reproductive isolation and adaptive introgression. Our method employs multinomial regression to estimate genomic clines and to quantify introgression for individual loci relative to the genomic background (clines in genotype frequency along a genomic admixture gradient). Loci with patterns of introgression that deviate significantly from null expectations based on the remainder of the genome are potentially subject to selection and thus of interest to understanding adaptation and the evolution of reproductive isolation. Using simulations, we show that different forms of selection modify these genomic clines in predictable ways and that our method has good power to detect moderate to strong selection for multiple forms of selection. Using individual-based simulations, we demonstrate that our method generally has a low false positive rate, except when genetic drift is particularly pronounced (e.g. low population size, low migration rates from parental populations, and substantial time since initial admixture). Additional individual-based simulations reveal that moderate selection against heterozygotes can be detected as much as 50 c m away from the focal locus directly experiencing selection, but is not detected at unlinked loci. Finally, we apply our analytical method to previously published data sets from a mouse ( Mus musculus and M. domesticus ) and two sunflower ( Helianthus petiolaris and H. annuus ) hybrid zones. This method should be applicable to numerous species that are currently the focus of research in evolution and ecology and should help bring about new insights regarding the processes underlying the origin and maintenance of biological diversity.     

Do landscape processes predict phylogeographic patterns in the wood frog?

Understanding factors that influence population connectivity and the spatial distribution of genetic variation is a major goal in molecular ecology. Improvements in the availability of high-resolution geographic data have made it increasingly possible to quantify the effects of landscape features on dispersal and genetic structure. However, most studies examining such landscape effects have been conducted at very fine (e.g. landscape genetics) or broad (e.g. phylogeography) spatial scales. Thus, the extent to which processes operating at fine spatial scales are linked to patterns at larger scales remains unclear. Here, we test whether factors impacting wood frog dispersal at fine spatial scales are correlated with genetic structure at regional scales. Using recently developed methods borrowed from electrical circuit theory, we generated landscape resistance matrices among wood frog populations in eastern North America based on slope, a wetness index, land cover and absolute barriers to wood frog dispersal. We then determined whether these matrices are correlated with genetic structure based on six microsatellite markers and whether such correlations outperform a landscape-free model of isolation by resistance. We observed significant genetic structure at regional spatial scales. However, topography and landscape variables associated with the intervening habitat between sites provide little explanation for patterns of genetic structure. Instead, absolute dispersal barriers appear to be the best predictor of regional genetic structure in this species. Our results suggest that landscape variables that influence dispersal, microhabitat selection and population structure at fine spatial scales do not necessarily explain patterns of genetic structure at broader scales.     

Evolutionary insights into Rhinolophus episcopus (Chiroptera,Rhinolophidae) in China: Isolation by distance,environment, or sensory system?

Evolutionary processes can be influenced by several factors, such as geographic isolation, environmental selection, and sensory variation. For most nocturnal bats, echolocation is the primary sensory system used to prey and communicate, and plays important roles in chiropteran diversification and evolution. Understanding the relative contribution of geography, the environment, and this sensory system to population genetic divergence can elucidate the processes involved in bat incipient speciation and evolution. In this study, we collected spatial and environmental information, echolocation calls, as well as the previously published genetic data (six microsatellite loci and the mitochondrial cytochrome b gene) of widely distributed Rhinolophus episcopus populations to test three hypotheses for nuclear and mitochondrial divergence (isolation by distance, isolation by environment, and isolation by sensory variation) and unveil the factors that drive intraspecific genetic differentiation. The moderate level of nuclear differentiation was correlated with geographic/spatial distance and acoustic variation, whereas the relatively high level of mitochondrial differentiation was mainly associated with acoustic divergence. No significant correlation was observed between genetic divergence and environmental variables. Among the three factors, acoustic divergence explained the highest percentage of both nuclear and mitochondrial divergence. Thus, our results indicate that sensory variation may have played important roles in driving population isolation early in bat speciation, which is consistent with the hypothesis of isolation by sensory variation. Our study emphasizes the need to consider more factors, especially sensory traits, and combine multiple statistical methods in landscape genetic studies to test their potential contributions to driving population divergence.     

Microspatial population genetic structure of the Mediterranean shrub Fumana thymifolia

Fumana thymifolia (Cistaceae) is an insect-pollinated, gravity-dispersed evergreen shrub, which is a common component of fire-prone Mediterranean shrubland ecosystems. Despite the availability of basic knowledge on its ecology, little is known of its breeding system and no information is available on its population genetic structure. We explored the within-population genetic structure of this species using amplified fragment length polymorphism (AFLP) molecular markers and related this to predictions based on its breeding system, pollen and seed dispersal. Existing information on the reproductive ecology of F. thymifolia was supplemented by artificial pollination experiments. We determined that self-fertilisation can occur in F. thymifolia but results in reduced fruit set. Significant genetic structuring was detected within the population, a likely consequence of localised seed dispersal in combination with a mixed mating system. In a study site covering approximately 0.5 ha, amova revealed that approximately 9% of genetic variability was distributed among population subsamples. Significant spatial genetic structure was detected, with kinship coefficients being significantly elevated above the null expectation in the first six distance classes (maximum 5 m), and a value of Sp of up to 0.0342, comparable with species having similar ecological characteristics. Weak isolation by distance at the plot scale was detected, suggesting that insect-mediated pollen flow is non-random, despite being more extensive than seed dispersal. Fumana thymifolia provides a promising model for the investigation of both short- and long-term population dynamics in relation to fire frequency within this plant community.     

Compatible genetic and ecological estimates of dispersal rates in insect (Coenagrion mercuriale: Odonata: Zygoptera) populations: analysis of 'neighbourhood size' using a more precise estimator

Genetic and demographic estimates of dispersal are often thought to be inconsistent. In this study, we use the damselfly Coenagrion mercuriale (Odonata: Zygoptera) as a model to evaluate directly the relationship between estimates of dispersal rate measured during capture-mark-recapture fieldwork with those made from the spatial pattern of genetic markers in linear and two-dimensional habitats. We estimate the 'neighbourhood size' (Nb) - the product of the mean axial dispersal rate between parent and offspring and the population density - by a previously described technique, here called the regression method. Because C. mercuriale is less philopatric than species investigated previously by the regression method we evaluate a refined estimator that may be more applicable for relatively mobile species. Results from simulations and empirical data sets reveal that the new estimator performs better under most situations, except when dispersal is very localized relative to population density. Analysis of the C. mercuriale data extends previous results which demonstrated that demographic and genetic estimates of Nb by the regression method are equivalent to within a factor of two at local scales where genetic estimates are less affected by habitat heterogeneity, stochastic processes and/or differential selective regimes. The corollary is that with a little insight into a species' ecology the pattern of spatial genetic structure provides quantitative information on dispersal rates and/or population densities that has real value for conservation management.     

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.     

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.