High levels of genetic variability and inbreeding in two Neotropical dioecious palms with contrasting life histories.

We characterized the population genetics of two Neotropical dioecious palm species of Chamaedorea with contrasting life strategies from the region that is both the northernmost extent and most species rich of the genus. Chamaedorea tepejilote is a common, wind-pollinated arboreal understory palm. Although most adult plants reproduce each year, only a few individuals produce the majority of flowers and seeds. Chamaedorea elatior, conversely, is an uncommon climbing subcanopy palm with entomophilous flowers (insect-pollinated characteristics). Most of the mature palms do not reproduce in consecutive years and fruiting is episodic. Isozymes with a total of 107 alleles for 27 loci of 17 enzymes from six populations were assessed. For both species, co-occurrence of high levels of genetic variation and homozygosity was observed (C. tepejilote: He: 0.385-0.442, f: 0.431-0.486; C. elatior: He: 0.278-0.342, f: 0.466-0.535). Genetic differentiation of C. elatior was much lower (theta=0.0315) than that for C. tepejilote (theta=0.152). The contrast in differentiation may be influenced by differences in the spatial scale of the genetic neighborhoods of the two species. The simultaneous maintenance of inbreeding and of a large number of alleles within the populations is attributable to the low and variable number of mating pairs. Demographic studies indicate that this pattern could be explained by low reproductive frequency among individuals and over years in C. elatior and by reproductive dominance in C. tepejilote.

Estimating dispersal from short distance spatial autocorrelation.

A series of theoretical studies has formed a strong connection between spatial statistics observed in populations and summary measures of the amount of dispersal. Synthesized, these developments allow dispersal to be indirectly estimated from standing spatial patterns of genetic variation under a range of conditions broad enough to be likely met in most populations of either plants or animals. The spatial correlations at the shortest distances are particularly robust to range of conditions and have disproportionately high statistical power. This review integrates theoretical results in a way that maximizes robustness and flexibility in the use of short distance autocorrelation to estimate Wright's neighborhood size, or the total variance in dispersal distances. Empirical guidelines are developed that are meant to be as practical and broad as possible. The guidelines focus on Moran's I-statistics for diploid genotypes converted to allele frequencies, but are also extended to or compared with several other approaches.

Spatial genetic structure of two sympatric neotropical palms with contrasting life histories.

The spatial genetic structure within sympatric populations of two neotropical dioecious palm species with contrasting life histories was characterized to evaluate the influence of life history traits on the extent of genetic isolation by distance. Chamaedorea tepejilote is a common wind-pollinated arboreal understory palm. Chamaedorea elatior is an uncommon climbing subcanopy palm with entomophilous pollination syndrome. A total of 59 allozyme alleles for C. tepejilote and 53 alleles for C. elatior was analyzed using both unweighted (Iu) and weighted (Iw) Moran's I spatial autocorrelation statistics. The spatial genetic structure detected within these populations is consistent with those reported for highly dispersed plants. A significance test for differences between mean Moran's I-coefficients revealed less spatial genetic structure within the C. tepejilote population than that in the C. elatior population. Adjacent individuals of C. elatior exhibited significant spatial genetic autocorrelation (Iu=0.039, Iw=0.034), indicating a Wright's neighborhood size of about 100 individuals. For C. tepejilote, nonrandom genetic distribution among nearest neighbors was detected, even from small spatial autocorrelation values (Iu=0.008, Iw=0.009), consistent with a neighborhood size of about 300 individuals. For both species, seed dispersal, mortality among life cycle stages, overlapping generations, and contrasting traits of mating and reproduction influence the standing spatial genetic structure within populations.

Multilocus estimation of genetic structure within populations.

Spatial structure of genetic variation within populations is well measured by statistics based on the distribution of pairs of individual genotypes, and various such statistics have been widely used in experimental studies. However, the problem of uncharacterized correlations among statistics for different alleles has limited the applications of multiallelic, multilocus summary measures, since these had unknown sampling distributions. Usually multiple alleles and/or multiple loci are required in order to precisely measure spatial structures, and to provide precise indirect estimates of the amount of dispersal in samples of reasonable size. This article examines the correlations among pair-wise statistics, including Moran I-statistics and various measures of conditional kinship, for different alleles of a locus. First the correlations are mathematically derived for random spatial distributions, which allow averages over alleles and loci to be used as more powerful yet exact test statistics for the null hypothesis. Then extensive computer simulations are conducted to examine the correlations among values for different alleles under isolation by distance processes. For loci with more than three alleles, the results show that the correlations are remarkably and perhaps surprisingly small, establishing the principle that then alleles behave as nearly independent realizations of space-time stochastic processes. The results also show that the correlations are largely robust with respect to the degree of spatial structure, and they can be used in a straightforward manner to form confidence intervals for averages. The results allow a precise connection between observations in experimental studies and levels of dispersal in theoretical models.

Temporal aspects of the fine-scale genetic structure in a population of Cinnamomum insularimontanum (Lauraceae).

Cinnamomum insularimontanum Hayata (Lauraceae) is an insect-pollinated, broad-leaved evergreen tree with bird-dispersed seeds. We used allozyme loci, Wright's fixation index, spatial autocorrelation statistics (Moran's I), and coancestry measures to examine changes in genetic structure among four age-classes within a recently founded study population (60 x 100 m area) in southern Korea. There were no significant differences in expected heterozygosity among age classes. However, significant genetic differentiation among age classes was detected (P<0.0001). Fixation indices within age classes showed significant deficits of observed heterozygosity, which may be caused by partial selfing. The homogeneity of genetic structure among four age-classes may reflect similar spatial patterns of seed immigration from surrounding populations occurring year after year. Finally, the average Moran's I and coancestry estimates indicated essentially random spatial distributions of alleles for each of the four age-classes and between seedlings and 2-4 year juveniles vs adult trees. These findings are very similar to those observed in the same study area for another member of the Lauraceae, Neolitsea sericea, which has a very similar life history and ecological characteristics (ie, bird-dispersed fruits, insect pollination, and a similar age structure). Together, these results suggest that the fleshy drupes of lauraceous species represent an adaptation to aid in the independent dispersal of seed by birds, which in turn may increase the genetic diversity of founders colonizing new habitats.

Spatial genetic structure of allozyme polymorphisms within populations of Pinus Strobus (Pinaceae).

The population structure of genetic variation for four allozyme loci was investigated for two populations (one old growth, OG, and the other logged, SS) of eastern white pine (Pinus strobus). Both seedlings and reproductive adults were studied for both study populations. Spatial autocorrelation statistics were used to examine the distribution of allozyme polymorphisms. The spatial genetic structure in adults of population OG indicated that individual genotypes were distributed in a structured, isolation-by-distance manner, consistent with observed levels of pollen and seed dispersal. In contrast, adult genotypes in population SS were nearly randomly distributed, probably as a result of logging. Nonetheless, spatial structuring of genotypes of seedlings occurred at both sites, indicating the power of limited seed flow, as well as temporal Wahlund effects, to create structure. None of four loci in both seedling populations showed a significant departure from Hardy-Weinberg proportions, whereas one and two significant deviations were found for loci in the two respective adult populations. These departures may be attributed to episodic reproductive events.

Clinal differentiation and putative hybridization in a contact zone of Pinus ponderosa and P. arizonica (Pinaceae).

The widely distributed Pinus subsection Ponderosae is a species complex that has a transition zone among taxa in the southwestern United States. In southern Arizona and New Mexico at least two recognized taxa, Pinus ponderosa var. scopulorum and Pinus arizonica or P. ponderosa var. arizonica, are known to coexist in close proximity. In this study, we report the existence of populations where the taxa are sympatric. One of the key characteristics distinguishing taxa is the number of needles per fascicle; P. ponderosa typically has three, P. arizonica has five. We examined the spatial distribution of needle-number types in a belt transect that covers a transition zone from nearly pure three-needle types at the top of Mount Lemmon to five-needle types downslope, in the Santa Catalina Mountains, Arizona. The spatial distribution is inconsistent with there being both free interbreeding among types and selective neutrality of types. Trees with intermediate types, having combinations of three, four, and five needles and/or mean numbers of needles between 3.0 and 5.0, are spatially concentrated in the middle of the transition zone. The spatial distribution supports the occurrence of hybridization and introgression, and this is consistent with reported crossabilities of the types. The results suggest that selection is acting, either on needle number per se or on other traits of the ecotype with which it may be in linkage disequilibrium, to maintain the observed steep clinal differentiation.

Geographic pattern of genetic variation in Pinus resinosa: area of greatest diversity is not the origin of postglacial populations.

Genetic diversity is low in natural populations of red pine, Pinus resinosa, a species that has a vast range across north-eastern North America. In this study, we examined 10 chloroplast microsatellite or simple sequence repeats (cpSSR) loci in 136 individuals from 10 widespread populations. Substantial variation for the cpSSR loci was observed in the study populations. The contrast with red pine's lack of variation for other types of loci is likely to be due to the higher mutation rates typical of SSR loci. The amount of variation is lower than that generally found for cpSSR loci in other pine species. In addition, the variation exhibits a striking geographical pattern. Most of the genetic diversity is among populations, with little within populations, indicating substantial isolation of and genetic drift within many populations in the southern half of the species distribution. The greatest diversity now occurs in the north-eastern part of New England, which is especially intriguing because this entire area was glaciated. Thus the centre of diversity cannot be the origin of postglacial populations, rather it is likely caused by admixture, most probably because of influences from two separate refugia. Furthermore, the pattern indicates that the spread of red pine since the last glaciation is rather more complex than usually described, and it likely includes more than one refugia, complex migration routes, and postglacial-retreat isolation and genetic drift among shrinking populations in regions of the present southern range.

Spatial genetic structure in a Neolitsea sericea population (Lauraceae).

Neolitsea sericea (Bl.) Koidz. (Lauraceae) is a dioecious, insect-pollinated, and broad-leaved evergreen tree with bird-dispersed seeds. We used allozyme loci, F-statistics, and spatial autocorrelation statistics (Moran's I ) to examine the changes in genetic structure among five age classes within a study population (60 m x 100 m area) in southern Korea. No significant differences in expected heterozygosity were found among the age classes. The mean F-values averaged over loci were similar among age classes and showed overall conformance of heterozygosities with Hardy-Weinberg proportions. Differences in allelic frequencies among age classes were small (mean G(ST)=0.012), and statistically significant only for one locus (Pgd-2). The mean Moran's I-values for each of five age classes indicated essentially random spatial distribution. The homogeneity of genetic structure and genetic diversity among the five age classes may reflect the occurrence of similar reproductive events, year after year. The results may reflect the attractive red drupes of N. sericea in that they cause various frugivorous birds to disperse the seed long distances and independently, which in turn may help N. sericea maintain higher levels of genetic diversity within populations.

Clonal and spatial genetic structure in Eurya emarginata (Theaceae).

Eurya emarginata (Thunb.) Makino (Theaceae) is a dioecious, insect-pollinated tree, which combines sexual reproduction and clonal spread. It is narrowly distributed in coastal areas from southern China, along southern Korea, and extending to central and southern Japan. We used allozyme loci and spatial autocorrelation statistics to examine the clonal structure and the spatial distribution of allozyme polymorphisms of sexually reproduced individuals in a study population (70 m x 120 m area) in Korea. The population maintains moderate levels of allozyme variability (mean He=0.133), and multilocus genotypic diversity is high (mean DG=0. 992). The frequency of clones was 0.377 (90/239), and the mean clone-pair distance was very large (35.06 m +/- 1.91 m [SE]), indicating that clones can form at long distances away from their ancestors. In addition, it was found that genetic patch width was at least 24 m. However, join-count statistics for the total number of unlike joins showed that, contrary to expectation for such species, clonal reproduction does not contribute substantially to genetic isolation by distance neither among the sexually reproduced individuals nor the whole population. In contrast, limits to seed and pollen dispersal create substantial levels of genetic structure.

Spatial distribution of allozyme polymorphisms following clonal and sexual reproduction in populations of Rhus javanica (Anacardiaceae).

Rhus javanica L. (Anacardiaceae), a dioecious tree with both sexual reproduction and clonal growth, is widely distributed in warm temperate, subtropical, and tropical regions in east Asia. We used allozyme loci and spatial autocorrelation statistics to examine clonal structure and the spatial distribution of allozyme polymorphisms in two Korean populations. Populations of the species maintain moderate levels of allozyme variability (mean He=0.175, GST=0.060), and high levels of multilocus genotypic diversity (mean DG=0.971). Clone-pair distances ranged from 1.4 m to 57.4 m, and had high mean values of 24.0 m and 25.6 m in the two study populations. Approximate genetic patch widths were inferred to be 23-25 m. The results indicated that within populations there is moderate (one study population) or no (other study population) spatial genetic structure among sexually reproduced individuals, and vegetatively reproduced genotypes also are almost randomly distributed. The spatial genetic structure among sexually reproduced trees in the one case is probably caused by limited pollen dispersal in that population, and the lack of structure in the other probably results from the short time elapsed since founding. It appears that clonal reproduction also does not contribute substantially to genetic isolation by distance neither among the sexually reproduced individuals nor the total population. Ramets often establish long distances from their progenitors and thus do not substantially increase the degree of local consanguineous matings.

Measures of spatial structure in samples of genotypes for multiallelic loci.

Various spatial autocorrelation statistics have been widely used both in theoretical population genetics and to study the spatial distribution of diploid genotypes in many plant and animal populations. However, previous simulation studies have considered only diallelic loci. In this paper, we use a large number of space-time simulations to characterize for the first time the parametric and statistical values of Moran's I-statistics for converted individual genotypes as well as for join-count statistics. A wide range of levels of dispersal and numbers of alleles and allele frequencies are modelled and the results reveal the different general effects of each of these factors on these statistics. We also examine the range of appropriate sampling designs and sizes for which predicted values can be interpolated for specific sampling schemes for any given population genetic field survey. Numbers of alleles and allele frequencies each affect some statistics but not others. The results indicate generally low standard deviations. The results also develop precise and efficient methods of estimating gene dispersal, based on the various autocorrelation measures of standing spatial patterns of genetic variation within populations. The results also extend these methods to loci with multiple alleles, typical of those studied through modern molecular methods.

Gene genealogies in geographically structured populations.

Population genetics theory has dealt only with the spatial or geographic pattern of degrees of relatedness or genetic similarity separately for each point in time. However, a frequent goal of experimental studies is to infer migration patterns that occurred in the past or over extended periods of time. To fully understand how a present geographic pattern of genetic variation reflects one in the past, it is necessary to build genealogy models that directly relate the two. For the first time, space-time probabilities of identity by descent and coalescence probabilities are formulated and characterized in this article. Formulations for general migration processes are developed and applied to specific types of systems. The results can be used to determine the level of certainty that genes found in present populations are descended from ancient genes in the same population or nearby populations vs. geographically distant populations. Some parameter combinations result in past populations that are quite distant geographically being essentially as likely to contain ancestors of genes at a given population as the past population located at the same place. This has implications for the geographic point of origin of ancestral, "Eve," genes. The results also form the first model for emerging "space-time" molecular genetic data.

Measurement of genetic structure within populations using Moran's spatial autocorrelation statistics.

Spatial structure of genetic variation within populations, an important interacting influence on evolutionary and ecological processes, can be analyzed in detail by using spatial autocorrelation statistics. This paper characterizes the statistical properties of spatial autocorrelation statistics in this context and develops estimators of gene dispersal based on data on standing patterns of genetic variation. Large numbers of Monte Carlo simulations and a wide variety of sampling strategies are utilized. The results show that spatial autocorrelation statistics are highly predictable and informative. Thus, strong hypothesis tests for neutral theory can be formulated. Most strikingly, robust estimators of gene dispersal can be obtained with practical sample sizes. Details about optimal sampling strategies are also described.

Spatial distributions of genotypes under isolation by distance.

The spatial distributions of single-locus diploid genotypes, produced within populations of sexually reproducing individuals under isolation by distance, are measured and characterized in detail by quantifying the join-counts for simulated model populations. The models more realistically reflect spatially explicit distributions of genotypes in populations, because unlike the classical theory, they include the stochasticity inherent in the process of matings between genotypes. This stochasticity causes the formation of large areas or patches containing mostly one homozygous genotype, which is not predicted by the classical theory. A number of previously uncharacterized features of the spatial structures produced under isolation by distance are revealed. Spatial autocorrelation measures based on counts of pairs of homozygotes are highly consistent quantifications of the concentrations of homozygotes in patchy genotypic distributions for a given level of dispersal. Most strikingly, the degree of intermixing of homozygotes with heterozygotes over small spatial scales is much higher than previously thought, unless dispersal is extremely limited (e.g., Wright's neighborhood size less than approximately 5.0). Among implications for studies of spatial structure of real populations, one is that the results provide a basis for using join-counts as estimators of gene dispersal based solely on genetic data.

Spatial structure of two-locus genotypes under isolation by distance.

Extensive Monte Carlo simulations are conducted of spatial distributions of two-locus genotypes in large, continuous populations under isolation by distance models. The results show that substantial patches of double homozygotes are present in the spatial structures, even when loci are unlinked. The stochastic spread of identical two-locus genotypes largely outpowers the tendency for recombination to decouple patterns for separate loci. A spatial patch is a large area containing mostly one double homozygous genotype in a highly contiguous constellation. This patch structure is reflected in high positive spatial autocorrelations and large excesses of pairs, or joins, of identical double homozygotes at short-to-intermediate distances of spatial separation. Although spatial patches of double homozygotes are the dominant spatial feature, and the major contributors to overall high levels of autocorrelations among two-locus genotypes, other substantial features include areas of concentrations of identical genotypes heterozygous at only one locus. One implication of the patch structure is the presence of high levels of linkage disequilibrium, caused by isolation by distance even for unlinked loci, at some spatial scales; yet the disequilibrium in the large total populations is near 0. Thus linkage disequilibrium produced by isolation by distance is highly dependent on spatial scale. Another implication is that high degrees of spatial structuring and autocorrelations are produced for genetic variation controlling quantitative traits, at least when the number of loci is relatively small, under a wide range of situations, even if the trait is selectively neutral. The significance of the results to field studies is also examined.

Spatial and space-time correlations in systems of subpopulations with stochastic migration.

The great majority of models of the population genetics of subdivided populations have made the simplifying assumption that the gene frequencies in migrant groups are deterministic. The present paper examines models which more closely mimic natural conditions, in which the gene frequencies in migrant groups are subject to stochastic effects. It is shown that some types of stochastic migration can cause dramatic changes in spatial correlations and variance. These changes depend on how the stochastic migration effects in the gene frequency recursion equations are shared among nearby subpopulations during the same generation. Only for cases where the effects are completely unshared are the equilibrium spatial and space-time correlations among adult subpopulations unaffected, but the variance is always inflated. The analyses here use novel methods, by recasting population genetic migration-drift models as space-time autoregressive moving average (STARMA) processes. Recent theorems for STARMA processes are employed for finding the spatial correlations, and for the first time in population genetics theory the complete set of space-time correlations, for systems with general patterns of migration rates and numbers of spatial dimensions. The space-time correlations provide a uniquely detailed description of a system, and thus form a link between observed spatial autocorrelation statistics and the underlying space-time population genetic process. STARMA theoretical processes have direct statistical analogues that can be applied for process identification, parameter estimation, model fitting, and forecasting in real systems.

Spatial and space-time correlations in systems of subpopulations with genetic drift and migration.

The geographic distribution of genetic variation is an important theoretical and experimental component of population genetics. Previous characterizations of genetic structure of populations have used measures of spatial variance and spatial correlations. Yet a full understanding of the causes and consequences of spatial structure requires complete characterization of the underlying space-time system. This paper examines important interactions between processes and spatial structure in systems of subpopulations with migration and drift, by analyzing correlations of gene frequencies over space and time. We develop methods for studying important features of the complete set of space-time correlations of gene frequencies for the first time in population genetics. These methods also provide a new alternative for studying the purely spatial correlations and the variance, for models with general spatial dimensionalities and migration patterns. These results are obtained by employing theorems, previously unused in population genetics, for space-time autoregressive (STAR) stochastic spatial time series. We include results on systems with subpopulation interactions that have time delay lags (temporal orders) greater than one. We use the space-time correlation structure to develop novel estimators for migration rates that are based on space-time data (samples collected over space and time) rather than on purely spatial data, for real systems. We examine the space-time and spatial correlations for some specific stepping stone migration models. One focus is on the effects of anisotropic migration rates. Partial space-time correlation coefficients can be used for identifying migration patterns. Using STAR models, the spatial, space-time, and partial space-time correlations together provide a framework with an unprecedented level of detail for characterizing, predicting and contrasting space-time theoretical distributions of gene frequencies, and for identifying features such as the pattern of migration and estimating migration rates in experimental studies of genetic variation over space and time.

Spatial autocorrelation of genotypes under directional selection.

The spatial distributions of genetic variation under selection-mutation equilibrium within populations that have limited dispersal are investigated. The results show that directional selection with moderate strength rapidly reduces the amount of genetic structure and spatial autocorrelations far below that predicted for selectively neutral loci. For the latter, homozygotes are spatially clustered into separate areas or patches, each consisting of several hundred homozygotes. When selection is added the patches of the deleterious homozygotes are much smaller, in the range of 25 to 50 individuals. Selection also reduces temporal correlations. Also investigated are the effects of random replacement processes, such as mutation, immigration, and long-distance migration, on spatial and temporal correlations. The detection of natural selection through spatial pattern analysis is discussed, and applied to data from populations of the morning glory, Ipomoea purpurea.