Genetic structure in patchy populations of a candidate foundation plant: a case study of Leymus chinensis using genetic and clonal diversity

PREMISE

The distribution of genetic diversity on the landscape has critical ecological and evolutionary implications. This may be especially the case on a local scale for foundation plant species because they create and define ecological communities, contributing disproportionately to ecosystem function.

METHODS

We examined the distribution of genetic diversity and clones, which we defined first as unique multilocus genotypes (MLG), and then by grouping similar MLGs into multilocus lineages. We used 186 markers from inter-simple sequence repeats (ISSR) across 358 ramets from 13 patches of the foundation grass Leymus chinensis. We examined the relationship between genetic and clonal diversities, their variation with patch size, and the effect of the number of markers used to evaluate genetic diversity and structure in this species.

RESULTS

Every ramet had a unique MLG. Almost all patches consisted of individuals belonging to a single multilocus lineages. We confirmed this with a clustering algorithm to group related genotypes. The predominance of a single lineage within each patch could be the result of the accumulation of somatic mutations, limited dispersal, some sexual reproduction with partners mainly restricted to the same patch, or a combination of all three.

CONCLUSIONS

We found strong genetic structure among patches of L. chinensis. Consistent with previous work on the species, the clustering of similar genotypes within patches suggests that clonal reproduction combined with somatic mutation, limited dispersal, and some degree of sexual reproduction among neighbors causes individuals within a patch to be more closely related than among patches.

Intraspecific trait variation influences physiological performance and fitness in the South Africa shrub genus Protea (Proteaceae)

BACKGROUND AND AIMS

Global plant trait datasets commonly identify trait relationships that are interpreted to reflect fundamental trade-offs associated with plant strategies, but often these trait relationships are not identified when evaluating them at smaller taxonomic and spatial scales. In this study we evaluate trait relationships measured on individual plants for five widespread Protea species in South Africa to determine whether broad-scale patterns of structural trait (e.g. leaf area) and physiological trait (e.g. photosynthetic rates) relationships can be detected within natural populations, and if these traits are themselves related to plant fitness.

METHODS

We evaluated the variance structure (i.e. the proportional intraspecific trait variation relative to among-species variation) for nine structural traits and six physiological traits measured in wild populations. We used a multivariate path model to evaluate the relationships between structural traits and physiological traits, and the relationship between these traits and plant size and reproductive effort.

KEY RESULTS

While intraspecific trait variation is relatively low for structural traits, it accounts for between 50 and 100 % of the variation in physiological traits. Furthermore, we identified few trait associations between any one structural trait and physiological trait, but multivariate regressions revealed clear associations between combinations of structural traits and physiological performance (R2 = 0.37-0.64), and almost all traits had detectable associations with plant fitness.

CONCLUSIONS

Intraspecific variation in structural traits leads to predictable differences in individual-level physiological performance in a multivariate framework, even though the relationship of any particular structural trait to physiological performance may be weak or undetectable. Furthermore, intraspecific variation in both structural and physiological traits leads to differences in plant size and fitness. These results demonstrate the importance of considering measurements of multivariate phenotypes on individual plants when evaluating trait relationships and how trait variation influences predictions of ecological and evolutionary outcomes.

Microscale trait-environment associations in two closely-related South African shrubs

PREMISE OF THE STUDY

Plant traits are often associated with the environments in which they occur, but these associations often differ across spatial and phylogenetic scales. Here we study the relationship between microenvironment, microgeographical location, and traits within populations using co-occurring populations of two closely related evergreen shrubs in the genus Protea.

METHODS

We measured a suite of functional traits on 147 plants along a single steep mountainside where both species occur, and we used data-loggers and soil analyses to characterize the environment at 10 microsites spanning the elevational gradient. We used Bayesian path analyses to detect trait-environment relationships in the field for each species. We used complementary data from greenhouse grown seedlings derived from wild collected seed to determine whether associations detected in the field are the result of genetic differentiation.

KEY RESULTS

Microenvironmental variables differed substantially across our study site. We found strong evidence for six trait-environment associations, although these differed between species. We were unable to detect similar associations in greenhouse-grown seedlings.

CONCLUSIONS

Several leaf traits were associated with temperature and soil variation in the field, but the inability to detect these in the greenhouse suggests that differences in the field are not the result of genetic differentiation.

Correlated evolution between climate and suites of traits along a fast-slow continuum in the radiation of Protea

Evolutionary radiations are responsible for much of Earth's diversity, yet the causes of these radiations are often elusive. Determining the relative roles of adaptation and geographic isolation in diversification is vital to understanding the causes of any radiation, and whether a radiation may be labeled as "adaptive" or not. Across many groups of plants, trait-climate relationships suggest that traits are an important indicator of how plants adapt to different climates. In particular, analyses of plant functional traits in global databases suggest that there is an "economics spectrum" along which combinations of functional traits covary along a fast-slow continuum. We examine evolutionary associations among traits and between trait and climate variables on a strongly supported phylogeny in the iconic plant genus Protea to identify correlated evolution of functional traits and the climatic-niches that species occupy. Results indicate that trait diversification in Protea has climate associations along two axes of variation: correlated evolution of plant size with temperature and leaf investment with rainfall. Evidence suggests that traits and climatic-niches evolve in similar ways, although some of these associations are inconsistent with global patterns on a broader phylogenetic scale. When combined with previous experimental work suggesting that trait-climate associations are adaptive in Protea, the results presented here suggest that trait diversification in this radiation is adaptive.

Isolation by distance and isolation by environment contribute to population differentiation in Protea repens (Proteaceae L.), a widespread South African species

PREMISE OF THE STUDY

The Cape Floristic Region (CFR) of South Africa is renowned for its botanical diversity, but the evolutionary origins of this diversity remain controversial. Both neutral and adaptive processes have been implicated in driving diversification, but population-level studies of plants in the CFR are rare. Here, we investigate the limits to gene flow and potential environmental drivers of selection in Protea repens L. (Proteaceae L.), a widespread CFR species.

METHODS

We sampled 19 populations across the range of P. repens and used genotyping by sequencing to identify 2066 polymorphic loci in 663 individuals. We used a Bayesian F_ST outlier analysis to identify single-nucleotide polymorphisms (SNPs) marking genomic regions that may be under selection; we used those SNPs to identify potential drivers of selection and excluded them from analyses of gene flow and genetic structure.

RESULTS

A pattern of isolation by distance suggested limited gene flow between nearby populations. The populations of P. repens fell naturally into two or three groupings, which corresponded to an east-west split. Differences in rainfall seasonality contributed to diversification in highly divergent loci, as do barriers to gene flow that have been identified in other species.

CONCLUSIONS

The strong pattern of isolation by distance is in contrast to the findings in the only other widespread species in the CFR that has been similarly studied, while the effects of rainfall seasonality are consistent with well-known patterns. Assessing the generality of these results will require investigations of other CFR species.

Anchored phylogenomics improves the resolution of evolutionary relationships in the rapid radiation of Protea L

PREMISE OF THE STUDY

Estimating phylogenetic relationships in relatively recent evolutionary radiations is challenging, especially if short branches associated with recent divergence result in multiple gene tree histories. We combine anchored enrichment next-generation sequencing with species tree analyses to produce a robust estimate of phylogenetic relationships in the genus Protea (Proteaceae), an iconic radiation in South Africa.

METHODS

We sampled multiple individuals within 59 out of 112 species of Protea and 6 outgroup species for a total of 163 individuals, and obtained sequences for 498 low-copy, orthologous nuclear loci using anchored phylogenomics. We compare several approaches for building species trees, and explore gene tree-species tree discrepancies to determine whether poor phylogenetic resolution reflects a lack of informative sites, incomplete lineage sorting, or hybridization.

KEY RESULTS

Phylogenetic estimates from species tree approaches are similar to one another and recover previously well-supported clades within Protea, in addition to providing well-supported phylogenetic hypotheses for previously poorly resolved intrageneric relationships. Individual gene trees are markedly different from one another and from species trees. Nonetheless, analyses indicate that differences among gene trees occur primarily concerning clades supported by short branches.

CONCLUSIONS

Species tree methods using hundreds of nuclear loci provided strong support for many previously unresolved relationships in the radiation of the genus Protea. In cases where support for particular relationships remains low, these appear to arise from few informative sites and lack of information rather than strongly supported disagreement among gene trees.

Transcriptome sequencing reveals population differentiation in gene expression linked to functional traits and environmental gradients in the South African shrub Protea repens

Understanding the environmental and genetic mechanisms underlying locally adaptive trait variation across the ranges of species is a major focus of evolutionary biology. Combining transcriptome sequencing with common garden experiments on populations spanning geographical and environmental gradients holds promise for identifying such mechanisms. The South African shrub Protea repens displays diverse phenotypes in the wild along drought and temperature gradients. We grew plants from seeds collected at 19 populations spanning this species' range, and sequenced the transcriptomes of these plants to reveal gene pathways associated with adaptive trait variation. We related expression in co-expressed gene networks to trait phenotypes measured in the common garden and to source population climate. We found that expression in gene networks correlated with source-population environment and with plant traits. In particular, the activity of gene networks enriched for growth related pathways correlated strongly with source site minimum winter temperature and with leaf size, stem diameter and height in the garden. Other gene networks with enrichments for photosynthesis related genes showed associations with precipitation. Our results strongly suggest that this species displays population-level differences in gene expression that have been shaped by source population site climate, and that are reflected in trait variation along environmental gradients.

Intraspecific variation in stomatal traits, leaf traits and physiology reflects adaptation along aridity gradients in a South African shrub

BACKGROUND AND AIMS

Trait-environment relationships are commonly interpreted as evidence for local adaptation in plants. However, even when selection analyses support this interpretation, the mechanisms underlying differential benefits are often unknown. This study addresses this gap in knowledge using the broadly distributed South African shrub Protea repens. Specifically, the study examines whether broad-scale patterns of trait variation are consistent with spatial differences in selection and ecophysiology in the wild.

METHODS

In a common garden study of plants sourced from 19 populations, associations were measured between five morphological traits and three axes describing source climates. Trait-trait and trait-environment associations were analysed in a multi-response model. Within two focal populations in the wild, selection and path analyses were used to test associations between traits, fecundity and physiological performance.

KEY RESULTS

Across 19 populations in a common garden, stomatal density increased with the source population's mean annual temperature and decreased with its average amount of rainfall in midsummer. Concordantly, selection analysis in two natural populations revealed positive selection on stomatal density at the hotter, drier site, while failing to detect selection at the cooler, moister site. Dry-site plants with high stomatal density also had higher stomatal conductances, cooler leaf temperatures and higher light-saturated photosynthetic rates than those with low stomatal density, but no such relationships were present among wet-site plants. Leaf area, stomatal pore index and specific leaf area in the garden also co-varied with climate, but within-population differences were not associated with fitness in either wild population.

CONCLUSIONS

The parallel patterns of broad-scale variation, differences in selection and differences in trait-ecophysiology relationships suggest a mechanism for adaptive differentiation in stomatal density. Densely packed stomata may improve performance by increasing transpiration and cooling, but predominately in drier, hotter climates. This study uniquely shows context-dependent benefits of stomatal density--a trait rarely linked to local adaptation in plants.

Extrapolating from local ecological processes to genus-wide patterns in colour polymorphism in South African Protea

Polymorphic traits are central to many fundamental discoveries in evolution, yet why they are found in some species and not others remains poorly understood. We use the African genus Protea-within which more than 40% of species have co-occurring pink and white floral colour morphs-to ask whether convergent evolution and ecological similarity could explain the genus-wide pattern of polymorphism. First, we identified environmental correlates of pink morph frequency across 28 populations of four species. Second, we determined whether the same correlates could predict species-level polymorphism and monomorphism across 31 species. We found that pink morph frequency increased with elevation in Protea repens and three section Exsertae species, increased eastward in P. repens, and increased with seed predation intensity in section Exsertae. For cross-species comparisons, populations of monomorphic pink species occurred at higher elevations than populations of monomorphic white species, and 18 polymorphic species spanned broader elevational gradients than 13 monomorphic species. These results suggest that divergent selection along elevational clines has repeatedly favoured polymorphism, and that more uniform selection in altitudinally restricted species may promote colour monomorphism. Our findings are, to our knowledge, the first to link selection acting within species to the presence and absence of colour polymorphism at broader phylogenetic scales.

Genetic diversity and population structure in Polygonum cespitosum: insights to an ongoing plant invasion

Molecular markers can help elucidate how neutral evolutionary forces and introduction history contribute to genetic variation in invaders. We examined genetic diversity, population structure and colonization patterns in the invasive Polygonum cespitosum, a highly selfing, tetraploid Asian annual introduced to North America. We used nine diploidized polymorphic microsatellite markers to study 16 populations in the introduced range (northeastern North America), via the analyses of 516 individuals, and asked the following questions: 1) Do populations have differing levels of within-population genetic diversity? 2) Do populations form distinct genetic clusters? 3) Does population structure reflect either geographic distances or habitat similarities? We found low heterozygosity in all populations, consistent with the selfing mating system of P. cespitosum. Despite the high selfing levels, we found substantial genetic variation within and among P. cespitosum populations, based on the percentage of polymorphic loci, allelic richness, and expected heterozygosity. Inferences from individual assignment tests (Bayesian clustering) and pairwise F_ST values indicated high among-population differentiation, which indicates that the effects of gene flow are limited relative to those of genetic drift, probably due to the high selfing rates and the limited seed dispersal ability of P. cespitosum. Population structure did not reflect a pattern of isolation by distance nor was it related to habitat similarities. Rather, population structure appears to be the result of the random movement of propagules across the introduced range, possibly associated with human dispersal. Furthermore, the high population differentiation, genetic diversity, and fine-scale genetic structure (populations founded by individuals from different genetic sources) in the introduced range suggest that multiple introductions to this region may have occurred. High genetic diversity may further contribute to the invasive success of P. cespitosum in its introduced range.

Developmental plasticity in Protea as an evolutionary response to environmental clines in the Cape Floristic Region

Local adaptation along steep environmental gradients likely contributes to plant diversity in the Cape Region of South Africa, yet existing analyses of trait divergence are limited to static measurements of functional traits rather than trajectories of individual development. We explore whether five taxa of evergreen shrubs (Protea section Exsertae) differ in their developmental trajectories and capacity for plasticity using two environmentally-distinct common gardens in South Africa. We measured seedlings in the summer-dry season and winter-wet season of each of two consecutive years to characterize ontogeny and plasticity within years, as same-age leaf cohorts mature, and between years, i.e., from leaf one cohort to the next. We compared patterns of development between gardens to assess whether trait trajectories are programmed versus plastic and examined whether developmental differences covaried with characteristics of a seedling’s home environment. We detected plasticity in developmental trajectories for leaf area, stomatal size, stomatal pore index, and to a limited extent specific leaf area, but not for stomatal density. We showed that the species growing in the harshest environments exhibits both the smallest increase in leaf area between years and the least change in SLA and photosynthetic rates as leaves age within years. These results show that within this clade, species have diverged in developmental trajectories and plasticity as well as in mean trait values. Some of these differences may be associated with adaptation to cold and drought stress within an environmentally-complex region.

Direct and indirect selection on floral pigmentation by pollinators and seed predators in a color polymorphic South African shrub

The coexistence of different color morphs is often attributed to variable selection pressures across space, time, morph frequencies, or selection agents, but the routes by which each morph is favored are rarely identified. In this study we investigated factors that influence floral color polymorphisms on a local scale in Protea, within which approximately 40% of species are polymorphic. Previous work shows that seed predators and reproductive differences likely contribute to maintaining polymorphism in four Protea species. We explored whether selection acts directly or indirectly on floral color in two populations of Protea aurea, using path analysis of pollinator behavior, nectar production, seed predation, color, morphology, and maternal fecundity fitness components. We found that avian pollinators spent more time on white morphs, likely due to nectar differences, but that this had no apparent consequences for fecundity. Instead, the number of flowers per inflorescence underpinned many of the reproductively important differences between color morphs. White morphs had more flowers per inflorescence, which itself was positively correlated with nectar production, seed predator occurrence, and total long-term seed production. The number of seeds per plant to survive predation, in contrast, was not directly associated with color or any other floral trait. Thus, although color differences may be associated with conflicting selection pressures, the selection appears to be associated with the number of flowers per inflorescence and its unmeasured correlates, rather than with inflorescence color itself.

Estimating covariation between vital rates: a simulation study of connected vs. separate generalized linear mixed models (GLMMs)

Covariation between vital rates is recognized as an important pattern to be accounted for in demographic modeling. We recently introduced a model for estimating vital rates and their covariation as a function of known and unknown effects, using generalized linear mixed models (GLMM's) implemented in a hierarchical Bayesian framework (Evans et al., 2010) In particular, this model included a model-wide year effect (YEAR) influencing all vital rates, which we used to estimate covariation between vital rates due to exogenous factors not directly included in the model. This YEAR effect connected the GLMMs of vital rates into one large model; we refer to this as the "connected GLMMs" approach. Here we used a simulation study to evaluate the performance of a simplified version of this model, compared to separate GLMMs of vital rates, in terms of their ability to estimate correlations between vital rates. We simulated data from known relationships between vital rates and a covariate, inducing correlations among the vital rates. We then estimated those correlations from the simulated data using connected vs. separate GLMMs with year random effects. We compared precision and accuracy of estimated vital rates and their correlations under three scenarios of the pervasiveness of the exogenous effect (and thus true correlations). The two approaches provide equally good point estimates of vital rate parameters, but connected GLMMs provide better estimates of covariation between vital rates than separate GLMMs, both in terms of accuracy and precision, when the common influence on vital rates is pervasive. We discuss the situations where connected GLMMs might be best used, as well as further areas of investigation for this approach.

Genetic diversity of microsatellite loci in hierarchically structured populations

Microsatellite loci are widely used for investigating patterns of genetic variation within and among populations. Those patterns are in turn determined by population sizes, migration rates, and mutation rates. We provide exact expressions for the first two moments of the allele frequency distribution in a stochastic model appropriate for studying microsatellite evolution with migration, mutation, and drift under the assumption that the range of allele sizes is bounded. Using these results, we study the behavior of several measures related to Wright's F(ST), including Slatkin's R(ST). Our analytical approximations for F(ST) and R(ST) show that familiar relationships between N(e)m and F(ST) or R(ST) hold when the migration and mutation rates are small. Using the exact expressions for F(ST) and R(ST), our numerical results show that, when the migration and mutation rates are large, these relationships no longer hold. Our numerical results also show that the diversity measures most closely related to F(ST) depend on mutation rates, mutational models (stepwise versus two-phase), migration rates, and population sizes. Surprisingly, R(ST) is relatively insensitive to the mutation rates and mutational models. The differing behaviors of R(ST) and F(ST) suggest that properties of the among-population distribution of allele frequencies may allow the roles of mutation and migration in producing patterns of diversity to be distinguished, a topic of continuing investigation.

Extreme environments select for reproductive assurance: evidence from evening primroses (Oenothera)

Competing evolutionary forces shape plant breeding systems (e.g. inbreeding depression, reproductive assurance). Which of these forces prevails in a given population or species is predicted to depend upon such factors as life history, ecological conditions, and geographical context. Here, we examined two such predictions: that self-compatibility should be associated with the annual life history or extreme climatic conditions. We analyzed data from a clade of plants remarkable for variation in breeding system, life history and climatic conditions (Oenothera, sections Anogra and Kleinia, Onagraceae). We used a phylogenetic comparative approach and Bayesian or hybrid Bayesian tests to account for phylogenetic uncertainty. Geographic information system (GIS)-based climate data and ecological niche modeling allowed us to quantify climatic conditions. Breeding system and reproductive life span are not correlated in Anogra and Kleinia. Instead, self-compatibility is associated with the extremes of temperature in the coldest part of the year and precipitation in the driest part of the year. In the 60 yr since this pattern was anticipated, this is the first demonstration of a relationship between the evolution of self-compatibility and climatic extremes. We discuss possible explanations for this pattern and possible implications with respect to anthropogenic climate change.

A Beta-mixture model for assessing genetic population structure

An important fraction of recently generated molecular data is dominant markers. They contain substantial information about genetic variation but dominance makes it impossible to apply standard techniques to calculate measures of genetic differentiation, such as F-statistics. In this article, we propose a new Bayesian beta-mixture model that more accurately describes the genetic structure from dominant markers and estimates multiple F(ST) s from the sample. The model also has important application for codominant markers and single-nucleotide polymorphism (SNP) data. The number of F(ST)  is assumed unknown beforehand and follows a random distribution. The reversible jump algorithm is used to estimate the unknown number of multiple F(ST) s. We evaluate the performance of three split proposals and the overall performance of the proposed model based on simulated dominant marker data. The model could reliably identify and estimate a spectrum of degrees of genetic differentiation present in multiple loci. The estimates of F(ST) s also incorporate uncertainty about the magnitude of within-population inbreeding coefficient. We illustrate the method with two examples, one using dominant marker data from a rare orchid and the other using codominant marker data from human populations.

Modifiers of mutation rate: Evolutionary optimum with complete selfing

It often has been assumed that, for infinite random mating populations in a constant environment, natural selection will favor genotypes at a neutral modifier locus that minimize the mutation rate. Mathematical modeling of this process confirms this assertion, independent of the selection regime. The same model under conditions of complete selfing can produce, under certain nondegenerate overdominance conditions, an optimum mutation rate below which increased mutation is favored and above which decreased mutation is favored. This occurs with unidirectional mutation models and a class of reversible mutation models with fitness overdominance. This is the first time that such a modifier optimum has been produced analytically for an infinite population in a constant environment.

Natural selection on inflorescence color polymorphisms in wild Protea populations: The role of pollinators, seed predators, and intertrait correlations

PREMISE OF THE STUDY

The processes maintaining flower color polymorphisms have long been of evolutionary interest. Mechanistic explanations include selection through pollinators, antagonists, local environments, drift, and pleiotropic effects. We examined the maintenance of inflorescence color polymorphisms in the genus Protea (Proteaceae) of South Africa, in which ∼40% of species contain different color morphs. •

METHODS

We studied 10 populations of four bird-pollinated Protea species and compared adult performance, floral and leaf morphology, vegetative pigmentation, germination, and seedling survival between co-occurring pink and white morphs. We also tested for differences in pollination success and pre-dispersal seed predation. •

KEY RESULTS

White morphs produced seeds 10% heavier and 3.5 times more likely to germinate, which all else being equal, should fuel positive selection on white. In one studied population per species, however, white morphs were more susceptible to seed predation by endophagous larvae. Pollinators had no morph-specific effects on female fecundity, as measured by amount or probability of seed set. Differences in stem color indicated that white morphs produced smaller quantities of pigment and associated compounds throughout, possibly explaining their higher seed palatability. •

CONCLUSIONS

Our findings suggest a mechanism for some white protea polymorphisms: deleterious pleiotropic effects on pink morphs are occasionally offset by reduced losses to seed-eating larvae. Because trends were repeated across species, we suggest that similar processes may also occur in other proteas, placing a new emphasis on seed predators for influencing some of South Africa's amazing floral diversity.

Breeding system variation in 10 evening primroses (Oenothera sections Anogra and Kleinia; Onagraceae)

PREMISE OF THE STUDY

We examined two accounts of the relationship between breeding system and life history variation in a clade of evening primroses (Oenothera, Onagraceae): (1) selection for reproductive assurance should generate an association between self-compatibility and monocarpy and (2) phylogenetic conservatism leads to retention of breeding system and life history traits among closely related taxa. •

METHODS

We performed over 4000 hand pollinations under greenhouse conditions to determine the compatibility of 10 Oenothera taxa (sections Anogra [17 taxa] and Kleinia [2 taxa)] for which breeding systems had not previously been reported. We used generalized linear mixed models to evaluate the influence of pollination treatment, parents, and population on fruiting success. •

KEY RESULTS

Among the taxa tested, six were self-incompatible, two were variable in compatibility, and two were self-compatible. We combined these data with published studies in Anogra and Kleinia and mapped breeding system and life history onto a published phylogeny. •

CONCLUSIONS

We found no evidence for phylogenetic conservatism, but detected considerable evolutionary lability in both traits. Additionally, we found no evidence for a consistent relationship between breeding system and life history. Only eight of 19 taxa followed the predicted association between self-incompatibility and polycarpy vs. self-compatibility and monocarpy. Instead, many taxa have retained self-incompatibility, regardless of monocarpy or polycarpy.

Genetics in geographically structured populations: defining, estimating and interpreting F(ST)

Wright's F-statistics, and especially F(ST), provide important insights into the evolutionary processes that influence the structure of genetic variation within and among populations, and they are among the most widely used descriptive statistics in population and evolutionary genetics. Estimates of F(ST) can identify regions of the genome that have been the target of selection, and comparisons of F(ST) from different parts of the genome can provide insights into the demographic history of populations. For these reasons and others, F(ST) has a central role in population and evolutionary genetics and has wide applications in fields that range from disease association mapping to forensic science. This Review clarifies how F(ST) is defined, how it should be estimated, how it is related to similar statistics and how estimates of F(ST) should be interpreted.

Proximity is not a proxy for parentage in an animal-dispersed Neotropical canopy palm

We used parentage analysis to estimate seedling recruitment distances and genetic composition of seedling patches centred around reproductive trees of the animal-dispersed Neotropical canopy palm Iriartea deltoidea in two 0.5 ha plots within second-growth forest and one 0.5 ha plot in adjacent old-growth forest at La Selva Biological Field Station in north-eastern Costa Rica. Seedlings were significantly spatially aggregated in all plots, but this pattern was not due to dispersal limitation. More than 70 per cent of seedlings were dispersed at least 50 m from parent trees. Few seedlings were offspring of the closest reproductive trees. Seedling patches observed beneath reproductive trees originate from dozens of parental trees. Observed patterns of seedling distribution and spatial genetic structure are largely determined by the behaviour of vertebrate seed dispersers rather than by spatial proximity to parental trees.

A Bayesian hierarchical model for analysis of SNP diversity in multilocus, multipopulation samples

The distribution of genetic variation among populations is conveniently measured by Wright's F(ST), which is a scaled variance taking on values in [0,1]. For certain types of genetic markers, and for single-nucleotide polymorphisms (SNPs) in particular, it is reasonable to presume that allelic differences at most loci are selectively neutral. For such loci, the distribution of genetic variation among populations is determined by the size of local populations, the pattern and rate of migration among those populations, and the rate of mutation. Because the demographic parameters (population sizes and migration rates) are common across all autosomal loci, locus-specific estimates of F(ST) will depart from a common distribution only for loci with unusually high or low rates of mutation or for loci that are closely associated with genomic regions having a relationship with fitness. Thus, loci that are statistical outliers showing significantly more among-population differentiation than others may mark genomic regions subject to diversifying selection among the sample populations. Similarly, statistical outliers showing significantly less differentiation among populations than others may mark genomic regions subject to stabilizing selection across the sample populations. We propose several Bayesian hierarchical models to estimate locus-specific effects on F(ST), and we apply these models to single nucleotide polymorphism data from the HapMap project. Because loci that are physically associated with one another are likely to show similar patterns of variation, we introduce conditional autoregressive models to incorporate the local correlation among loci for high-resolution genomic data. We estimate the posterior distributions of model parameters using Markov chain Monte Carlo (MCMC) simulations. Model comparison using several criteria, including DIC and LPML, reveals that a model with locus- and population-specific effects is superior to other models for the data used in the analysis. To detect statistical outliers we propose an approach that measures divergence between the posterior distributions of locus-specific effects and the common F(ST) with the Kullback-Leibler divergence measure. We calibrate this measure by comparing values with those produced from the divergence between a biased and a fair coin. We conduct a simulation study to illustrate the performance of our approach for detecting loci subject to stabilizing/divergent selection, and we apply the proposed models to low- and high-resolution SNP data from the HapMap project. Model comparison using DIC and LPML reveals that CAR models are superior to alternative models for the high resolution data. For both low and high resolution data, we identify statistical outliers that are associated with known genes.

Detecting the influence of ornamental Berberis thunbergii var. atropurpurea in invasive populations of Berberis thunbergii (Berberidaceae) using AFLP1

Japanese barberry (Berberis thunbergii DC.) is a widespread invasive plant that remains an important landscape shrub represented by ornamental, purple-leaved forms of the botanical variety atropurpurea. These forms differ greatly in appearance from feral plants, bringing into question whether they contribute to invasive populations or whether the invasions represent self-sustaining populations derived from the initial introduction of the species in the late 19th century. In this study we used amplified fragment length polymorphism (AFLP) markers to determine whether genetic contributions from B. t. var. atropurpurea are found within naturalized Japanese barberry populations in southern New England. Bayesian clustering of AFLP genotypes and principal coordinate analysis distinguished B. t. var. atropurpurea genotypes from 85 plants representing five invasive populations. While a single feral plant resembled B. t. var. atropurpurea phenotypically and fell within the same genetic cluster, all other naturalized plants sampled were genetically distinct from the purple-leaved genotypes. Seven plants from two different sites possessed morphology consistent with Berberis vulgaris (common barberry) or B. ×ottawensis (B. thunbergii × B. vulgaris). Genetic analysis placed these plants in two clusters separate from B. thunbergii. Although the Bayesian analysis indicated some introgression of B. t. var. atropurpurea and B. vulgaris, these genotypes have had limited influence on extant feral populations of B. thunbergii.

Multigenerational genetic analysis of tropical secondary regeneration in a canopy palm

Iriartea deltoidea (Arecaceae) is an abundant canopy palm with a wide geographic distribution in Neotropical wet forests. We analyzed the genetic profile across three generations of Iriartea within a 43-ha area encompassing two areas of second-growth and adjoining old-growth forest at La Selva Biological Field Station in northeastern Costa Rica. A total of 311 reproductively mature trees, 99 large saplings, 207 small saplings, and 601 seedlings were genotyped using 141 AFLP loci. Parentage analysis revealed high dispersal distances, both for seed (over 2.3 km) and pollen (over 3.8 km), indicating a large genetic neighborhood within La Selva Biological Station. In a 20-ha area of second growth, the founding palm population was dominated by a small number of parental trees located in the adjacent old-growth forest; two old-growth trees contributed 48% of the second-growth genes. The genetic diversity of reproductively mature trees in this second-growth forest was significantly reduced compared to adjacent old-growth forest. Within 400 m of the border with old-growth forest, we observed a similar reduction of genetic diversity in saplings, and an even greater loss of genetic diversity in the second generation of seedlings. Nearly half of these seedlings were offspring of local parents. In contrast, in the distant portion of second-growth forest (400-800 m from the old-growth border), parentage analysis showed that 40% of seedlings originated from outside the study area and only 10% were offspring of local parents. These high levels of gene flow maintained genetic diversity in saplings and seedlings similar to levels observed in old-growth forest. Our findings highlight the importance of gene flow from diverse seed and pollen sources for sustaining levels of genetic diversity of tree populations in second-growth forests.

Model fitting and inference under Latent Equilibrium Processes

This paper presents a methodology for model fitting and inference in the context of Bayesian models of the type f(Y | X, theta)f(X | theta)f(theta), where Y is the (set of) observed data, theta is a set of model parameters and X is an unobserved (latent) stationary stochastic process induced by the first order transition model f(X((t+1)) | X((t)), theta), where X((t)) denotes the state of the process at time (or generation) t. The crucial feature of the above type of model is that, given theta, the transition model f(X((t+1)) | X((t)), theta) is known but the distribution of the stochastic process in equilibrium, that is f(X | theta), is, except in very special cases, intractable, hence unknown. A further point to note is that the data Y has been assumed to be observed when the underlying process is in equilibrium. In other words, the data is not collected dynamically over time.We refer to such specification as a latent equilibrium process (LEP) model. It is motivated by problems in population genetics (though other applications are discussed), where it is of interest to learn about parameters such as mutation and migration rates and population sizes, given a sample of allele frequencies at one or more loci. In such problems it is natural to assume that the distribution of the observed allele frequencies depends on the true (unobserved) population allele frequencies, whereas the distribution of the true allele frequencies is only indirectly specified through a transition model.As a hierarchical specification, it is natural to fit the LEP within a Bayesian framework. Fitting such models is usually done via Markov chain Monte Carlo (MCMC). However, we demonstrate that, in the case of LEP models, implementation of MCMC is far from straightforward. The main contribution of this paper is to provide a methodology to implement MCMC for LEP models. We demonstrate our approach in population genetics problems with both simulated and real data sets. The resultant model fitting is computationally intensive and thus, we also discuss parallel implementation of the procedure in special cases.

Differentiation among populations with migration, mutation, and drift: implications for genetic inference

Populations may become differentiated from one another as a result of genetic drift. The amounts and patterns of differentiation at neutral loci are determined by local population sizes, migration rates among populations, and mutation rates. We provide exact analytical expressions for the mean, variance, and covariance of a stochastic model for hierarchically structured populations subject to migration, mutation, and drift. In addition to the expected correlation in allele frequencies among populations in the same geographic region, we demonstrate that there is a substantial correlation in allele frequencies among regions at the top level of the hierarchy. We propose a hierarchical Bayesian model for inference of Wright's F-statistics in a two-level hierarchy in which we estimate the among-region correlation in allele frequencies by substituting replication across loci for replication across time. We illustrate the approach through an analysis of human microsatellite data, and we show that approaches ignoring the among-region correlation in allele frequencies underestimate the amount of genetic differentiation among major geographic population groups by approximately 30%. Finally, we discuss the implications of these results for the use and interpretation of F-statistics in evolutionary studies.

Polytomies and Bayesian Phylogenetic Inference

Bayesian phylogenetic analyses are now very popular in systematics and molecular evolution because they allow the use of much more realistic models than currently possible with maximum likelihood methods. There are, however, a growing number of examples in which large Bayesian posterior clade probabilities are associated with very short branch lengths and low values for non-Bayesian measures of support such as nonparametric bootstrapping. For the four-taxon case when the true tree is the star phylogeny, Bayesian analyses become increasingly unpredictable in their preference for one of the three possible resolved tree topologies as data set size increases. This leads to the prediction that hard (or near-hard) polytomies in nature will cause unpredictable behavior in Bayesian analyses, with arbitrary resolutions of the polytomy receiving very high posterior probabilities in some cases. We present a simple solution to this problem involving a reversible-jump Markov chain Monte Carlo (MCMC) algorithm that allows exploration of all of tree space, including unresolved tree topologies with one or more polytomies. The reversible-jump MCMC approach allows prior distributions to place some weight on less-resolved tree topologies, which eliminates misleadingly high posteriors associated with arbitrary resolutions of hard polytomies. Fortunately, assigning some prior probability to polytomous tree topologies does not appear to come with a significant cost in terms of the ability to assess the level of support for edges that do exist in the true tree. Methods are discussed for applying arbitrary prior distributions to tree topologies of varying resolution, and an empirical example showing evidence of polytomies is analyzed and discussed.

Genetic Consequences of Tropical Second-Growth Forest Regeneration

Secondary forests are more extensive than old-growth forests in many tropical regions, yet the genetic composition of colonizing populations is poorly understood. We analyzed the parentage of a founder population of 130 individuals of the canopy palm Iriartea deltoidea in a 24-year-old second-growth forest in lowland Costa Rica. Among 66 trees in adjacent old-growth forest, only two individuals contributed 56% of the genes in founders. Second-growth trees had lower genetic diversity and larger patches of similar genotypes than old-growth trees. Recovery of genetic diversity of populations in tropical second-growth forests may take many generations and will require continued dispersal from genetically diverse source populations.

Bayesian models for the analysis of genetic structure when populations are correlated

MOTIVATION

Population allele frequencies are correlated when populations have a shared history or when they exchange genes. Unfortunately, most models for allele frequency and inference about population structure ignore this correlation. Recent analytical results show that among populations, correlations can be very high, which could affect estimates of population genetic structure. In this study, we propose a mixture beta model to characterize the allele frequency distribution among populations. This formulation incorporates the correlation among populations as well as extending the model to data with different clusters of populations.

RESULTS

Using simulated data, we show that in general, the mixture model provides a good approximation of the among-population allele frequency distribution and a good estimate of correlation among populations. Results from fitting the mixture model to a dataset of genotypes at 377 autosomal microsatellite loci from human populations indicate high correlation among populations, which may not be appropriate to neglect. Traditional measures of population structure tend to overestimate the amount of genetic differentiation when correlation is neglected. Inference is performed in a Bayesian framework.

CONTACT

fur@ohsu.edu.

Natural selection on light response curve parameters in the herbaceous annual, Impatiens capensis

We tested for genetic variation in light response curves and their acclimation to sun versus shade in recombinant inbred lines (RILs) of the annual species Impatiens capensis derived from a cross between sun and shade populations. We exposed replicates of 49 RILs to experimentally manipulated light levels (open versus shade) in a greenhouse and measured photosynthetic light response curves, height, biomass, and reproduction. Plants were taller in the shade treatment, but we were unable to detect differences between light treatments (i.e., acclimation) in the maximal rate of photosynthesis, the light compensation point, or the quantum efficiency of photosynthesis. Genotypic selection analyses indicated that higher maximal rates of carbon assimilation and higher light compensation points (typical of sun-acclimated light curves) were favored by natural selection in both light treatments. Thus, it appears that the pattern of selection on photosynthetic parameters may not depend on light environment in this species.

Bayesian approaches for the analysis of population genetic structure: an example from Platanthera leucophaea (Orchidaceae)

We describe four extensions to existing Bayesian methods for the analysis of genetic structure in populations: (i) use of beta distributions to approximate the posterior distribution of f and theta(B); (ii) use of an entropy statistic to describe the amount of information about a parameter derived from the data; (iii) use of the Deviance Information Criterion (DIC) as a model choice criterion for determining whether there is evidence for inbreeding within populations or genetic differentiation among populations; and (iv) use of samples from the posterior distributions for f and theta(B) derived from different data sets to determine whether the estimates are consistent with one another. We illustrate each of these extensions by applying them to data derived from previous allozyme and random amplified polymorphic DNA surveys of an endangered orchid, Platanthera leucophaea, and we conclude that differences in theta(B) from the two data sets may represent differences in the underlying mutational processes.

Local differentiation and plasticity in size and sex expression in jack-in-the-pulpit, Arisaema triphyllum (Araceae)

The size advantage hypothesis suggests that natural selection will favor size-dependent sex expression when one sex gains more than the other by being large. But members of a minority sex will also have a higher reproductive value, on average. Thus, an individual's reproductive success depends on the reproductive decisions made by neighboring individuals. As a result, the optimal relationship between size and sex may differ among populations. In Arisaema triphyllum, the probability for an individual to be female increases with size, regardless of the character measured. A reciprocal transplant experiment showed the relationship between size and sexual expression is environmentally plastic. Plants originating from our two study sites became female at a larger average size when grown at one site than when grown at the other. In addition to environmental influence on sex expression, the experiment demonstrated genetic differences in the relationship between size and sex. Plants collected from one site became female at a larger size than those from the other, regardless of where they were grown. Thus, while the environment in which an individual was grown had a substantial influence on its sex expression, populations only a few kilometers apart have genetically different relationships between size and sex.