Search

This paper analyses how allele frequencies and population sizes co-evolve in a metapopulation with infinitely many islands that are connected via migration. Each island belongs to one of several distinct ecological niches or habitats. The genetic component of fitness is influenced by an additive trait which is under habitat-specific selection. We analyse the conditions under which locally favoured alleles can be maintained in a rare habitat within the metapopulation, and clarify how demographic stochasticity, the genetic architecture of the selected trait and the relative strengths of selection, gene flow and genetic drift influence local adaptation. An important focus is to understand how the coupling between population size and multiple loci under hard selection shape eco-evolutionary outcomes. Our analysis is based on the diffusion approximation (neglecting linkage disequilibria), and yields an explicit solution for the joint distribution of allele frequencies and population size in each habitat, given the average across the whole metapopulation. We also derive simpler approximations for various limits: including when the coupling between mean fitness and population size can be neglected (the soft selection limit), when loci are close to fixation for one or other allele (the low migration limit), and when population sizes are essentially determined by the expected mean population fitness (the semi-deterministic limit). Individual-based simulations are used to test the validity of key approximations underlying the diffusion framework.

International audience; Species that have sex determined by environmental conditions during development (i.e., environmental sex determination [ESD]) are especially vulnerable to environmental change, including altered stress levels, habitat loss, and species translocations. These factors can produce multigenerational trends in population size and eco-evolutionary dynamics not captured by existing theory based on lifetime reproductive success (R0). Here, we extend ESD theory to use per capita growth rate r as a more appropriate measure of evolutionary success (fitness), and we demonstrate the importance of this change when males and females can differ in maturation times and when maturation times vary with local conditions (plasticity). In these cases, we show that primary and secondary sex ratios may be strongly biased; that optimal maturation times, when locally plastic, depend on the balance between mortality and growth effects; and that plasticity of maturation times can ameliorate fitness costs of increasing environmental stress

Levels of genetic differentiation vary widely along the genomes of recently diverged species. What processes cause this variation? Here, I analyze geographic population structure and genome-wide patterns of variation in the Rufous, Allen's, and Calliope Hummingbirds (Selasphorus rufus/Selasphorus sasin/Selasphorus calliope) and assess evidence that linked selection on the Z chromosome drives patterns of genetic differentiation in a pair of hybridizing species. Demographic models, introgression tests, and genotype clustering analyses support a reticulate evolutionary history consistent with divergence during the late Pleistocene followed by gene flow across migrant Rufous and Allen's Hummingbirds during the Holocene. Relative genetic differentiation ( Fst ) is elevated, and within-population diversity (π) is depressed on the Z chromosome in all interspecific comparisons. The ratio of Z to autosomal within-population diversity is much lower than that expected from population size effects alone, and Tajima's D is depressed on the Z chromosome in S. rufus and S. calliope. These results suggest that conserved structural features of the genome play a prominent role in shaping genetic differentiation through the early stages of speciation in northern Selasphorus hummingbirds, and that the Z chromosome is a likely site of genes underlying behavioral and morphological variation in the group.

Reliable estimates of effective population size Ne are of central importance in population genetics and evolutionary biology. For populations that fluctuate in size, harmonic mean population size is commonly used as a proxy for (multi-) generational effective size. This assumes no effects of density dependence on the ratio between effective and actual population size, which limits its potential application. Here, we introduce density dependence on vital rates in a demographic model of variance effective size. We derive an expression for the ratio Ne/N in a density-regulated population in a fluctuating environment. We show by simulations that yearly genetic drift is accurately predicted by our model, and not proportional to 1/(2N) as assumed by the harmonic mean model, where N is the total population size of mature individuals. We find a negative relationship between Ne/N and N. For a given N, the ratio depends on variance in reproductive success and the degree of resource limitation acting on the population growth rate. Finally, our model indicate that environmental stochasticity may affect Ne/N not only through fluctuations in N, but also for a given N at a given time. Our results show that estimates of effective population size must include effects of density dependence and environmental stochasticity.

Reduced population size is thought to have strong consequences for evolutionary processes as it enhances the strength of genetic drift. In its interaction with selection, this is predicted to increase the genetic load, reduce inbreeding depression, and increase hybrid vigor, and in turn affect phenotypic evolution. Several of these predictions have been tested, but comprehensive studies controlling for confounding factors are scarce. Here, we show that populations of Daphnia magna, which vary strongly in genetic diversity, also differ in genetic load, inbreeding depression, and hybrid vigor in a way that strongly supports theoretical predictions. Inbreeding depression is positively correlated with genetic diversity (a proxy for Ne ), and genetic load and hybrid vigor are negatively correlated with genetic diversity. These patterns remain significant after accounting for potential confounding factors and indicate that, in small populations, a large proportion of the segregation load is converted into fixed load. Overall, the results suggest that the nature of genetic variation for fitness-related traits differs strongly between large and small populations. This has large consequences for evolutionary processes in natural populations, such as selection on dispersal, breeding systems, ageing, and local adaptation.

How population size influences quantitative genetic variation and differentiation among natural, fragmented populations remains unresolved. Small, isolated populations might occupy poor quality habitats and lose genetic variation more rapidly due to genetic drift than large populations. Genetic drift might furthermore overcome selection as population size decreases. Collectively, this might result in directional changes in additive genetic variation (VA ) and trait differentiation (QST ) from small to large population size. Alternatively, small populations might exhibit larger variation in VA and QST if habitat fragmentation increases variability in habitat types. We explored these alternatives by investigating VA and QST using nine fragmented populations of brook trout varying 50-fold in census size N (179-8416) and 10-fold in effective number of breeders, Nb (18-135). Across 15 traits, no evidence was found for consistent differences in VA and QST with population size and almost no evidence for increased variability of VA or QST estimates at small population size. This suggests that (i) small populations of some species may retain adaptive potential according to commonly adopted quantitative genetic measures and (ii) populations of varying sizes experience a variety of environmental conditions in nature, however extremely large studies are likely required before any firm conclusions can be made.

Rates of molecular evolution may vary widely between populations, yet the causes of this variation are still incompletely understood. Genetic differences between populations may make an important contribution to variation in rates of evolution, owing to differences in fitness, population size, mutation rates, or in the distribution of fitness effects (DFEs) of available beneficial mutations. By whole genome sequencing of Escherichia coli populations experimentally evolved in the presence of a quinolone antibiotic, we found that rates of substitution varied by genotype, with evidence for a contribution from a genotype's starting fitness. Subsequent targeted sequencing showed that genotypes with high average substitution rates were more likely to undergo the simultaneous fixation of several mutations, consistent with theoretical models of multiple mutation dynamics. Moreover, patterns of substitution were indicative of epistatic relationships between known resistance mutations.

One of the hallmarks of human fairness is its insensitivity to power: although strong individuals are often in a position to coerce weak individuals, fairness requires them to share the benefits of cooperation equally. The existence of such egalitarianism is poorly explained by current evolutionary models. We present a model based on cooperation and partner choice that can account for the emergence of a psychological disposition toward fairness, whatever the balance of power between the cooperative partners. We model the evolution of the division of a benefit in an interaction similar to an ultimatum game, in a population made up of individuals of variable strength. The model shows that strong individuals will not receive any advantage from their strength, instead having to share the benefits of cooperation equally with weak individuals at the evolutionary equilibrium, a result that is robust to variations in population size and the proportion of weak individuals. We discuss how this model suggests an explanation for why egalitarian behaviors toward everyone, including the weak, should be more likely to evolve in humans than in any other species.

Evolution experiments with microorganisms coupled with genome-wide sequencing now allow for the systematic study of population genetic processes under a wide range of conditions. In learning about these processes in natural, sexual populations, neutral models that describe the behavior of diversity and divergence summaries have played a pivotal role. It is therefore natural to ask whether neutral models, suitably modified, could be useful in the context of evolution experiments. Here, we introduce coalescent models for polymorphism and divergence under the most common experimental evolution assay, a serial transfer experiment. This relatively simple setting allows us to address several issues that could affect diversity patterns in evolution experiments, whether selection is operating or not: the transient behavior of neutral polymorphism in an experiment beginning from a single clone, the effects of randomness in the timing of cell division and noisiness in population size in the dilution stage. In our analyses and discussion, we emphasize the implications for experiments aimed at measuring diversity patterns and making inferences about population genetic processes based on these measurements.

We analyze the stochastic components of the Robertson-Price equation for the evolution of quantitative characters that enables decomposition of the selection differential into components due to demographic and environmental stochasticity. We show how these two types of stochasticity affect the evolution of multivariate quantitative characters by defining demographic and environmental variances as components of individual fitness. The exact covariance formula for selection is decomposed into three components, the deterministic mean value, as well as stochastic demographic and environmental components. We show that demographic and environmental stochasticity generate random genetic drift and fluctuating selection, respectively. This provides a common theoretical framework for linking ecological and evolutionary processes. Demographic stochasticity can cause random variation in selection differentials independent of fluctuating selection caused by environmental variation. We use this model of selection to illustrate that the effect on the expected selection differential of random variation in individual fitness is dependent on population size, and that the strength of fluctuating selection is affected by how environmental variation affects the covariance in Malthusian fitness between individuals with different phenotypes. Thus, our approach enables us to partition out the effects of fluctuating selection from the effects of selection due to random variation in individual fitness caused by demographic stochasticity.

Stochastic population processes may cause differences between species histories and gene histories. These processes are assumed to only influence the most recent divergences in the tree of life; however, there may be underappreciated potential for microevolutionary processes to impact deep divergences. I used multispecies coalescent models to determine the impact of stochastic processes on deep phylogenomic histories. Here I show phylogenomic discordance between gene histories and species histories is expected at deep divergences for many eukaryotic taxa, and the probability of discordance increases with population size, generation time, and the number of species in the tree. Five eukaryotic clades (angiosperms, birds, harpaline beetles, mammals, and nymphalid butterflies) demonstrate significant discordance potential at divergences over 50 million years old, and this discordance potential is independent of the age of divergence. These findings demonstrate population processes acting over very short timescales will leave a lasting impact on genomic histories, even for divergence events occurring tens to hundreds of millions of years ago.

Although there is no known general explanation as to why sexual populations resist asexual invasion, previous work has shown that sexuals can outcompete asexuals in structured populations. However, it is currently unknown whether costly sex can be maintained with the weak structure that is commonly observed in nature. We investigate the conditions under which obligate sexuals resist asexual invasion in structured populations subject to recurrent mutation. We determine the level of population structure needed to disfavor asexuals, as calculated using the average F(st) between all pairs of demes. We show that the critical F(st) needed to maintain sex decreases as the population size increases, and approaches modest levels as observed in many natural populations. Sex is maintained with lower F(st) if there are both advantageous and deleterious mutation, if mutation rates are sufficiently high, and if deleterious mutants have intermediate selective strengths, which maximizes the effect of Muller's ratchet. Additionally, the critical F(st) needed to maintain sex is lower when there are a large number of subpopulations. Lower F(st) values are needed to maintain sex when demes vary substantially in their pairwise distances (e.g., when arrayed along one dimension), although this effect is often modest, especially if some long-distance dispersal is present.

Natural populations must constantly adapt to ever-changing environmental conditions. A particularly interesting question is whether such adaptations can be reversed by returning the population to an ancestral environment. Such evolutionary reversals have been observed in both natural and laboratory populations. However, the factors that determine the reversibility of evolution are still under debate. The time scales of environmental change vary over a wide range, but little is known about how the rate of environmental change influences the reversibility of evolution. Here, we demonstrate computationally that slowly switching between environments increases the reversibility of evolution for small populations that are subject to only modest clonal interference. For small populations, slow switching reduces the mean number of mutations acquired in a new environment and also increases the probability of reverse evolution at each of these "genetic distances." As the population size increases, slow switching no longer reduces the genetic distance, thus decreasing the evolutionary reversibility. We confirm this effect using both a phenomenological model of clonal interference and also a Wright-Fisher stochastic simulation that incorporates genetic diversity. Our results suggest that the rate of environmental change is a key determinant of the reversibility of evolution, and provides testable hypotheses for experimental evolution.

This article explores the combined evolutionary and ecological responses of resource uptake abilities in a generalist consumer to exploitative competition for one resource using a simple 2-resource model. It compares the sizes of ecologically and evolutionarily caused changes in population densities in cases where the original consumer has a strong or a weak trade-off in its abilities to consume the two resources. The analysis also compares the responses of the original species to competition when the competitor's population size is or is not limited by the shared resource. Although divergence in resource use traits in the resident generalist consumer is expected under all scenarios when resources are substitutable, the changes in population densities of the resources and resident consumer frequently differ between scenarios. The population of the original consumer often decreases as a result of its own adaptive divergence, and this decrease is often much greater than the initial ecological decrease. If the evolving consumer has a strong trade-off, the overlapped resource increases in equilibrium population density in response to being consumed by a generalist competitor. Some of these predictions differ qualitatively in alternative scenarios involving sustained variation in population densities or nutritionally essential resources.

Mutators have been shown to hitchhike in asexual populations when the anticipated beneficial mutation supply rate of the mutator subpopulation, NUb (for subpopulation of size N and beneficial mutation rate Ub) exceeds that of the wild-type subpopulation. Here, we examine the effect of total population size on mutator dynamics in asexual experimental populations of Saccharomyces cerevisiae. Although mutators quickly hitchhike to fixation in smaller populations, mutator fixation requires more and more time as population size increases; this observed delay in mutator hitchhiking is consistent with the expected effect of clonal interference. Interestingly, despite their higher beneficial mutation supply rate, mutators are supplanted by the wild type in very large populations. We postulate that this striking reversal in mutator dynamics is caused by an interaction between clonal interference, the fitness cost of the mutator allele, and infrequent large-effect beneficial mutations in our experimental populations. Our work thus identifies a potential set of circumstances under which mutator hitchhiking can be inhibited in natural asexual populations, despite recent theoretical predictions that such populations should have a net tendency to evolve ever-higher genomic mutation rates.

Populations that are connected by immigrants play an important role in evolutionary and conservation biology, yet we have little direct evidence of how such metapopulations change genetically over evolutionary time. We compared historic (1894-1906) to modern (1988-2006) genetic variation in 11 populations of warbler finches at 14 microsatellite loci. Although several lines of evidence suggest that Darwin's finches may be in decline, we found that the genetic diversity of warbler finches has not generally declined, and broad-scale patterns of variation remained similar over time. Contrary to expectations, inferred population sizes have generally increased over time (6-8%) as have immigration rates (8-16%), which may reflect a recent increase in the frequency and intensity of El Nino events. Individual island populations showed significant declines (18-19%) and also substantial gains (18-20%) in allelic richness over time. Changes in genetic diversity were correlated with changes in immigration rates, but did not correspond to population size or human disturbance. These results reflect the expected stabilizing properties of whole metapopulations over time. However, the dramatic and unpredictable changes observed in individual populations during this short time interval suggests that care should be taken when monitoring individual population fragments with snapshots of genetic variation.

Population genetic theory predicts that adaptation in novel environments is enhanced by genetic variation for fitness. However, theory also predicts that under strong selection, demographic stochasticity can drive populations to extinction before they can adapt. We exposed wheat-adapted populations of the flour beetle (Tribolium castaneum) to a novel suboptimal corn resource, to test the effects of founding genetic variation on population decline and subsequent extinction or adaptation. As previously reported, genetically diverse populations were less likely to go extinct. Here, we show that among surviving populations, genetically diverse groups recovered faster after the initial population decline. Within two years, surviving populations significantly increased their fitness on corn via increased fecundity, increased egg survival, faster larval development, and higher rate of egg cannibalism. However, founding genetic variation only enhanced the increase in fecundity, despite existing genetic variation-and apparent lack of trade-offs-for egg survival and larval development time. Thus, during adaptation to novel habitats the positive impact of genetic variation may be restricted to only a few traits, although change in many life-history traits may be necessary to avoid extinction. Despite severe initial maladaptation and low population size, genetic diversity can thus overcome the predicted high extinction risk in new habitats.

Recent experimental and theoretical studies have shown that small asexual populations evolving on complex fitness landscapes may achieve a higher fitness than large ones due to the increased heterogeneity of adaptive trajectories. Here, we introduce a class of haploid three-locus fitness landscapes that allow the investigation of this scenario in a precise and quantitative way. Our main result derived analytically shows how the probability of choosing the path of the largest initial fitness increase grows with the population size. This makes large populations more likely to get trapped at local fitness peaks and implies an advantage of small populations at intermediate time scales. The range of population sizes where this effect is operative coincides with the onset of clonal interference. Additional studies using ensembles of random fitness landscapes show that the results achieved for a particular choice of three-locus landscape parameters are robust and also persist as the number of loci increases. Our study indicates that an advantage for small populations is likely whenever the fitness landscape contains local maxima. The advantage appears at intermediate time scales, which are long enough for trapping at local fitness maxima to have occurred but too short for peak escape by the creation of multiple mutants.

Conflicts of interest between mates can promote the evolution of male traits that reduce female fitness and that drive coevolution between the sexes. The rate of adaptation depends on the intensity of selection and its efficiency, which depends on drift and genetic variability. This leads to the largely untested prediction that coevolutionary adaptations such as those driven by sexual conflict should evolve faster in large populations. We tested this using the bruchid beetle Callosobruchus maculatus, a species where harm inflicted by males is well documented. Although most experimental evolution studies remove sexual conflict, we reintroduced it in populations in which it had been experimentally removed. Both population size and standing genetic variability were manipulated in a factorial experimental design. After 90 generations of relaxed conflict (monogamy), the reintroduction of sexual conflicts for 30 generations favored males that harmed females and females that were more resistant to the genital damage inflicted by males. Males evolved to become more harmful when population size was large rather than when initial genetic variation was enriched. Our study shows that sexual selection can create conditions in which males can benefit from harming females and that selection may tend to be more intense and effective in larger populations.

Selection is recognized to operate on multiple levels. In disease organisms, selection among hosts is thought to provide an important counterbalance to selection for faster growth within hosts. We performed three experiments, each selecting for a divergence in group size in the entomopathogenic nematode, Steinernema carpocapsae. These nematodes infect and kill insect larvae, reproduce inside the host carcass, and emerge as infective juveniles. We imposed selection on group size by selecting among hosts for either high or low numbers of emerging nematodes. Our goal was to determine whether this trait could respond to selection at the group level, and if so, to examine what other traits would evolve as correlated responses. One of the three experiments showed a significant response to group selection. In that experiment, the high-selected treatment consistently produced more emerging nematodes per host than the low-selected treatment. In addition, nematodes were larger and they emerged later from hosts in the low-selected lines. Despite small effective population sizes, the effects of inbreeding were small in this experiment. Thus, selection among hosts can be effective, leading to both a direct evolutionary response at the population level, as well as to correlated responses in populational and individual traits.

Clonal interference refers to the competition that arises in asexual populations when multiple beneficial mutations segregate simultaneously. A large body of theoretical and experimental work now addresses this issue. Although much of the experimental work is performed in populations that grow exponentially between periodic population bottlenecks, the theoretical work to date has addressed only populations of a constant size. We derive an analytical approximation for the rate of adaptation in the presence of both clonal interference and bottlenecks, and compare this prediction to the results of an individual-based simulation, showing excellent agreement in the parameter regime in which clonal interference prevails. We also derive an appropriate definition for the effective population size for adaptive evolution experiments in the presence of population bottlenecks. This "adaptation effective population size" allows for a good approximation of the expected rate of adaptation, either in the strong-selection weak-mutation regime, or when clonal interference comes into play. In the multiple mutation regime, when the product of the population size and mutation rate is extremely large, these results no longer hold.

Small populations of self-incompatible plants are assumed to be threatened by a limitation of compatible mating partners due to low genetic diversity at the self-incompatibility (S) locus. In contrast, we show by using a PCR-RFLP approach for S-genotype identification that 15 small populations (N = 8-88) of the rare wild pear (Pyrus pyraster) displayed no mate limitation. S-allele diversity within populations was high (N = 9-21) as was mate availability (92.9-100%). Although population size and S-allele diversity were strongly related, no relationship was found between population size and mate availability, gene diversity (He), or fixation index (F IS), based on five neutral microsatellite loci. As we determined the principal mate availability within populations based on the S-genotypes observed, the realized mate availability under natural conditions may differ from our estimates, for example, due to spatially limited pollen dispersal. We therefore urge studies on self-incompatible plants to proceed from the simple assessment of principal mate availability to the determination of realized mate availability in natural populations. © 2008 The Author(s).

The role and importance of ecological interactions for evolutionary responses to environmental changes is to large extent unknown. Here it is shown that interspecific competition may slow down rates of adaptation substantially and fundamentally change patterns of adaptation to long-term environmental changes. In the model investigated here, species compete for resources distributed along an ecological niche space. Environmental change is represented by a slowly moving resource maximum and evolutionary responses of single species are compared with responses of coalitions of two and three competing species. In scenarios with two and three species, species that are favored by increasing resource availability increase in equilibrium population size whereas disfavored species decline in size. Increased competition makes it less favorable for individuals of a disfavored species to occupy a niche close to the maximum and reduces the selection pressure for tracking the moving resource distribution. Individual-based simulations and an analysis using adaptive dynamics show that the combination of weaker selection pressure and reduced population size reduces the evolutionary rate of the disfavored species considerably. If the resource landscape moves stochastically, weak evolutionary responses cause large fluctuations in population size and thereby large extinction risk for competing species, whereas a single species subject to the same environmental variability may track the resource maximum closely and maintain a much more stable population size. Other studies have shown that competitive interactions may amplify changes in mean population sizes due to environmental changes and thereby increase extinction risks. This study accentuates the harmful role of competitive interactions by illustrating that they may also decrease rates of adaptation. The slowdown in evolutionary rates caused by competition may also contribute to explain low rates of morphological change in spite of large environmental fluctuations found in fossil records.

Elucidating the forces responsible for genomic variation is critical for understanding evolution. Under standard conditions, X-linked diversity is expected to be three-quarters the level of autosomal diversity. Empirical data often deviate from this prediction, but the reasons for these departures are unclear. We demonstrate that population size changes can greatly alter relative levels of X-linked and autosomal variation: population size reductions lead to particularly low X-linked diversity, whereas growth elevates X-linked relative to autosomal diversity. Genetic variation from a diverse array of taxa supports an important role for this effect in accounting for population differences in the ratio of X-linked to autosomal diversity. Consideration of this effect may improve the inference of population history and other evolutionary processes.

Physiological causes of genetic differences in cannibalism were examined to gain a better understanding of constraints on behavior evolution. Cannibalism has complex population level consequences in Tribolium confusum, including dramatic effects on population size. Laboratory strains with low and high cannibalism rates, obtained through inbreeding, have maintained distinct levels of cannibalism for over two decades even in the absence of artificial selection to maintain the differences. Why strains differ in their cannibalism rates was examined by measuring: (1) the nutritional benefit from cannibalism in both nutritionally good and poor environments, and (2) the possibility that eggs are an important source of water. How strains achieve differences in cannibalism was examined by testing for differences between strains in their ability to find eggs and in their tendency to eat eggs. Beetles from both strains survive equally well in a nutritionally good environment, but they accomplish this in different ways. The low cannibalism strain has high survivorship with and without cannibalism. The high cannibalism strain has low survivorship when not fed eggs and survivorship equivalent to the low cannibalism strain when fed eggs, suggesting it compensates for poor nutritional adaptation by eating eggs. The strains also differ in feeding behavior; beetles from the high cannibalism strain have a higher appetite for eggs. Beetles from the two strains did not differ in locomotor activity, search efficiency, or need for water. The observed behavioral and nutritional differences may contribute to the maintenance of different levels of cannibalism.

A method for estimating the number of founding chromosomes in an isolated population is introduced. The method assumes that n/2 diploid individuals are sampled from a population and that alleles are identified at L unlinked loci. The population is assumed to have been founded T generations in the past by individuals carrying c chromosomes drawn randomly from a known source population, which has also been sampled. If c is small and the population grew rapidly after it was founded, accurate estimates of c can be obtained and those estimates are not sensitive to details of the history of population sizes. If c is larger or the population remained small after it was founded, then estimates of c depend on the history of population sizes. We test the performance of our method on simulated data and demonstrate its use on data from a rainbow trout (Oncorhynchus mykiss) population.

Although most parasites show at least some degree of host specificity, factors governing the evolution of specificity remain poorly understood. Many different groups of host-specific parasites show a striking correlation between parasite and host body size, suggesting that size reinforces specificity. We tested this hypothesis by measuring the relative fitness of host-specific feather lice transferred to pigeons and doves that differ in size by an order of magnitude. To test the general influence of size, we transferred unrelated groups of wing and body lice, which are specialized for different regions of the host. Lice were transferred in both directions, from a large native host species, the rock pigeon (Columba livia), to several progressively smaller hosts, and from a small native host species, the common ground dove (Columbina passerina), to several larger hosts. We measured the relative fitness (population size) of lice transferred to these novel host species after two louse generations. Neither wing lice nor body lice could survive on novel host species that were smaller in size than the native host. However, when host defense (preening behavior) was blocked, both groups survived and reproduced on all novel hosts tested. Thus, host defense interacted with host size to govern the ability of lice to establish on small hosts. Neither wing lice nor body lice could survive on larger hosts, even when preening was blocked. In summary, host size influenced the fitness of both types of feather lice, but through different mechanisms, depending on the direction of the transfer. Our results indicate that host switching is most likely between hosts of similar body size. This finding has important implications for studies of host-parasite coevolution at both the micro- and macroevolutionary scales.

Despite the strong influence of pollination ecology on the evolution of selfing, we have little information on how distinct groups of insect pollinators influence outcrossing rate. However, differences in behavior between pollinator groups could easily influence how each group affects outcrossing rate. We examined the influence of distinct insect pollinator groups on outcrossing rate in the rocky mountain columbine, Aquilegia coerulea. The impact of population size, plant density, size of floral display, and herkogamy (spatial separation between anthers and stigmas) on outcrossing rate was also considered as these variables were previously found to affect outcrossing rate in some plant species. We quantified correlations between all independent variables and used simple and two-factor regressions to determine direct and indirect impact of each independent variable on outcrossing rate. Outcrossing rate increased significantly with hawkmoth abundance but not with the abundance of any of the other groups of floral visitors, which included bumblebees, solitary bees, syrphid flies, and muscidae. Outcrossing rate was also significantly affected by floral display size and together, hawkmoth abundance and floral display size explained 87% of the variation in outcrossing rate. None of the other independent variables directly affected the outcrossing rate. This is the first report of a significant impact of pollinator type on outcrossing rate. Hawkmoths did not visit fewer flowers per plant relative to other pollinator groups but preferred visiting female-phase flowers first on a plant. Both the behavior of pollinators and floral display size affected outcrossing rate via their impact on the level of geitonogamous (among flower) selfing. Given that geitonogamous selfing is never advantageous, the variation in outcrossing rate and maintenance of mixed mating systems in populations of A. coerulea may not require an adaptive explanation.

The minority cytotype exclusion principle describes how random mating between diploid and autotetraploid cytotypes hinders establishment of the rare cytotype. We present deterministic and stochastic models to ascertain how selfing, inbreeding depression, unreduced gamete production, and finite population size affect minority cytotype exclusion and the establishment of autotetraploids. Results demonstrate that higher selfing rates and lower inbreeding depression in autotetraploids facilitate establishment of autotetraploid populations. Stochastic effects due to finite population size increase the probability of polyploid establishment and decrease the mean time to tetraploid fixation. Our results extend the minority cytotype exclusion principle to include important features of plant reproduction and demonstrate that variation in mating system parameters significantly influences the conditions necessary for polyploid establishment.

The ratio of the effective population size to adult (or census) population size (Ne/N) is an indicator of the extent of genetic variation expected in a population. It has been suggested that this ratio may be quite low for highly fecund species in which there is a sweepstakes-like chance of reproductive success, known as the Hedgecock effect. Here I show theoretically how the ratio may be quite small when there are only a few successful breeders (Nb) and that in this case, the Ne/N ratio is approximately Nb/N. In other words, high variance in reproductive success within a generation can result in a very low effective population size in an organism with large numbers of adults and consequently a very low Ne/N ratio. This finding appears robust when there is a large proportion of families with exactly two progeny or when there is random variation in progeny numbers among these families.

Evolutionarily stable strategy (ESS) models are widely viewed as predicting the strategy of an individual that when monomorphic or nearly so prevents a mutant with any other strategy from entering the population. In fact, the prediction of some of these models is ambiguous when the predicted strategy is “mixed”, as in the case of a sex ratio, which may be regarded as a mixture of the subtraits “produce a daughter” and “produce a son.” Some models predict only that such a mixture be manifested by the population as a whole, that is, as an “evolutionarily stable state”; consequently, strategy monomorphism or polymorphism is consistent with the prediction. The hawk-dove game and the sex-ratio game in a panmictic population are models that make such a “degenerate” prediction. We show here that the incorporation of population finiteness into degenerate models has effects for and against the evolution of a monomorphism (an ESS) that are of equal order in the population size, so that no one effect can be...

Theory predicts a significant relationship between the size of a population and the magnitude and composition of its genetic load, but few natural populations have been investigated. We examined the magnitude of genetic load due to recessive deleterious alleles (GL) both segregating and fixed within Gentianella germanica populations of varying size by selfing and reciprocally crossing plants within and between natural populations according to a partial diallel design and by comparing the performance of the experimental progeny in a common-garden experiment. The results show that GL for total fitness in small populations (fewer than 200 plants) was mainly due to fixed recessive deleterious alleles, whereas GL for total fitness in larger populations (more than 200 plants) appeared to be mainly due to segregating deleterious recessive alleles. The total fitness of selfed plants increased with decreasing population size, indicating some purging of deleterious alleles associated with declining population sizes. The magnitudes of GL due to fixed deleterious alleles in small populations and segregating deleterious alleles in large populations, however, were overall similar, suggesting that purging selection was an insignificant force when compared to genetic drift in determining the magnitude of GL in small natural populations in this species. The results of this study highlight the importance of population size in determining the dynamics of genetic loads of natural populations and are overall in line with a large body of theoretical work indicating that small populations may face higher extinction risks due to the fixation and accumulation of deleterious alleles of small effect.

We present moments and likelihood methods that estimate a DNA substitution rate from a group of closely related sister species pairs separated at an assumed time, and we test these methods with simulations. The methods also estimate ancestral population size and can test whether there is a significant difference among the ancestral population sizes of the sister species pairs. Estimates presented in the literature often ignore the ancestral coalescent prior to speciation and therefore should be biased upward. The simulations show that both methods yield accurate estimates given sample sizes of five or more species pairs and that better likelihood estimates are obtained if there is no significant difference among ancestral population sizes. The model presented here indicates that the larger than expected variation found in multitaxa datasets can be explained by variation in the ancestral coalescence and the Poisson mutation process. In this context, observed variation can often be accounted for by variation in ancestral population sizes rather than invoking variation in other parameters, such as divergence time or mutation rate. The methods are applied to data from two groups of species pairs (sea urchins and Alpheus snapping shrimp) that are thought to have separated by the rise of Panama three million years ago.

Molecular methods as applied to the biogeography of single species (phylogeography) or multiple codistributed species (comparative phylogeography) have been productively and extensively used to elucidate common historical features in the diversification of the Earth's biota. However, only recently have methods for estimating population divergence times or their confidence limits while taking into account the critical effects of genetic polymorphism in ancestral species become available, and earlier methods for doing so are underutilized. We review models that address the crucial distinction between the gene divergence, the parameter that is typically recovered in molecular phylogeographic studies, and the population divergence, which is in most cases the parameter of interest and will almost always postdate the gene divergence. Assuming that population sizes of ancestral species are distributed similarly to those of extant species, we show that phylogeographic studies in vertebrates suggest that divergence of alleles in ancestral species can comprise from less than 10% to over 50% of the total divergence between sister species, suggesting that the problem of ancestral polymorphism in dating population divergence can be substantial. The variance in the number of substitutions (among loci for a given species or among species for a given gene) resulting from the stochastic nature of DNA change is generally smaller than the variance due to substitutions along allelic lines whose coalescence times vary due to genetic drift in the ancestral population. Whereas the former variance can be reduced by further DNA sequencing at a single locus, the latter cannot. Contrary to phylogeographic intuition, dating population divergence times when allelic lines have achieved reciprocal monophyly is in some ways more challenging than when allelic lines have not achieved monophyly, because in the former case critical data on ancestral population size provided by residual ancestral polymorphism is lost. In the former case differences in coalescence time between species pairs can in principle be explained entirely by differences in ancestral population size without resorting to explanations involving differences in divergence time. Furthermore, the confidence limits on population divergence times are severely underestimated when those for number of substitutions per site in the DNA sequences examined are used as a proxy. This uncertainty highlights the importance of multilocus data in estimating population divergence times; multilocus data can in principle distinguish differences in coalescence time (T) resulting from differences in population divergence time and differences in T due to differences in ancestral population sizes and will reduce the confidence limits on the estimates. We analyze the contribution of ancestral population size (theta) to T and the effect of uncertainty in theta on estimates of population divergence (tau) for single loci under reciprocal monophyly using a simple Bayesian extension of Takahata and Satta's and Yang's recent coalescent methods. The confidence limits on tau decrease when the range over which ancestral population size theta is assumed to be distributed decreases and when tau increases; they generally exclude zero when tau/(4Ne) > 1. We also apply a maximum-likelihood method to several single and multilocus data sets. With multilocus data, the criterion for excluding tau = 0 is roughly that l tau/(4Ne) > 1, where l is the number of loci. Our analyses corroborate recent suggestions that increasing the number of loci is critical to decreasing the uncertainty in estimates of population divergence time.

For clonal lineages of finite size that differ in their deleterious mutational effects, the probability of fixation is investigated by mathematical theory and Monte Carlo simulations. If these fitness effects are sufficiently small in one or both lineages, then the lineage with the less deleterious effects will become fixed with high probability. If, however, in both lineages the deleterious effects are larger than a threshold s(c), then the probability of fixation is independent of the fitness effects and depends only on the initial frequencies of the lineages. This threshold decreases with decreasing genomic mutation rate U and increases with population size N. (For N = 10(5), we have s(c) approximately = 0.1 if U = 1, and s(c) approximately = 0.015 if U = 0.1). Above the threshold, the competition is not driven by the ratio of mean fitnesses of the lineages, but by the relative sizes of the zero-mutation classes, which are independent of the fitness effects of the mutations. After the loss of the zero-mutation class of a lineage, the other lineage will spread to fixation with high probability and within a short time span. If the mutation rates of the lineages differ substantially, the lineage with the lower mutation rate is fixed with very high probability unless the lineage with the larger mutation rate has very slightly deleterious mutational effects. If the mutation rates differ by not more than a few percent, then the lineage with the higher mutation rate and the more deleterious effects can become fixed with appreciable probability for a certain range of parameters. The independence of the fixation probability on the fitness effects in a single population leads to dramatic effects in metapopulations: lineages with more deleterious effects have a much higher fixation probability. The critical value s(c), above which this phenomenon occurs, decreases as the migration rate between the subpopulations decreases.

Although highly variable loci, such as microsatellite loci, are revolutionizing both evolutionary and conservation biology, data from these loci need to be carefully evaluated. First, because these loci often have very high within-population heterozygosity, the magnitude of differentiation measures may be quite small. For example, maximum GST values for populations with no common alleles at highly variable loci may be small and are at maximum less than the average within-population homozygosity. As a result, measures that are variation independent are recommended for highly variable loci. Second, bottlenecks or a reduction in population size can generate large genetic distances in a short time for these loci. In this case, the genetic distance may be corrected for low variation in a population and tests to detect bottlenecks are advised. Third, statistically significant differences may not reflect biologically meaningful differences both because the patterns of adaptive loci may not be correlated with highly variable loci and statistical power with these markers is so high. As an example of this latter effect, the statistical power to detect a one-generation bottleneck of different sizes for different numbers of highly variable loci is discussed. All of these concerns need to be incorporated in the utilization and interpretation of patterns of highly variable loci for both evolutionary and conservation biology.

In this paper we present a method for estimating population divergence times by maximum likelihood in models without mutation. The maximum-likelihood estimator is compared to a commonly applied estimator based on Wright's FST statistic. Simulations suggest that the maximum-likelihood estimator is less biased and has a lower variance than the FST-based estimator. The maximum-likelihood estimator provides a statistical framework for the analysis of population history given genetic data. We demonstrate how maximum-likelihood estimates of the branching pattern of divergence of multiple populations may be obtained. We also describe how the method may be applied to test hypotheses such as whether populations have maintained equal population sizes. We illustrate the method by applying it to two previously published sets of human restriction fragment length polymorphism (RFLP) data. The estimation of population divergence times and genetic distances has many applications in the demographic and ge- netic analysis of population history. Several estimators of genetic distances have been proposed (Cavalli-Sforza and Edwards 1964; Nei 1972; Reynolds et al. 1983). In this article we propose a new maximum-likelihood estimator of popu- lation divergence time based on the coalescent model (King- man 1982) with no mutation. We describe applications of this estimator, most notably the inference of population phylog- enies and show that the maximum-likelihood estimator has desirable statistical properties. To evaluate the performance of the new estimator, we compare it to the estimator based on Wright's FST statistic described by Reynolds at al. (1983). FST is the most commonly applied divergence estimator based upon a model of genetic drift without mutation. FST measures the reduction in heterozygosity in a subpop- ulation relative to the heterozygosity of the total population. It is a standard measure of population differentiation and is applied in the estimation of population divergence times (see for example Weir 1996). Under a model of neutral divergence of two populations from a common ancestral population, FST can be translated directly into an estimate of the time since population divergence. In this case, divergence is measured in terms of the scaled time, T = tl2N, where t is the number of generations since the two populations diverged and N is the effective size of each of the two populations. T can then be estimated by