Deme Size Research Articles

Elevational Range Impacts Connectivity and Predicted Deme Sizes From Models of Habitat Suitability.

In integrative distributional, demographic and coalescent (iDDC) modelling, a critical component is the statistical relationship between habitat suitability and local population sizes. This study explores this relationship in two Enyalius lizard species from the Brazilian Atlantic Forest: the high-elevation E. iheringii and low-elevation E. catenatus and how this transformation affects spatiotemporal demographic inference. Most previous iDDC studies assumed a linear relationship, but this study hypothesises that the relationship may be nonlinear, especially for high-elevation species with broader environmental tolerances. We test two key hypotheses: (1) The habitat suitability to population size relationship is nonlinear for E. iheringii (high-elevation) and linear for E. catenatus (low-elevation); and (2) E. iheringii exhibits higher effective migration across populations than E. catenatus. Our findings provide clear support for hypothesis (2), but mixed support for hypothesis (1), with strong model support for a nonlinear transformation in the high-elevation E. iheringii and some (albeit weak) support for a nonlinear transformation also in E. catenatus. The iDDC models allow us to generate landscape-wide maps of predicted genetic diversity for both species, revealing that genetic diversity predictions for the high-elevation E. iheringii align with estimated patterns of historical range stability, whereas predictions for low-elevation E. catenatus are distinct from range-wide stability predictions. This research highlights the importance of accurately modelling the habitat suitability to population size relationship in iDDC studies, contributing to our understanding of species' demographic responses to environmental changes.

Stochastic viability in an island model with partial dispersal: Approximation by a diffusion process in the limit of a large number of islands

In this paper, we investigate a finite population undergoing evolution through an island model with partial dispersal and without mutation, where generations are discrete and non-overlapping. The population is structured into D demes, each containing N individuals of two possible types, A and B, whose viability coefficients, sA and sB, respectively, vary randomly from one generation to the next. We assume that the means, variances and covariance of the viability coefficients are inversely proportional to the number of demes D, while higher-order moments are negligible in comparison to 1/D. We use a discrete-time Markov chain with two timescales to model the evolutionary process, and we demonstrate that as the number of demes D approaches infinity, the accelerated Markov chain converges to a diffusion process for any deme size N≥2. This diffusion process allows us to evaluate the fixation probability of type A following its introduction as a single mutant in a population that was fixed for type B. We explore the impact of increasing the variability in the viability coefficients on this fixation probability. At least when N is large enough, it is shown that increasing this variability for type B or decreasing it for type A leads to an increase in the fixation probability of a single A. The effect of the population-scaled variances, σA2 and σB2, can even cancel the effects of the population-scaled means, μA and μB. We also show that the fixation probability of a single A increases as the deme-scaled migration rate increases. Moreover, this probability is higher for type A than for type B if the population-scaled geometric mean viability coefficient is higher for type A than for type B, which means that μA−σA2/2>μB−σB2/2.

Host body size, not host population size, predicts genome-wide effective population size of parasites.

The effective population size (Ne) of an organism is expected to be generally proportional to the total number of individuals in a population. In parasites, we might expect the effective population size to be proportional to host population size and host body size, because both are expected to increase the number of parasite individuals. However, among other factors, parasite populations are sometimes so extremely subdivided that high levels of inbreeding may distort these predicted relationships. Here, we used whole-genome sequence data from dove parasites (71 feather louse species of the genus Columbicola) and phylogenetic comparative methods to study the relationship between parasite effective population size and host population size and body size. We found that parasite effective population size is largely explained by host body size but not host population size. These results suggest the potential local population size (infrapopulation or deme size) is more predictive of the long-term effective population size of parasites than is the total number of potential parasite infrapopulations (i.e., host individuals).

Using gridCoal to assess whether standard population genetic theory holds in the presence of spatio-temporal heterogeneity in population size.

Spatially explicit population genetic models have long been developed, yet have rarely been used to test hypotheses about the spatial distribution of genetic diversity or the genetic divergence between populations. Here, we use spatially explicit coalescence simulations to explore the properties of the island and the two-dimensional stepping stone models under a wide range of scenarios with spatio-temporal variation in deme size. We avoid the simulation of genetic data, using the fact that under the studied models, summary statistics of genetic diversity and divergence can be approximated from coalescence times. We perform the simulations using gridCoal, a flexible spatial wrapper for the software msprime (Kelleher et al., 2016, Theoretical Population Biology, 95, 13) developed herein. In gridCoal, deme sizes can change arbitrarily across space and time, as well as migration rates between individual demes. We identify different factors that can cause a deviation from theoretical expectations, such as the simulation time in comparison to the effective deme size and the spatio-temporal autocorrelation across the grid. Our results highlight that FST , a measure of the strength of population structure, principally depends on recent demography, which makes it robust to temporal variation in deme size. In contrast, the amount of genetic diversity is dependent on the distant past when Ne is large, therefore longer run times are needed to estimate Ne than FST . Finally, we illustrate the use of gridCoal on a real-world example, the range expansion of silver fir (Abies alba Mill.) since the last glacial maximum, using different degrees of spatio-temporal variation in deme size.

Evolutionary Game Dynamics in a Finite Continental Island Population Model and Emergence of Cooperation

We consider the continental island model for a finite haploid population with a total number of \({\textit{n}}\) demes consisting of one continent and \(n-1\) islands. We assume viability differences in the population captured by a linear game within each deme as a result of pairwise interactions. Assuming weak selection, conservative migration and the limit case of the structured coalescent assumptions, we derive the first-order approximation for the fixation probability of a single mutant, initially introduced in the continent, with respect to the intensity of selection. This result is applied to the case of the iterated Prisoner’s Dilemma, when the resident strategy is always defect and the mutant cooperative strategy is tit-for-tat. In this context, we investigate the condition under which selection favors the emergence of cooperation and we derive an extension of the “one-third law” of evolution. When the continent and the islands are of the same size, we compare the continental island model to its Wright’s island model counterpart. When the islands have the same size, but this size differs from the size of the continent, we investigate how the asymmetry in the deme sizes can better promote the evolution of tit-for-tat compared to its equal deme sizes model counterpart.

The response of a metapopulation to a changing environment.

A species distributed across diverse environments may adapt to local conditions. We ask how quickly such a species changes its range in response to changed conditions. Szép et al. (Szép E, Sachdeva H, Barton NH. 2021 Polygenic local adaptation in metapopulations: a stochastic eco-evolutionary model. Evolution 75, 1030–1045 (doi:10.1111/evo.14210)) used the infinite island model to find the stationary distribution of allele frequencies and deme sizes. We extend this to find how a metapopulation responds to changes in carrying capacity, selection strength, or migration rate when deme sizes are fixed. We further develop a ‘fixed-state’ approximation. Under this approximation, polymorphism is only possible for a narrow range of habitat proportions when selection is weak compared to drift, but for a much wider range otherwise. When rates of selection or migration relative to drift change in a single deme of the metapopulation, the population takes a time of order m−1 to reach the new equilibrium. However, even with many loci, there can be substantial fluctuations in net adaptation, because at each locus, alleles randomly get lost or fixed. Thus, in a finite metapopulation, variation may gradually be lost by chance, even if it would persist in an infinite metapopulation. When conditions change across the whole metapopulation, there can be rapid change, which is predicted well by the fixed-state approximation. This work helps towards an understanding of how metapopulations extend their range across diverse environments.This article is part of the theme issue ‘Species’ ranges in the face of changing environments (Part II)’.

Demographic history shapes genomic ancestry in hybrid zones.

Demographic factors such as migration rate and population size can impede or facilitate speciation. In hybrid zones, reproductive boundaries between species are tested and demography mediates the opportunity for admixture between lineages that are partially isolated. Genomic ancestry is a powerful tool for revealing the history of admixed populations, but models and methods based on local ancestry are rarely applied to structured hybrid zones. To understand the effects of demography on ancestry in hybrids zones, we performed individual‐based simulations under a stepping‐stone model, treating migration rate, deme size, and hybrid zone age as parameters. We find that the number of ancestry junctions (the transition points between genomic regions with different ancestries) and heterogenicity (the genomic proportion heterozygous for ancestry) are often closely connected to demographic history. Reducing deme size reduces junction number and heterogenicity. Elevating migration rate increases heterogenicity, but migration affects junction number in more complex ways. We highlight the junction frequency spectrum as a novel and informative summary of ancestry that responds to demographic history. A substantial proportion of junctions are expected to fix when migration is limited or deme size is small, changing the shape of the spectrum. Our findings suggest that genomic patterns of ancestry could be used to infer demographic history in hybrid zones.

A narrow window for geographic cline analysis using genomic data: Effects of age, drift, and migration on error rates.

The use of genomic and phenotypic data to scan for outliers is a mainstay for studies of hybridization and speciation. Geographic cline analysis of natural hybrid zones is widely used to identify putative signatures of selection by detecting deviations from baseline patterns of introgression. As with other outlier-based approaches, demographic histories can make neutral regions appear to be under selection and vice versa. In this study, we use a forward-time individual-based simulation approach to evaluate the robustness of geographic cline analysis under different evolutionary scenarios. We modelled multiple stepping-stone hybrid zones with distinct age, deme sizes, and migration rates, and evolving under different types of selection. We found that drift distorts cline shapes and increases false positive rates for signatures of selection. This effect increases with hybrid zone age, particularly if migration between demes is low. Drift can also distort the signature of deleterious effects of hybridization, with genetic incompatibilities and particularly underdominance prone to spurious typing as adaptive introgression. Our results suggest that geographic clines are most useful for outlier analysis in young hybrid zones with large populations of hybrid individuals. Current approaches may overestimate adaptive introgression and underestimate selection against maladaptive genotypes.

Imperfect Strategy Transmission Can Reverse the Role of Population Viscosity on the Evolution of Altruism

Population viscosity, i.e., low emigration out of the natal deme, leads to high within-deme relatedness, which is beneficial to the evolution of altruistic behavior when social interactions take place among deme-mates. However, a detrimental side effect of low emigration is the increase in competition among related individuals. The evolution of altruism depends on the balance between these opposite effects. This balance is already known to be affected by details of the life cycle; we show here that it further depends on the fidelity of strategy transmission from parents to their offspring. We consider different life cycles and identify thresholds of parent–offspring strategy transmission inaccuracy, above which higher emigration can increase the frequency of altruists maintained in the population. Predictions were first obtained analytically assuming weak selection and equal deme sizes and then confirmed with stochastic simulations relaxing these assumptions. Contrary to what happens with perfect strategy transmission from parent to offspring, our results show that higher emigration can be favorable to the evolution of altruism.

The IICR and the non-stationary structured coalescent: towards demographic inference with arbitrary changes in population structure

In the last years, a wide range of methods allowing to reconstruct past population size changes from genome-wide data have been developed. At the same time, there has been an increasing recognition that population structure can generate genetic data similar to those produced under models of population size change. Recently, Mazet et al. (Heredity 116:362–371, 2016) showed that, for any model of population structure, it is always possible to find a panmictic model with a particular function of population size changes, having exactly the same distribution of T2 (the coalescence time for a sample of size two) as that of the structured model. They called this function IICR (Inverse Instantaneous Coalescence Rate) and showed that it does not necessarily correspond to population size changes under non-panmictic models. Besides, most of the methods used to analyse data under models of population structure tend to arbitrarily fix that structure and to minimise or neglect population size changes. Here, we extend the seminal work of Herbots (PhD thesis, University of London, 1994) on the structured coalescent and propose a new framework, the Non-Stationary Structured Coalescent (NSSC) that incorporates demographic events (changes in gene flow and/or deme sizes) to models of nearly any complexity. We show how to compute the IICR under a wide family of stationary and non-stationary models. As an example we address the question of human and Neanderthal evolution and discuss how the NSSC framework allows to interpret genomic data under this new perspective.

Does Population Structure Predict the Rate of Speciation? A Comparative Test across Australia's Most Diverse Vertebrate Radiation.

Population divergence is the first step in allopatric speciation, as has long been recognized in both theoretical models of speciation and empirical explorations of natural systems. All else being equal, lineages with substantial population differentiation should form new species more quickly than lineages that maintain range-wide genetic cohesion through high levels of gene flow. However, there have been few direct tests of the extent to which population differentiation predicts speciation rates as measured on phylogenetic trees. Here, we explicitly test the links between organismal traits, population-level processes, and phylogenetic speciation rates across a diverse clade of Australian lizards that shows remarkable variation in speciation rate. Using genome-wide double digest restriction site-associated DNA data from 892 individuals, we generated a comparative data set on isolation by distance and population differentiation across 104 putative species-level lineages (operational taxonomic units). We find that species show substantial variation in the extent of population differentiation, and this variation is predicted by organismal traits that are thought to be proxies for dispersal and deme size. However, variation in population structure does not predict variation in speciation rate. Our results suggest that population differentiation is not the rate-limiting step in species formation and that other ecological and historical factors are primary determinants of speciation rates at macroevolutionary scales.

Distribution of natal dispersal distances and the genetic structure of Spruce Grouse (Falcipennis canadensis) populations

Natal dispersal distances are difficult to measure, yet important for estimating the genetic structure and demographic connectedness of natural populations. Here we provide estimates of the distributions of male and female natal dispersal distances from a long-term study of Spruce Grouse (Falcipennis canadensis (L., 1758)) in southwestern Alberta, Canada, based on individuals marked as brood chicks and re-observed as adults during subsequent breeding seasons. The mean distance dispersed by females (2.33 km) was twice that of males (1.13 km), and both dispersal distributions were leptokurtic. Given estimates of population density and survivorship, we estimated the genetic effective neighborhood size of this population as approximately 541 individuals. We computed equivalent estimates for two additional long-term studies of this species, based on data available in the literature; mean natal dispersal distances, averaged across sexes, ranged from 1.73 to 2.73 km for the three populations; effective deme sizes ranged from 541 to 890. Consequently, three widespread populations of Spruce Grouse yielded roughly similar estimates of demographic and genetic structure.

Predicting the genetic consequences of future climate change: The power of coupling spatial demography, the coalescent, and historical landscape changes.

Climate change is a widely accepted threat to biodiversity. Species distribution models (SDMs) are used to forecast whether and how species distributions may track these changes. Yet, SDMs generally fail to account for genetic and demographic processes, limiting population-level inferences. We still do not understand how predicted environmental shifts will impact the spatial distribution of genetic diversity within taxa. We propose a novel method that predicts spatially explicit genetic and demographic landscapes of populations under future climatic conditions. We use carefully parameterized SDMs as estimates of the spatial distribution of suitable habitats and landscape dispersal permeability under present-day, past, and future conditions. We use empirical genetic data and approximate Bayesian computation to estimate unknown demographic parameters. Finally, we employ these parameters to simulate realistic and complex models of responses to future environmental shifts. We contrast parameterized models under current and future landscapes to quantify the expected magnitude of change. We implement this framework on neutral genetic data available from Penstemon deustus. Our results predict that future climate change will result in geographically widespread declines in genetic diversity in this species. The extent of reduction will heavily depend on the continuity of population networks and deme sizes. To our knowledge, this is the first study to provide spatially explicit predictions of within-species genetic diversity using climatic, demographic, and genetic data. Our approach accounts for climatic, geographic, and biological complexity. This framework is promising for understanding evolutionary consequences of climate change, and guiding conservation planning.

Genetic variation and population structure of American mink Neovison vison from PCB-contaminated and non-contaminated locales in eastern North America.

American mink Neovison vison may be particularly vulnerable to toxicities of persistent contaminants such as PCBs because of their aquatic-based diet, position near the top of the food web, and small deme sizes. Furthermore, ranched mink are sensitive to reproductive toxicities of fish diets from PCB-polluted sites. The upper Hudson River is highly contaminated with PCBs and previous studies have shown elevated hepatic burdens of total and coplanar PCBs in mink collected near the river compared with those from more distant locales in New York and elsewhere. We hypothesized that bioaccumulation of PCBs in Hudson River mink has reduced their levels of genetic diversity or altered their genetic population structure. To address this, we conducted microsatellite DNA analysis on collections made in proximity to and from more distant locales in the Hudson River watershed, elsewhere in New York State, and at other sites in eastern North America including New Brunswick, four locales in Ontario, multiple drainages in Maine, and two ecoregions in Rhode Island. We did not find reduced genetic diversity at the individual or population levels in mink collected near (<6 km) to PCB hotspots in the Hudson River nor evidence of altered population structure. Consistent with their distribution in small localized and isolated demes, we did find significant genetic population structure among many mink collections in New York State and elsewhere. Depending on the analytical approach used, genetically distinct populations numbered between 16 when using STRUCTURE to 19-20 when using Exact G tests, F ST, or AMOVA analyses. Genetically distinct population units were found among major ecoregions and minor ecoregions in New York State, among different hydrologic subunits within the Hudson River watershed, among spatially separate locales in Ontario, and among most watersheds in Maine. However, despite this localization and potential heightened impact of stressors, genetic diversity and genetic population structure in mink does not seem to be affected by their bioaccumulation of high levels of PCBs of Hudson River origin.

Modelling the evolution and expected lifetime of a deme’s principal gene sequence

The principal gene sequence (PGS), defined as the most common gene sequence in a deme, is replaced over time because new gene sequences are created and compete with the current PGS, and a small fraction become PGSs. We have developed a set of coupled difference equations to represent an ensemble of demes, in which new gene sequences are introduced via chromosomal inversions. The set of equations used to calculate the expected lifetime of an existing PGS include inversion size and rate, recombination rate and deme size. Inversion rate and deme size effects are highlighted in this work. Our results compare favourably with a cellular automaton-based representation of a deme.

Outbreeding effects in an inbreeding insect, Cimex lectularius

In some species, populations with few founding individuals can be resilient to extreme inbreeding. Inbreeding seems to be the norm in the common bed bug, Cimex lectularius, a flightless insect that, nevertheless, can reach large deme sizes and persist successfully. However, bed bugs can also be dispersed passively by humans, exposing inbred populations to gene flow from genetically distant populations. The introduction of genetic variation through this outbreeding could lead to increased fitness (heterosis) or be costly by causing a loss of local adaptation or exposing genetic incompatibility between populations (outbreeding depression). Here, we addressed how inbreeding within demes and outbreeding between distant populations impact fitness over two generations in this re-emerging public health pest. We compared fitness traits of families that were inbred (mimicking reproduction following a founder event) or outbred (mimicking reproduction following a gene flow event). We found that outbreeding led to increased starvation resistance compared to inbred families, but this benefit was lost after two generations of outbreeding. No other fitness benefits of outbreeding were observed in either generation, including no differences in fecundity between the two treatments. Resilience to inbreeding is likely to result from the history of small founder events in the bed bug. Outbreeding benefits may only be detectable under stress and when heterozygosity is maximized without disruption of coadaptation. We discuss the consequences of these results both in terms of inbreeding and outbreeding in populations with genetic and spatial structuring, as well as for the recent resurgence of bed bug populations.

Coalescent simulation in continuous space: Algorithms for large neighbourhood size

Many species have an essentially continuous distribution in space, in which there are no natural divisions between randomly mating subpopulations. Yet, the standard approach to modelling these populations is to impose an arbitrary grid of demes, adjusting deme sizes and migration rates in an attempt to capture the important features of the population. Such indirect methods are required because of the failure of the classical models of isolation by distance, which have been shown to have major technical flaws. A recently introduced model of extinction and recolonisation in two dimensions solves these technical problems, and provides a rigorous technical foundation for the study of populations evolving in a spatial continuum. The coalescent process for this model is simply stated, but direct simulation is very inefficient for large neighbourhood sizes. We present efficient and exact algorithms to simulate this coalescent process for arbitrary sample sizes and numbers of loci, and analyse these algorithms in detail.

THE EFFECT OF COLLECTIVE DISPERSAL ON THE GENETIC STRUCTURE OF A SUBDIVIDED POPULATION

Correlated dispersal paths between two or more individuals are widespread across many taxa. The population genetic implications of this collective dispersal have received relatively little attention. Here we develop two-sample coalescent theory that incorporates collective dispersal in a finite island model to predict expected coalescence times, genetic diversities, and F-statistics. We show that collective dispersal reduces mixing in the system, which decreases expected coalescence times and increases FST . The effects are strongest in systems with high migration rates. Collective dispersal breaks the invariance of within-deme coalescence times to migration rate, whatever the deme size. It can also cause FST to increase with migration rate because the ratio of within- to between-deme coalescence times can decrease as migration rate approaches unity. This effect is most biologically relevant when deme size is small. We find qualitatively similar results for diploid and gametic dispersal. We also demonstrate with simulations and analytical theory the strong similarity between the effects of collective dispersal and anisotropic dispersal. These findings have implications for our understanding of the balance between drift-migration-mutation in models of neutral evolution. This has applied consequences for the interpretation of genetic structure (e.g., chaotic genetic patchiness) and estimation of migration rates from genetic data.

The role of colonization in the dynamics of patchy populations of a cyclic vole species

The crash phase of vole populations with cyclic dynamics regularly leads to vast areas of uninhabited habitats. Yet although the capacity for cyclic voles to re-colonize such empty space is likely to be large and predicted to have become evolved as a distinct life history trait, the processes of colonization and its effect on the spatio-temporal dynamics have been little studied. Here we report from an experiment with root voles (Microtus oeconomus) specifically targeted at quantifying the process of colonization of empty patches from distant source patches and its resultant effect on local vole deme size variation in a patchy landscape. Three experimental factors: habitat quality, predation risk and inter-patch distance were employed among 24 habitat patches in a 100 × 300-m experimental area. The first-born cohort in the spring efficiently colonized almost all empty patches irrespective of the degree of patch isolation and predation risk, but this was dependent on habitat quality. Just after the initial colonization wave the deme sizes in patches of the same quality were underdispersed relative to Poisson variance, indicating regulated (density-dependent) settlement. Towards the end of the breeding season local demographic processes acted to smooth out the initial post-colonization differences among source and colonization patches, and among patches of initially different quality. However, at this time demographic stochasticity had also given rise to a large (overdispersed) variation in deme sizes that may have contributed to an overshadowing of the effect of other factors. The results of this experiment confirmed our expectation that the space-filling capacity of voles is large. The costs associated with transience appeared to be so low, at least at the spatial scale considered in this experiment, that such costs are not likely to substantially constrain habitat selection and colonization in the increase phase of cyclic patchy populations.

THE DYNAMICS OF MITOCHONDRIAL MUTATIONS CAUSING MALE INFERTILITY IN SPATIALLY STRUCTURED POPULATIONS

Mitochondrial genomes are usually inherited maternally and therefore there is no direct selection against mutations that have deleterious effects in males only (mother's curse). This is true in particular for mitochondrial mutations that reduce the fertility of their male carriers, as has been reported in a number of species. Using both analytical methods and computer simulations, we demonstrate that spatial population structure can induce strong selection against such male infertility mutations. This is because (1) infertile males may reduce the fecundity of the females they mate with and (2) population structure induces increased levels of inbreeding, so that the fitness of females carrying the mutation is more strongly reduced than the fitness of wild-type females. Selection against mitochondrial male infertility mutations increases with decreasing deme size and migration rates, and in particular with female migration rates. On the other hand, the migration model (e.g., island or stepping stone model) has generally only minor effects on the fate of the mitochondrial mutations.