Effective population size of natural populations of Drosophila buzzatii, with a comparative evaluation of nine methods of estimation

Recent Changes in Genetic Diversity, Structure, and Gene Flow in a Passerine Experiencing a Rapid Population Decline, the Dupont’s Lark (Chersophilus duponti)

Monitoring temporal dynamics in genetic diversity is of great importance for conservation, especially for threatened species that are suffering a rapid population decline and increased fragmentation. Here, we investigate temporal variation in genetic diversity, structure, and gene flow in the Dupont’s lark (Chersophilus duponti) across most of its range. This species shows increasing levels of population fragmentation, substantial population declines, and severe range contraction, so temporal losses of genetic diversity, increasing differentiation, and decreasing gene flow are expected when comparing present day data with previous situations. To address this, we resampled sites (nine regions in two countries) after 12–15 years (five-to-seven generations) and assessed changes in genetic parameters using 11 microsatellite markers. We found no substantial loss in genetic diversity over time at the species level, but we detected considerable variation among regions in the amount of allelic diversity and heterozygosity lost over time. Temporal variation in allele frequencies (common, rare, and private alleles), and changes in genetic differentiation and gene flow over time suggest a major role of connectivity for the stability of the overall metapopulation. Our results agree with the hypothesis that connectivity rescues genetic diversity via immigration and gene flow. However, evidence of recent genetic bottleneck and the substantial changes detected in some regions are clear signs of genetic erosion and may be signalling a rapid decline of the populations. Urgent actions must be carried out to stop and reverse human impacts on this threatened lark and its habitat.

Temporal Analysis of Effective Population Size and Mating System in a Social Wasp

Highly social species are successful because they cooperate in obligately integrated societies. We examined temporal genetic variation in the eusocial wasp Vespula maculifrons to gain a greater understanding of evolution in highly social taxa. First, we wished to test if effective population sizes of eusocial species were relatively low due to the reproductive division of labor that characterizes eusocial taxa. We thus estimated the effective population size of V. maculifrons by examining temporal changes in population allele frequencies. We sampled the genetic composition of a V. maculifrons population at 3 separate timepoints spanning a 13-year period. We found that effective population size ranged in the hundreds of individuals, which is similar to estimates in other, non-eusocial taxa. Second, we estimated levels of polyandry in V. maculifrons in different years to determine if queen mating system varied over time. We found no significant change in the number or skew of males mated to queens. In addition, mating skew was not significant within V. maculifrons colonies. Therefore, our data suggest that queen mate number may be subject to stabilizing selection in this taxon. Overall, our study provides novel insight into the selective processes operating in eusocial species by analyzing temporal genetic changes within populations.

A brief history and popularity of methods and tools used to estimate micro-evolutionary forces

Population genetics is a field of research that predates the current generations of sequencing technology. Those approaches, that were established before massively parallel sequencing methods, have been adapted to these new marker systems (in some cases involving the development of new methods) that allow genome-wide estimates of the four major micro-evolutionary forces-mutation, gene flow, genetic drift, and selection. Nevertheless, classic population genetic markers are still commonly used and a plethora of analysis methods and programs is available for these and high-throughput sequencing (HTS) data. These methods employ various and diverse theoretical and statistical frameworks, to varying degrees of success, to estimate similar evolutionary parameters making it difficult to get a concise overview across the available approaches. Presently, reviews on this topic generally focus on a particular class of methods to estimate one or two evolutionary parameters. Here, we provide a brief history of methods and a comprehensive list of available programs for estimating micro-evolutionary forces. We furthermore analyzed their usage within the research community based on popularity (citation bias) and discuss the implications of this bias for the software community. We found that a few programs received the majority of citations, with program success being independent of both the parameters estimated and the computing platform. The only deviation from a model of exponential growth in the number of citations was found for the presence of a graphical user interface (GUI). Interestingly, no relationship was found for the impact factor of the journals, when the tools were published, suggesting accessibility might be more important than visibility.

Drosophila Interspecific Hybridization Causes A Deregulation of the piRNA Pathway Genes

Almost all eukaryotes have transposable elements (TEs) against which they have developed defense mechanisms. In the Drosophila germline, the main transposable element (TE) regulation pathway is mediated by specific Piwi-interacting small RNAs (piRNAs). Nonetheless, for unknown reasons, TEs sometimes escape cellular control during interspecific hybridization processes. Because the piRNA pathway genes are involved in piRNA biogenesis and TE control, we sequenced and characterized nine key genes from this pathway in Drosophila buzzatii and Drosophila koepferae species and studied their expression pattern in ovaries of both species and their F1 hybrids. We found that gene structure is, in general, maintained between both species and that two genes—armitage and aubergine—are under positive selection. Three genes—krimper, methyltransferase 2, and zucchini—displayed higher expression values in hybrids than both parental species, while others had RNA levels similar to the parental species with the highest expression. This suggests that the overexpression of some piRNA pathway genes can be a primary response to hybrid stress. Therefore, these results reinforce the hypothesis that TE deregulation may be due to the protein incompatibility caused by the rapid evolution of these genes, leading to a TE silencing failure, rather than to an underexpression of piRNA pathway genes.

neogen: A tool to predict genetic effective population size (Ne ) for species with generational overlap and to assist empirical Ne study design

Molecular genetic estimates of population effective size (N_e ) lose accuracy and precision when insufficient numbers of samples or loci are used. Ideally, researchers would like to forecast the necessary power when planning their project. neogen (genetic N_e for Overlapping Generations) enables estimates of precision and accuracy in advance of empirical investigation and allows exploration of the power available in different user-specified age-structured sampling schemes. neogen provides a population simulation and genetic power analysis framework that simulates the demographics, genetic composition, and N_e , from species-specific life history, mortality, population size, and genetic priors. neogen guides the user to establish a tractable sampling regime and to determine the numbers of samples and microsatellite or SNP loci required for accurate and precise genetic N_e estimates when sampling a natural population. neogen is useful at multiple stages of a study's life cycle: when budgeting, as sampling and locus development progresses, and for corroboration when empirical N_e estimates are available. The underlying model is applicable to a wide variety of iteroparous species with overlapping generations (e.g., mammals, birds, reptiles, long-lived fishes). In this paper, we describe the neogen model, detail the workflow for the point-and-click software, and explain the graphical results. We demonstrate the use of neogen with empirical Australian east coast zebra shark (Stegostoma fasciatum) data. For researchers wishing to make accurate and precise genetic N_e estimates for overlapping generations species, neogen facilitates planning for sample and locus acquisition, and with existing empirical genetic N_e estimates neogen can corroborate population demographic and life history properties.

Genetic and genomic monitoring with minimally invasive sampling methods

The decreasing cost and increasing scope and power of emerging genomic technologies are reshaping the field of molecular ecology. However, many modern genomic approaches (e.g., RAD-seq) require large amounts of high-quality template DNA. This poses a problem for an active branch of conservation biology: genetic monitoring using minimally invasive sampling (MIS) methods. Without handling or even observing an animal, MIS methods (e.g., collection of hair, skin, faeces) can provide genetic information on individuals or populations. Such samples typically yield low-quality and/or quantities of DNA, restricting the type of molecular methods that can be used. Despite this limitation, genetic monitoring using MIS is an effective tool for estimating population demographic parameters and monitoring genetic diversity in natural populations. Genetic monitoring is likely to become more important in the future as many natural populations are undergoing anthropogenically driven declines, which are unlikely to abate without intensive adaptive management efforts that often include MIS approaches. Here, we profile the expanding suite of genomic methods and platforms compatible with producing genotypes from MIS, considering factors such as development costs and error rates. We evaluate how powerful new approaches will enhance our ability to investigate questions typically answered using genetic monitoring, such as estimating abundance, genetic structure and relatedness. As the field is in a period of unusually rapid transition, we also highlight the importance of legacy data sets and recommend how to address the challenges of moving between traditional and next-generation genetic monitoring platforms. Finally, we consider how genetic monitoring could move beyond genotypes in the future. For example, assessing microbiomes or epigenetic markers could provide a greater understanding of the relationship between individuals and their environment.

A century of temporal stability of genetic diversity in wild bumblebees

Since the 1950s, bumblebee (Bombus) species are showing a clear decline worldwide. Although many plausible drivers have been hypothesized, the cause(s) of this phenomenon remain debated. Here, genetic diversity in recent versus historical populations of bumblebee species was investigated by selecting four currently restricted and four currently widespread species. Specimens from five locations in Belgium were genotyped at 16 microsatellite loci, comparing historical specimens (1913–1915) with recent ones (2013–2015). Surprisingly, our results showed temporal stability of genetic diversity in the restricted species. Furthermore, both historical and recent populations of restricted species showed a significantly lower genetic diversity than found in populations of co-occurring widespread species. The difference in genetic diversity between species was thus already present before the alleged recent drivers of bumblebee decline could have acted (from the 1950’s). These results suggest that the alleged drivers are not directly linked with the genetic variation of currently declining bumblebee populations. A future sampling in the entire distribution range of these species will infer if the observed link between low genetic diversity and population distribution on the Belgium scale correlates with species decline on a global scale.

A longitudinal genetic survey identifies temporal shifts in the population structure of Dutch house sparrows

Dutch house sparrow (Passer domesticus) densities dropped by nearly 50% since the early 1980s, and similar collapses in population sizes have been reported across Europe. Whether, and to what extent, such relatively recent demographic changes are accompanied by concomitant shifts in the genetic population structure of this species needs further investigation. Therefore, we here explore temporal shifts in genetic diversity, genetic structure and effective sizes of seven Dutch house sparrow populations. To allow the most powerful statistical inference, historical populations were resampled at identical locations and each individual bird was genotyped using nine polymorphic microsatellites. Although the demographic history was not reflected by a reduction in genetic diversity, levels of genetic differentiation increased over time, and the original, panmictic population (inferred from the museum samples) diverged into two distinct genetic clusters. Reductions in census size were supported by a substantial reduction in effective population size, although to a smaller extent. As most studies of contemporary house sparrow populations have been unable to identify genetic signatures of recent population declines, results of this study underpin the importance of longitudinal genetic surveys to unravel cryptic genetic patterns.

Assessing performance of single-sample molecular genetic methods to estimate effective population size: empirical evidence from the endangered Gochu Asturcelta pig breed

Estimating effective population size (N_e) using linkage disequilibrium (LD) information (N_e(LD)) has the operational advantage of using a single sample. However, N_e(LD) estimates assume discrete generations and its performance are constrained by demographic issues. However, such concerns have received little empirical attention so far. The pedigree of the endangered Gochu Asturcelta pig breed includes individuals classified into discrete filial generations and individuals with generations overlap. Up to 780 individuals were typed with a set of 17 microsatellites. Performance of N_e(LD) was compared with N_e estimates obtained using genealogical information, molecular coancestry (N_e(M)) and a temporal (two‐sample) method (N_e(JR)). Molecular‐based estimates of N_e exceeded those obtained using pedigree data. Estimates of N_e(LD) for filial generations F3 and F4 (17.0 and 17.3, respectively) were lower and steadier than those obtained using yearly or biannual samplings. N_e(LD) estimated for samples including generations overlap could only be compared with those obtained for the discrete filial generations when sampling span approached a generation interval and demographic correction for bias was applied. Single‐sample N_e(M) estimates were lower than their N_e(LD) counterparts. N_e(M) estimates are likely to partially reflect the number of founders rather than population size. In any case, estimates of LD and molecular coancestry tend to covary and, therefore, N_e(M) and N_e(LD) can hardly be considered independent. Demographically adjusted estimates of N_e(JR) and N_e(LD) took comparable values when: (1) the two samples used for the former were separated by one equivalent to discrete generations in the pedigree and (2) sampling span used for the latter approached a generation interval. Overall, the empirical evidence given in this study suggested that the advantage of using single‐sample methods to obtain molecular‐based estimates of N_e is not clear in operational terms. Estimates of N_e obtained using methods based in molecular information should be interpreted with caution.

Estimating the Effective Population Size from Temporal Allele Frequency Changes in Experimental Evolution

The effective population size (Ne) is a major factor determining allele frequency changes in natural and experimental populations. Temporal methods provide a powerful and simple approach to estimate short-term Ne. They use allele frequency shifts between temporal samples to calculate the standardized variance, which is directly related to Ne. Here we focus on experimental evolution studies that often rely on repeated sequencing of samples in pools (Pool-seq). Pool-seq is cost-effective and often outperforms individual-based sequencing in estimating allele frequencies, but it is associated with atypical sampling properties: Additional to sampling individuals, sequencing DNA in pools leads to a second round of sampling, which increases the variance of allele frequency estimates. We propose a new estimator of Ne, which relies on allele frequency changes in temporal data and corrects for the variance in both sampling steps. In simulations, we obtain accurate Ne estimates, as long as the drift variance is not too small compared to the sampling and sequencing variance. In addition to genome-wide Ne estimates, we extend our method using a recursive partitioning approach to estimate Ne locally along the chromosome. Since the type I error is controlled, our method permits the identification of genomic regions that differ significantly in their Ne estimates. We present an application to Pool-seq data from experimental evolution with Drosophila and provide recommendations for whole-genome data. The estimator is computationally efficient and available as an R package at https://github.com/ThomasTaus/Nest.

Stock enhancement or sea ranching? Insights from monitoring the genetic diversity, relatedness and effective population size in a seeded great scallop population (Pecten maximus)

The mass release of hatchery-propagated stocks raises numerous questions concerning its efficiency in terms of local recruitment and effect on the genetic diversity of wild populations. A seeding program, consisting of mass release of hatchery-produced juveniles in the local naturally occurring population of great scallops (Pecten maximus L.), was initiated in the early 1980s in the Bay of Brest (France). The present study aims at evaluating whether this seeding program leads to actual population enhancement, with detectable effects on genetic diversity and effective population size, or consists of sea ranching with limited genetic consequences on the wild stock. To address this question, microsatellite-based genetic monitoring of three hatchery-born and naturally recruited populations was conducted over a 5-year period. Results showed a limited reduction in allelic richness but a strong alteration of allelic frequencies in hatchery populations, while genetic diversity appeared very stable over time in the wild populations. A temporal increase in relatedness was observed in both cultured stock and wild populations. Effective population size (Ne) estimates were low and variable in the wild population. Moreover, the application of the Ryman-Laikre model suggested a high contribution of hatchery-born scallops to the reproductive output of the wild population. Overall, the data suggest that the main objective of the seeding program, which is stock enhancement, is fulfilled. Moreover, gene flow from surrounding populations and/or the reproductive input of undetected sub-populations within the bay may buffer the Ryman-Laikre effect and ensure the retention of the local genetic variability.

Challenging the inbreeding hypothesis in a eusocial mammal: population genetics of the naked mole-rat, Heterocephalus glaber

The role of genetic relatedness in the evolution of eusociality has been the topic of much debate, especially when contrasting eusocial insects with vertebrates displaying reproductive altruism. The naked mole-rat, Heterocephalus glaber, was the first described eusocial mammal. Although this discovery was based on an ecological constraints model of eusocial evolution, early genetic studies reported high levels of relatedness in naked mole-rats, providing a compelling argument that low dispersal rates and consanguineous mating (inbreeding as a mating system) are the driving forces for the evolution of this eusocial species. One caveat to accepting this long-held view is that the original genetic studies were based on limited sampling from the species' geographic distribution. A growing body of evidence supports a contrary view, with the original samples not representative of the species-rather reflecting a single founder event, establishing a small population south of the Athi River. Our study is the first to address these competing hypotheses by examining patterns of molecular variation in colonies sampled from north and south of the Athi and Tana rivers, which based on our results, serve to isolate genetically distinct populations of naked mole-rats. Although colonies south of the Athi River share a single mtDNA haplotype and are fixed at most microsatellite loci, populations north of the Athi River are considerably more variable. Our findings support the position that the low variation observed in naked mole-rat populations south of the Athi River reflects a founder event, rather than a consequence of this species' unusual mating system.

Temporal stability of genetic variability and differentiation in the three-spined stickleback (Gasterosteus aculeatus)

Temporal variation in allele frequencies, whether caused by deterministic or stochastic forces, can inform us about interesting demographic and evolutionary phenomena occurring in wild populations. In spite of the continued surge of interest in the genetics of three-spined stickleback (Gasterosteus aculeatus) populations, little attention has been paid towards the temporal stability of allele frequency distributions, and whether there are consistent differences in effective size (Ne) of local populations. We investigated temporal stability of genetic variability and differentiation in 15 microsatellite loci within and among eight collection sites of varying habitat type, surveyed twice over a six-year time period. In addition, Nes were estimated with the expectation that they would be lowest in isolated ponds, intermediate in larger lakes and largest in open marine sites. In spite of the marked differences in genetic variability and differentiation among the study sites, the temporal differences in allele frequencies, as well as measures of genetic diversity and differentiation, were negligible. Accordingly, the Ne estimates were temporally stable, but tended to be lower in ponds than in lake or marine habitats. Hence, we conclude that allele frequencies in putatively neutral markers in three-spined sticklebacks seem to be temporally stable - at least over periods of few generations - across a wide range of habitat types differing markedly in levels of genetic variability, effective population size and gene flow.

Post-fragmentation population structure in a cooperative breeding Afrotropical cloud forest bird: emergence of a source-sink population network

The impact of demographic parameters on the genetic population structure and viability of organisms is a long-standing issue in the study of fragmented populations. Demographic and genetic tools are now readily available to estimate census and effective population sizes and migration and gene flow rates with increasing precision. Here we analysed the demography and genetic population structure over a recent 15-year time span in five remnant populations of Cabanis's greenbul (Phyllastrephus cabanisi), a cooperative breeding bird in a severely fragmented cloud forest habitat. Contrary to our expectation, genetic admixture and effective population sizes slightly increased, rather than decreased between our two sampling periods. In spite of small effective population sizes in tiny forest remnants, none of the populations showed evidence of a recent population bottleneck. Approximate Bayesian modelling, however, suggested that differentiation of the populations coincided at least partially with an episode of habitat fragmentation. The ratio of meta-Ne to meta-Nc was relatively low for birds, which is expected for cooperative breeding species, while Ne /Nc ratios strongly varied among local populations. While the overall trend of increasing population sizes and genetic admixture may suggest that Cabanis's greenbuls increasingly cope with fragmentation, the time period over which these trends were documented is rather short relative to the average longevity of tropical species. Furthermore, the critically low Nc in the small forest remnants keep the species prone to demographic and environmental stochasticity, and it remains open if, and to what extent, its cooperative breeding behaviour helps to buffer such effects.

Challenges in analysis and interpretation of microsatellite data for population genetic studies

Advancing technologies have facilitated the ever-widening application of genetic markers such as microsatellites into new systems and research questions in biology. In light of the data and experience accumulated from several years of using microsatellites, we present here a literature review that synthesizes the limitations of microsatellites in population genetic studies. With a focus on population structure, we review the widely used fixation (F ST) statistics and Bayesian clustering algorithms and find that the former can be confusing and problematic for microsatellites and that the latter may be confounded by complex population models and lack power in certain cases. Clustering, multivariate analyses, and diversity-based statistics are increasingly being applied to infer population structure, but in some instances these methods lack formalization with microsatellites. Migration-specific methods perform well only under narrow constraints. We also examine the use of microsatellites for inferring effective population size, changes in population size, and deeper demographic history, and find that these methods are untested and/or highly context-dependent. Overall, each method possesses important weaknesses for use with microsatellites, and there are significant constraints on inferences commonly made using microsatellite markers in the areas of population structure, admixture, and effective population size. To ameliorate and better understand these constraints, researchers are encouraged to analyze simulated datasets both prior to and following data collection and analysis, the latter of which is formalized within the approximate Bayesian computation framework. We also examine trends in the literature and show that microsatellites continue to be widely used, especially in non-human subject areas. This review assists with study design and molecular marker selection, facilitates sound interpretation of microsatellite data while fostering respect for their practical limitations, and identifies lessons that could be applied toward emerging markers and high-throughput technologies in population genetics.

Pleiotropic mutations are subject to strong stabilizing selection

The assumption that pleiotropic mutations are more deleterious than mutations with more restricted phenotypic effects is an important premise in models of evolution. However, empirical evidence supporting this assumption is limited. Here, we estimated the strength of stabilizing selection on mutations affecting gene expression in male Drosophila serrata. We estimated the mutational variance (VM) and the standing genetic variance (VG) from two well-matched panels of inbred lines: a panel of mutation accumulation (MA) lines derived from a single inbred ancestral line and a panel of inbred lines derived from an outbred population. For 855 gene-expression traits, we estimated the strength of stabilizing selection as s = VM/VG. Selection was observed to be relatively strong, with 17% of traits having s > 0.02, a magnitude typically associated with life-history traits. Randomly assigning expression traits to five-trait sets, we used factor analytic mixed modeling in the MA data set to identify covarying traits that shared pleiotropic mutations. By assigning traits to the same trait sets in the outbred line data set, we then estimated s for the combination of traits affected by pleiotropic mutation. For these pleiotropic combinations, the median s was three times greater than s acting on the individual component traits, and 46% of the pleiotropic trait combinations had s > 0.02. Although our analytical approach was biased toward detecting mutations with relatively large effects, likely overestimating the average strength of selection, our results provide widespread support for the prediction that stronger selection can act against mutations with pleiotropic effects.

Gene flow and demographic history of leopards (Panthera pardus) in the central Indian highlands

Gene flow is a critical ecological process that must be maintained in order to counteract the detrimental effects of genetic drift in subdivided populations, with conservation benefits ranging from promoting the persistence of small populations to spreading adaptive traits in changing environments. We evaluated historical and contemporary gene flow and effective population sizes of leopards in a landscape in central India using noninvasive sampling. Despite the dramatic changes in land-use patterns in this landscape through recent times, we did not detect any signs that the leopard populations have been through a genetic bottleneck, and they appear to have maintained migration-drift equilibrium. We found that historical levels of gene flow (mean m h = 0.07) were significantly higher than contemporary levels (mean m c = 0.03), and populations with large effective population sizes (Satpura and Kanha Tiger Reserves) are the larger exporters of migrants at both timescales. The greatest decline in historical versus contemporary gene flow is between pairs of reserves that are currently not connected by forest corridors (i.e., Melghat-Pench m h - m c = 0.063; and Kanha-Satpura m h - m c = 0.054). We attribute this reduction in gene flow to accelerated fragmentation and habitat alteration in the landscape over the past few centuries, and suggest protection of forest corridors to maintain gene flow in this landscape.

Linkage Disequilibrium Estimation of Effective Population Size with Immigrants from Divergent Populations: A Case Study on Spanish Mackerel (Scomberomorus commerson)

Estimates of genetic effective population size (Ne) using molecular markers are a potentially useful tool for the management of endangered through to commercial species. However, pitfalls are predicted when the effective size is large because estimates require large numbers of samples from wild populations for statistical validity. Our simulations showed that linkage disequilibrium estimates of Ne up to 10,000 with finite confidence limits can be achieved with sample sizes of approximately 5000. This number was deduced from empirical allele frequencies of seven polymorphic microsatellite loci in a commercially harvested fisheries species, the narrow-barred Spanish mackerel (Scomberomorus commerson). As expected, the smallest SD of Ne estimates occurred when low-frequency alleles were excluded. Additional simulations indicated that the linkage disequilibrium method was sensitive to small numbers of genotypes from cryptic species or conspecific immigrants. A correspondence analysis algorithm was developed to detect and remove outlier genotypes that could possibly be inadvertently sampled from cryptic species or nonbreeding immigrants from genetically separate populations. Simulations demonstrated the value of this approach in Spanish mackerel data. When putative immigrants were removed from the empirical data, 95% of the Ne estimates from jacknife resampling were greater than 24,000.

Patterns of evolutionary conservation of microsatellites (SSRs) suggest a faster rate of genome evolution in Hymenoptera than in Diptera

Microsatellites, or simple sequence repeats (SSRs), are common and widespread DNA elements in genomes of many organisms. However, their dynamics in genome evolution is unclear, whereby they are thought to evolve neutrally. More available genome sequences along with dated phylogenies allowed for studying the evolution of these repetitive DNA elements along evolutionary time scales. This could be used to compare rates of genome evolution. We show that SSRs in insects can be retained for several hundred million years. Different types of microsatellites seem to be retained longer than others. By comparing Dipteran with Hymenopteran species, we found very similar patterns of SSR loss during their evolution, but both taxa differ profoundly in the rate. Relative to divergence time, Diptera lost SSRs twice as fast as Hymenoptera. The loss of SSRs on the Drosophila melanogaster X-chromosome was higher than on the other chromosomes. However, accounting for generation time, the Diptera show an 8.5-fold slower rate of SSR loss than the Hymenoptera, which, in contrast to previous studies, suggests a faster genome evolution in the latter. This shows that generation time differences can have a profound effect. A faster genome evolution in these insects could be facilitated by several factors very different to Diptera, which is discussed in light of our results on the haplodiploid D. melanogaster X-chromosome. Furthermore, large numbers of SSRs can be found to be in synteny and thus could be exploited as a tool to investigate genome structure and evolution.

Can genetic estimators provide robust estimates of the effective number of breeders in small populations?

The effective population size (N(e)) is proportional to the loss of genetic diversity and the rate of inbreeding, and its accurate estimation is crucial for the monitoring of small populations. Here, we integrate temporal studies of the gecko Oedura reticulata, to compare genetic and demographic estimators of N(e). Because geckos have overlapping generations, our goal was to demographically estimate N(bI), the inbreeding effective number of breeders and to calculate the N(bI)/N(a) ratio (N(a) =number of adults) for four populations. Demographically estimated N(bI) ranged from 1 to 65 individuals. The mean reduction in the effective number of breeders relative to census size (N(bI)/N(a)) was 0.1 to 1.1. We identified the variance in reproductive success as the most important variable contributing to reduction of this ratio. We used four methods to estimate the genetic based inbreeding effective number of breeders N(bI(gen)) and the variance effective populations size N(eV(gen)) estimates from the genotype data. Two of these methods - a temporal moment-based (MBT) and a likelihood-based approach (TM3) require at least two samples in time, while the other two were single-sample estimators - the linkage disequilibrium method with bias correction LDNe and the program ONeSAMP. The genetic based estimates were fairly similar across methods and also similar to the demographic estimates excluding those estimates, in which upper confidence interval boundaries were uninformative. For example, LDNe and ONeSAMP estimates ranged from 14-55 and 24-48 individuals, respectively. However, temporal methods suffered from a large variation in confidence intervals and concerns about the prior information. We conclude that the single-sample estimators are an acceptable short-cut to estimate N(bI) for species such as geckos and will be of great importance for the monitoring of species in fragmented landscapes.

Monitoring the effective population size of a brown bear (Ursus arctos) population using new single-sample approaches

The effective population size (N(e) ) could be the ideal parameter for monitoring populations of conservation concern as it conveniently summarizes both the evolutionary potential of the population and its sensitivity to genetic stochasticity. However, tracing its change through time is difficult in natural populations. We applied four new methods for estimating N(e) from a single sample of genotypes to trace temporal change in N(e) for bears in the Northern Dinaric Mountains. We genotyped 510 bears using 20 microsatellite loci and determined their age. The samples were organized into cohorts with regard to the year when the animals were born and yearly samples with age categories for every year when they were alive. We used the Estimator by Parentage Assignment (EPA) to directly estimate both N(e) and generation interval for each yearly sample. For cohorts, we estimated the effective number of breeders (N(b) ) using linkage disequilibrium, sibship assignment and approximate Bayesian computation methods and extrapolated these estimates to N(e) using the generation interval. The N(e) estimate by EPA is 276 (183-350 95% CI), meeting the inbreeding-avoidance criterion of N(e) > 50 but short of the long-term minimum viable population goal of N(e) > 500. The results obtained by the other methods are highly consistent with this result, and all indicate a rapid increase in N(e) probably in the late 1990s and early 2000s. The new single-sample approaches to the estimation of N(e) provide efficient means for including N(e) in monitoring frameworks and will be of great importance for future management and conservation.