Disentangling the impact of demographic factors on population differentiation of an endangered freshwater crayfish (Austropotamobius pallipes) using population density and microsatellite data

1. Habitat fragmentation of stream ecosystems often results in decreased connectivity between populations and lower population sizes. Hence, understanding how habitat fragmentation affects genetic erosion is important for the preservation of freshwater biodiversity, in particular, as small populations suffer from loss of genetic diversity through genetic drift and loss of fitness because of inbreeding, increasing the risk of extinction. 2. Here, we assess the impact of demographic factors on population differentiation in the endangered freshwater crayfish Austropotamobius pallipes by analysing population genetic structure, estimating effective population sizes and comparing levels of polymorphism at five microsatellite loci with density estimates of 10 populations within a small French catchment that has become progressively confined to headwaters over the last six decades. 3. Levels of expected heterozygosity and allelic richness per population were relatively low (0.214–0.396 and 1.6–2.6, respectively). We found strong genetic differentiation between these geographically close populations (F_ST = 0.283), with weak statistical evidence for a pattern of isolation by distance. Estimates of effective population size were low (<150) in most populations, but potentially reached several thousands in three populations. 4. Population density and allelic richness were strongly positively correlated. A robust relationship between population density and heterozygosity values was also noted, but only after discarding two populations for which significant genetic signatures of a recent bottleneck were found; these two populations displayed high expected heterozygosity compared with a very low density. Populations with the highest densities of individuals had the highest effective population size estimates and vice versa. 5. Our results clearly show the importance of demographic factors and genetic drift on A. pallipes populations. Furthermore, analysis of genetic and population density data is a pragmatic and efficient approach to corroborate inferences from genetic data and can be particularly useful in the identification of populations experiencing a bottleneck and therefore in conservation genetics studies aiming at identifying priority populations for conservation.     

Conservation genetics and demographic history of the endangered Cape Fear shiner (Notropis mekistocholas)

We examined allelic variation at 22 nuclear-encoded markers (21 microsatellites and one anonymous locus) and mitochondrial (mt)DNA in two geographical samples of the endangered cyprinid fish Notropis mekistocholas (Cape Fear shiner). Genetic diversity was relatively high in comparison to other endangered vertebrates, and there was no evidence of small population effects despite the low abundance reported for the species. Significant heterogeneity (following Bonferroni correction) in allele distribution at three microsatellites and in haplotype distribution in mtDNA was detected between the two localities. This heterogeneity may be due to reduced gene flow caused by a dam built in the early 1900 s. Bayesian coalescent analysis of microsatellite variation indicated that effective population size of Cape Fear shiners has declined in recent times (11-25 435 years ago, with highest posterior probabilities between 126 and 2007 years ago) by one-two orders of magnitude, consistent with the observed decline in abundance of the species. A decline in effective size was not indicated by analysis of mtDNA, where sequence polymorphism appeared to carry the signature of an older expansion phase that dated to the Pleistocene ( approximately 12 700 > 1 million years ago). Cape Fear shiners thus appear to have undergone an expansion phase following a glacial cycle but to have declined significantly in more recent times. These results suggest that rapidly evolving markers such as microsatellites may constitute a suitable tool when inferring recent demographic dynamics of populations.     

Historical demographic profiles and genetic variation of the East African Butana and Kenana indigenous dairy zebu cattle

Butana and Kenana breeds from Sudan are part of the East African zebu Bos indicus type of cattle. Unlike other indigenous zebu cattle in Africa, they are unique due to their reputation for high milk production and are regarded as dairy cattle, the only ones of their kind on the African continent. In this study, we sequenced the complete mitochondrial DNA (mtDNA) D‐loop of 70 animals to understand the maternal genetic variation, demographic profiles and history of the two breeds in relation to the history of cattle pastoralism on the African continent. Only taurine mtDNA sequences were identified. We found very high mtDNA diversity but low level of maternal genetic structure within and between the two breeds. Bayesian coalescent‐based analysis revealed different historical and demographic profiles for the two breeds, with an earlier population expansion in the Butana vis a vis the Kenana. The maternal ancestral populations of the two breeds may have diverged prior to their introduction into the African continent, with first the arrival of the ancestral Butana population. We also reveal distinct demographic history between the two breeds with the Butana showing a decline in its effective population size (N_e) in the recent past ~590 years. Our results provide new insights on the early history of cattle pastoralism in Sudan indicative of a large ancient effective population size.     

Reconstructing the demographic history of orang‐utans using Approximate Bayesian Computation

Investigating how different evolutionary forces have shaped patterns of DNA variation within and among species requires detailed knowledge of their demographic history. Orang‐utans, whose distribution is currently restricted to the South‐East Asian islands of Borneo (Pongo pygmaeus) and Sumatra (Pongo abelii), have likely experienced a complex demographic history, influenced by recurrent changes in climate and sea levels, volcanic activities and anthropogenic pressures. Using the most extensive sample set of wild orang‐utans to date, we employed an Approximate Bayesian Computation (ABC) approach to test the fit of 12 different demographic scenarios to the observed patterns of variation in autosomal, X‐chromosomal, mitochondrial and Y‐chromosomal markers. In the best‐fitting model, Sumatran orang‐utans exhibit a deep split of populations north and south of Lake Toba, probably caused by multiple eruptions of the Toba volcano. In addition, we found signals for a strong decline in all Sumatran populations ~24 ka, probably associated with hunting by human colonizers. In contrast, Bornean orang‐utans experienced a severe bottleneck ~135 ka, followed by a population expansion and substructuring starting ~82 ka, which we link to an expansion from a glacial refugium. We showed that orang‐utans went through drastic changes in population size and connectedness, caused by recurrent contraction and expansion of rainforest habitat during Pleistocene glaciations and probably hunting by early humans. Our findings emphasize the fact that important aspects of the evolutionary past of species with complex demographic histories might remain obscured when applying overly simplified models.     

Inferring past demographic changes from contemporary genetic data: A simulation‐based evaluation of the ABC methods implemented in diyabc

Inferring the demographic history of species and their populations is crucial to understand their contemporary distribution, abundance and adaptations. The high computational overhead of likelihood‐based inference approaches severely restricts their applicability to large data sets or complex models. In response to these restrictions, approximate Bayesian computation (ABC) methods have been developed to infer the demographic past of populations and species. Here, we present the results of an evaluation of the ABC‐based approach implemented in the popular software package diyabc using simulated data sets (mitochondrial DNA sequences, microsatellite genotypes and single nucleotide polymorphisms). We simulated population genetic data under five different simple, single‐population models to assess the model recovery rates as well as the bias and error of the parameter estimates. The ability of diyabc to recover the correct model was relatively low (0.49): 0.6 for the simplest models and 0.3 for the more complex models. The recovery rate improved significantly when reducing the number of candidate models from five to three (from 0.57 to 0.71). Among the parameters of interest, the effective population size was estimated at a higher accuracy compared to the timing of events. Increased amounts of genetic data did not significantly improve the accuracy of the parameter estimates. Some gains in accuracy and decreases in error were observed for scaled parameters (e.g., N_eμ) compared to unscaled parameters (e.g., N_e and μ). We concluded that diyabc ‐based assessments are not suited to capture a detailed demographic history, but might be efficient at capturing simple, major demographic changes.     

Elucidating the spatio‐temporal dynamics of an emerging wildlife pathogen using approximate Bayesian computation

Emerging pathogens constitute a severe threat for human health and biodiversity. Determining the status (native or non‐native) of emerging pathogens, and tracing back their spatio‐temporal dynamics, is crucial to understand the eco‐evolutionary factors promoting their emergence, to control their spread and mitigate their impacts. However, tracing back the spatio‐temporal dynamics of emerging wildlife pathogens is challenging because (i) they are often neglected until they become sufficiently abundant and pose socio‐economical concerns and (ii) their geographical range is often little known. Here, we combined classical population genetics tools and approximate Bayesian computation (i.e. ABC) to retrace the dynamics of Tracheliastes polycolpus, a poorly documented pathogenic ectoparasite emerging in Western Europe that threatens several freshwater fish species. Our results strongly suggest that populations of T. polycolpus in France emerged from individuals originating from a unique genetic pool that were most likely introduced in the 1920s in central France. From this initial population, three waves of colonization occurred into peripheral watersheds within the next two decades. We further demonstrated that populations remained at low densities, and hence undetectable, during 10 years before a major demographic expansion occurred, and before its official detection in France. These findings corroborate and expand the few historical records available for this emerging pathogen. More generally, our study demonstrates how ABC can be used to determine the status, reconstruct the colonization history and infer key evolutionary parameters of emerging wildlife pathogens with low data availability, and for which samples from the putative native area are inaccessible.     

Estimating the ratio of effective to actual size of an age‐structured population from individual demographic data

The effective population size is a central concept for understanding evolutionary processes in a finite population. We employ Fisher's reproductive value to estimate the ratio of effective to actual population size for an age‐structured population with two sexes using random samples of individual vital rates. The population may be subject to environmental stochasticity affecting the vital rates. When the mean sex ratio at birth is known, improved efficiency is obtained by utilizing the records of total number of offspring rather than considering separately female and male offspring. We also show how to incorporate uncertain paternity.     

WFABC: a Wright–Fisher ABC‐based approach for inferring effective population sizes and selection coefficients from time‐sampled data

With novel developments in sequencing technologies, time‐sampled data are becoming more available and accessible. Naturally, there have been efforts in parallel to infer population genetic parameters from these data sets. Here, we compare and analyse four recent approaches based on the Wright–Fisher model for inferring selection coefficients (s) given effective population size (N_e), with simulated temporal data sets. Furthermore, we demonstrate the advantage of a recently proposed approximate Bayesian computation (ABC)‐based method that is able to correctly infer genomewide average N_e from time‐serial data, which is then set as a prior for inferring per‐site selection coefficients accurately and precisely. We implement this ABC method in a new software and apply it to a classical time‐serial data set of the medionigra genotype in the moth Panaxia dominula. We show that a recessive lethal model is the best explanation for the observed variation in allele frequency by implementing an estimator of the dominance ratio (h).     

Adaptive divergence despite strong genetic drift: genomic analysis of the evolutionary mechanisms causing genetic differentiation in the island fox (Urocyon littoralis)

The evolutionary mechanisms generating the tremendous biodiversity of islands have long fascinated evolutionary biologists. Genetic drift and divergent selection are predicted to be strong on islands and both could drive population divergence and speciation. Alternatively, strong genetic drift may preclude adaptation. We conducted a genomic analysis to test the roles of genetic drift and divergent selection in causing genetic differentiation among populations of the island fox (Urocyon littoralis). This species consists of six subspecies, each of which occupies a different California Channel Island. Analysis of 5293 SNP loci generated using Restriction‐site Associated DNA (RAD) sequencing found support for genetic drift as the dominant evolutionary mechanism driving population divergence among island fox populations. In particular, populations had exceptionally low genetic variation, small N_e (range = 2.1–89.7; median = 19.4), and significant genetic signatures of bottlenecks. Moreover, islands with the lowest genetic variation (and, by inference, the strongest historical genetic drift) were most genetically differentiated from mainland grey foxes, and vice versa, indicating genetic drift drives genome‐wide divergence. Nonetheless, outlier tests identified 3.6–6.6% of loci as high F_ST outliers, suggesting that despite strong genetic drift, divergent selection contributes to population divergence. Patterns of similarity among populations based on high F_ST outliers mirrored patterns based on morphology, providing additional evidence that outliers reflect adaptive divergence. Extremely low genetic variation and small N_e in some island fox populations, particularly on San Nicolas Island, suggest that they may be vulnerable to fixation of deleterious alleles, decreased fitness and reduced adaptive potential.     

Short‐term temporal instability in fine‐scale genetic structure of masu salmon

相似文献   

Blacktip reef sharks,Carcharhinus melanopterus,have high genetic structure and varying demographic histories in their Indo‐Pacific range

For free‐swimming marine species like sharks, only population genetics and demographic history analyses can be used to assess population health/status as baseline population numbers are usually unknown. We investigated the population genetics of blacktip reef sharks, Carcharhinus melanopterus; one of the most abundant reef‐associated sharks and the apex predator of many shallow water reefs of the Indian and Pacific Oceans. Our sampling includes 4 widely separated locations in the Indo‐Pacific and 11 islands in French Polynesia with different levels of coastal development. Four‐teen microsatellite loci were analysed for samples from all locations and two mitochondrial DNA fragments, the control region and cytochrome b, were examined for 10 locations. For microsatellites, genetic diversity is higher for the locations in the large open systems of the Red Sea and Australia than for the fragmented habitat of the smaller islands of French Polynesia. Strong significant structure was found for distant locations with F_ST values as high as ~0.3, and a smaller but still significant structure is found within French Polynesia. Both mitochondrial genes show only a few mutations across the sequences with a dominant shared haplotype in French Polynesia and New Caledonia suggesting a common lineage different to that of East Australia. Demographic history analyses indicate population expansions in the Red Sea and Australia that may coincide with sea level changes after climatic events. Expansions and flat signals are indicated for French Polynesia as well as a significant recent bottleneck for Moorea, the most human‐impacted lagoon of the locations in French Polynesia.     

Spatio‐temporal genetic structure and the effects of long‐term fishing in two partially sympatric offshore demersal fishes

Environmental gradients have been shown to disrupt gene flow in marine species, yet their influence in structuring populations at depth remains poorly understood. The Cape hakes (Merluccius paradoxus and M. capensis) are demersal species co‐occurring in the Benguela Current system, where decades of intense fishing resulted in severely depleted stocks in the past. Previous studies identified conflicting mtDNA genetic substructuring patterns and thus contrasting evolutionary trajectories for both species. Using 10 microsatellite loci, the control region of mtDNA and employing a seascape genetics approach, we investigated genetic connectivity and the impact of prolonged exploitation in the two species, which are characterized by different patterns of fishing pressure. Three consecutive years were sampled covering the entire distribution (N = 2100 fishes). Despite large estimated population sizes, both species exhibited low levels of contemporary genetic diversity (0.581 < H_E < 0.692), implying that fishing has had a significant impact on their genetic composition and evolutionary trajectories. Further, for M. paradoxus, significant temporal, but not spatial, divergence points to the presence of genetic chaotic patchiness. In contrast, M. capensis exhibited a clear latitudinal cline in genetic differentiation between Namibia and South Africa (F_ST = 0.063, P < 0.05), with low (0.2% per generation) estimates of contemporary gene flow. Seascape analyses reveal an association with bathymetry and upwelling events, suggesting that adaptation to local environmental conditions may drive genetic differentiation in M. capensis. Importantly, our results highlight the need for temporal sampling in disentangling the complex factors that impact population divergence in marine fishes.     

Past and future demographic dynamics of alpine species: limited genetic consequences despite dramatic range contraction in a plant from the Spanish Sierra Nevada

Anthropogenic global climate change is expected to cause severe range contractions among alpine plants. Alpine areas in the Mediterranean region are of special concern because of the high abundance of endemic species with narrow ranges. This study combined species distribution models, population structure analyses and Bayesian skyline plots to trace the past and future distribution and diversity of Linaria glacialis, an endangered narrow endemic species that inhabits summits of Sierra Nevada (Spain). The results showed that: (i) the habitat of this alpine‐Mediterranean species in Sierra Nevada suffered little changes during glacial and interglacial stages of late Quaternary; (ii) climatic oscillations in the last millennium (Medieval Warm Period and Little Ice Age) moderately affected the demographic trends of L. glacialis; (iii) future warming conditions will cause severe range contractions; and (iv) genetic diversity will not diminish at the same pace as the distribution range. As a consequence of the low population structure of this species, genetic impoverishment in the alpine zones of Sierra Nevada should be limited during range contraction. We conclude that maintenance of large effective population sizes via high mutation rates and high levels of gene flow may promote the resilience of alpine plant species when confronted with global warming.     

On the genetic parameter determining the efficiency of purging: an estimate for Drosophila egg‐to‐pupae viability

The consequences of inbreeding on fitness can be crucial in evolutionary and conservation grounds and depend upon the efficiency of purging against deleterious recessive alleles. Recently, analytical expressions have been derived to predict the evolution of mean fitness, taking into account both inbreeding and purging, which depend on an ‘effective purging coefficient (d_e)’. Here, we explore the validity of that predictive approach and assay the strength of purging by estimating d_e for egg‐to‐pupae viability (EPV) after a drastic reduction in population size in a recently captured base population of Drosophila melanogaster. For this purpose, we first obtained estimates of the inbreeding depression rate (δ) for EPV in the base population, and we found that about 40% was due to segregating recessive lethals. Then, two sets of lines were founded from this base population and were maintained with different effective size throughout the rest of the experiment (N = 6; N = 12), their mean EPV being assayed at different generations. Due to purging, the reductions in mean EPV experienced by these lines were considerably smaller than the corresponding neutral predictions. For the 60% of δ attributable to nonlethal deleterious alleles, our results suggest an effective purging coefficient d_e > 0.02. Similarly, we obtain that d_e > 0.09 is required to roughly account for purging against the pooled inbreeding depression from lethal and nonlethal deleterious alleles. This implies that purging should be efficient for population sizes of the order of a few tens and larger, but might be inefficient against nonlethal deleterious alleles in smaller populations.     

Population genetic analysis of white shrimp,Litopenaeus setiferus,using microsatellite genetic markers

The white shrimp (Litopenaeus setiferus) is a commercially and recreationally valuable species, yet little is known of its population structure or genetic diversity. White shrimp are distributed along the Atlantic coast of the United States and from the west coast of Florida to the Bay of Campeche, Mexico. In this study, shrimp were collected from North Carolina, South Carolina (four separate collections were taken from 1995 to 1999), Georgia, the Atlantic and Gulf coasts of Florida, Louisiana, Texas and Mexico. DNA was isolated from these individuals, and genetic variation was assessed at six microsatellite loci. These loci were, for the most part, highly polymorphic with an average expected heterozygosity of 0.68. Deviations from Hardy-Weinberg proportions were observed over all samples, but experimental results suggested the presence of null alleles, which confounded a biological interpretation of this result. Pairwise tests of the similarity of allele frequency distributions and distance measure analyses showed broad-scale genetic homogeneity superimposed over occasional indications of random geographical and temporal differentiation. FST and RST estimates over all loci and samples were 0.002 or less and indicated little population structure. Weak but significant genetic differentiation was evident only between pooled western Atlantic and pooled Gulf of Mexico samples. Within the Gulf of Mexico or within the western Atlantic, the large-scale genetic homogeneity observed may be a consequence of genetic mixing resulting from pelagic larvae and adult migrations, while the random local genetic differentiation may be a result of genetic sampling or experimental sampling error. The weak differentiation between shrimp from the Gulf of Mexico and the western Atlantic can be explained by a relatively recent separation of these two populations and/or small amounts of ongoing gene flow.     

Effective size of density‐dependent populations in fluctuating environments

Reliable estimates of effective population size 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 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 as assumed by the harmonic mean model, where N is the total population size of mature individuals. We find a negative relationship between 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 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.     

Multiple estimates of effective population size for monitoring a long‐lived vertebrate: an application to Yellowstone grizzly bears

Effective population size (N_e) is a key parameter for monitoring the genetic health of threatened populations because it reflects a population's evolutionary potential and risk of extinction due to genetic stochasticity. However, its application to wildlife monitoring has been limited because it is difficult to measure in natural populations. The isolated and well‐studied population of grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem provides a rare opportunity to examine the usefulness of different N_e estimators for monitoring. We genotyped 729 Yellowstone grizzly bears using 20 microsatellites and applied three single‐sample estimators to examine contemporary trends in generation interval (GI), effective number of breeders (N_b) and N_e during 1982–2007. We also used multisample methods to estimate variance (N_eV) and inbreeding N_e (N_eI). Single‐sample estimates revealed positive trajectories, with over a fourfold increase in N_e (≈100 to 450) and near doubling of the GI (≈8 to 14) from the 1980s to 2000s. N_eV (240–319) and N_eI (256) were comparable with the harmonic mean single‐sample N_e (213) over the time period. Reanalysing historical data, we found N_eV increased from ≈80 in the 1910s–1960s to ≈280 in the contemporary population. The estimated ratio of effective to total census size (N_e/N_c) was stable and high (0.42–0.66) compared to previous brown bear studies. These results support independent demographic evidence for Yellowstone grizzly bear population growth since the 1980s. They further demonstrate how genetic monitoring of N_e can complement demographic‐based monitoring of N_c and vital rates, providing a valuable tool for wildlife managers.     

A comparison of single‐sample estimators of effective population sizes from genetic marker data

In molecular ecology and conservation genetics studies, the important parameter of effective population size (N_e) is increasingly estimated from a single sample of individuals taken at random from a population and genotyped at a number of marker loci. Several estimators are developed, based on the information of linkage disequilibrium (LD), heterozygote excess (HE), molecular coancestry (MC) and sibship frequency (SF) in marker data. The most popular is the LD estimator, because it is more accurate than HE and MC estimators and is simpler to calculate than SF estimator. However, little is known about the accuracy of LD estimator relative to that of SF and about the robustness of all single‐sample estimators when some simplifying assumptions (e.g. random mating, no linkage, no genotyping errors) are violated. This study fills the gaps and uses extensive simulations to compare the biases and accuracies of the four estimators for different population properties (e.g. bottlenecks, nonrandom mating, haplodiploid), marker properties (e.g. linkage, polymorphisms) and sample properties (e.g. numbers of individuals and markers) and to compare the robustness of the four estimators when marker data are imperfect (with allelic dropouts). Extensive simulations show that SF estimator is more accurate, has a much wider application scope (e.g. suitable to nonrandom mating such as selfing, haplodiploid species, dominant markers) and is more robust (e.g. to the presence of linkage and genotyping errors of markers) than the other estimators. An empirical data set from a Yellowstone grizzly bear population was analysed to demonstrate the use of the SF estimator in practice.     

Anthropogenic fragmentation may not alter pre‐existing patterns of genetic diversity and differentiation in perennial shrubs

Many plant species have pollination and seed dispersal systems and evolutionary histories that have produced strong genetic structuring. These genetic patterns may be consistent with expectations following recent anthropogenic fragmentation, making it difficult to detect fragmentation effects if no prefragmentation genetic data are available. We used microsatellite markers to investigate whether severe habitat fragmentation may have affected the structure and diversity of populations of the endangered Australian bird‐pollinated shrub Grevillea caleyi R.Br., by comparing current patterns of genetic structure and diversity with those of the closely related G. longifolia R.Br. that has a similar life history but has not experienced anthropogenic fragmentation. Grevillea caleyi and G. longifolia showed similar and substantial population subdivision at all spatial levels (global F′_ST = 0.615 and 0.454; S_p = 0.039 and 0.066), marked isolation by distance and large heterozygous deficiencies. These characteristics suggest long‐term effects of inbreeding in self‐compatible species that have poor seed dispersal, limited connectivity via pollen flow and undergo population bottlenecks because of periodic fires. Highly structured allele size distributions, most notably in G. caleyi, imply historical processes of drift and mutation were important in isolated subpopulations. Genetic diversity did not vary with population size but was lower in more isolated populations for both species. Through this comparison, we reject the hypothesis that anthropogenic fragmentation has impacted substantially on the genetic composition or structure of G. caleyi populations. Our results suggest that highly self‐compatible species with limited dispersal may be relatively resilient to the genetic changes predicted to follow habitat fragmentation.     

Effective size of density‐dependent two‐sex populations: the effect of mating systems

Density dependence in vital rates is a key feature affecting temporal fluctuations of natural populations. This has important implications for the rate of random genetic drift. Mating systems also greatly affect effective population sizes, but knowledge of how mating system and density regulation interact to affect random genetic drift is poor. Using theoretical models and simulations, we compare N_e in short‐lived, density‐dependent animal populations with different mating systems. We study the impact of a fluctuating, density‐dependent sex ratio and consider both a stable and a fluctuating environment. We find a negative relationship between annual N_e/N and adult population size N due to density dependence, suggesting that loss of genetic variation is reduced at small densities. The magnitude of this decrease was affected by mating system and life history. A male‐biased, density‐dependent sex ratio reduces the rate of genetic drift compared to an equal, density‐independent sex ratio, but a stochastic change towards male bias reduces the N_e/N ratio. Environmental stochasticity amplifies temporal fluctuations in population size and is thus vital to consider in estimation of effective population sizes over longer time periods. Our results on the reduced loss of genetic variation at small densities, particularly in polygamous populations, indicate that density regulation may facilitate adaptive evolution at small population sizes.