Long-distance dispersal in the short-distance dispersing house sparrow (Passer domesticus)

The house sparrow (Passer domesticus) is a small passerine known to be highly sedentary. Throughout a 30-year capture-mark-recapture study, we have obtained occasional reports of recoveries far outside our main metapopulation study system, documenting unusually long dispersal distances. Our records constitute the highest occurrence of long-distance dispersal events recorded for this species in Scandinavia. Such long-distance dispersals radically change the predicted distribution of dispersal distances and connectedness for our study metapopulation. Moreover, it reveals a much greater potential for colonization than formerly recorded for the house sparrow, which is an invasive species across four continents. These rare and occasional long-distance dispersal events are challenging to document but may have important implications for the genetic composition of small and isolated populations and for our understanding of dispersal ecology and evolution.

Harvest and decimation affect genetic drift and the effective population size in wild reindeer

Harvesting and culling are methods used to monitor and manage wildlife diseases. An important consequence of these practices is a change in the genetic dynamics of affected populations that may threaten their long-term viability. The effective population size (N e) is a fundamental parameter for describing such changes as it determines the amount of genetic drift in a population. Here, we estimate N e of a harvested wild reindeer population in Norway. Then we use simulations to investigate the genetic consequences of management efforts for handling a recent spread of chronic wasting disease, including increased adult male harvest and population decimation. The N e/N ratio in this population was found to be 0.124 at the end of the study period, compared to 0.239 in the preceding 14 years period. The difference was caused by increased harvest rates with a high proportion of adult males (older than 2.5 years) being shot (15.2% in 2005-2018 and 44.8% in 2021). Increased harvest rates decreased N e in the simulations, but less sex biased harvest strategies had a lower negative impact. For harvest strategies that yield stable population dynamics, shifting the harvest from calves to adult males and females increased N e. Population decimation always resulted in decreased genetic variation in the population, with higher loss of heterozygosity and rare alleles with more severe decimation or longer periods of low population size. A very high proportion of males in the harvest had the most severe consequences for the loss of genetic variation. This study clearly shows how the effects of harvest strategies and changes in population size interact to determine the genetic drift of a managed population. The long-term genetic viability of wildlife populations subject to a disease will also depend on population impacts of the disease and how these interact with management actions.

The genetic basis of dispersal in a vertebrate metapopulation

Dispersal affects evolutionary processes by changing population size and genetic composition, influencing the viability and persistence of populations. Investigating which mechanisms underlie variation in dispersal phenotypes and whether populations harbour adaptive potential for dispersal is crucial to understanding the eco-evolutionary dynamics of this important trait. Here, we investigate the genetic architecture of dispersal among successfully recruited individuals in an insular metapopulation of house sparrows. We use an extensive long-term individual-based ecological data set and high-density single-nucleotide polymorphism (SNP) genotypes for over 2500 individuals. We conducted a genome-wide association study (GWAS), and found a relationship between dispersal probability and a SNP located near genes known to regulate circadian rhythm, glycogenesis and exercise performance, among other functions. However, this SNP only explained 3.8% of variance, suggesting that dispersal is a polygenic trait. We then used an animal model to estimate heritable genetic variation (σA 2 ), which composes 10% of the total variation in dispersal probability. Finally, we investigated differences in σA 2 across populations occupying ecologically relevant habitat types (farm vs. non-farm) using a genetic groups animal model. We found different adaptive potentials across habitats, with higher mean breeding value, σA 2 , and heritability for the habitat presenting lower dispersal rates, suggesting also different roles of environmental variation. Our results suggest a complex genetic architecture of dispersal and demonstrate that adaptive potential may be environment dependent in key eco-evolutionary traits. The eco-evolutionary implications of such environment dependence and consequent spatial variation are likely to become ever more important with the increased fragmentation and loss of suitable habitats for many natural populations.

Spatial variation in the evolutionary potential and constraints of basal metabolic rate and body mass in a wild bird

An organism's energy budget is strongly related to resource consumption, performance, and fitness. Hence, understanding the evolution of key energetic traits, such as basal metabolic rate (BMR), in natural populations is central for understanding life-history evolution and ecological processes. Here we used quantitative genetic analyses to study evolutionary potential of BMR in two insular populations of the house sparrow (Passer domesticus). We obtained measurements of BMR and body mass (M_b ) from 911 house sparrows on the islands of Leka and Vega along the coast of Norway. These two populations were the source populations for translocations to create an additional third, admixed 'common garden' population in 2012. With the use of a novel genetic group animal model concomitant with a genetically determined pedigree, we differentiate genetic and environmental sources of variation, thereby providing insight into the effects of spatial population structure on evolutionary potential. We found that the evolutionary potential of BMR was similar in the two source populations, whereas the Vega population had a somewhat higher evolutionary potential of M_b than the Leka population. BMR was genetically correlated with M_b in both populations, and the conditional evolutionary potential of BMR (independent of body mass) was 41% (Leka) and 53% (Vega) lower than unconditional estimates. Overall, our results show that there is potential for BMR to evolve independently of M_b , but that selection on BMR and/or M_b may have different evolutionary consequences in different populations of the same species.

Spatial structure and dispersal dynamics in a house sparrow metapopulation

The effects of spatial structure on metapopulation dynamics depend upon the interaction between local population dynamics and dispersal, and how this relationship is affected by the geographical isolation and spatial heterogeneity in habitat characteristics. Our aim is to examine how emigration and immigration of house sparrows Passer domesticus in a Norwegian archipelagic metapopulation are affected by key factors predicted by classic metapopulation models to affect dispersal-spatial and temporal variation in population size, inter-island distance, local demography and habitat characteristics. This metapopulation can be divided into two major habitat types: (a) islands closer to the mainland where sparrows breed in colonies on farms, and (b) islands without farms, situated farther away from the mainland where sparrows are exposed to harsher environmental conditions. Dispersal was spatially structured within the metapopulation; there was proportionally and numerically less emigration and immigration involving farm islands, as compared to non-farm islands. Furthermore, emigration and immigration occurred mostly between nearby islands. Moreover, emigration in response to spatial differences in mean population size differed between the habitat types, but populations with large mean received more immigrants in both habitat types. The number of emigrants and immigrants was negatively related to long-term recruit production, which was not the case in non-farm islands. The proportion and number of emigrants was positively related to temporal increases in recruit production on farm islands, however not on non-farm islands. Our results demonstrate that spatial heterogeneity in environmental conditions influences how spatial variation in long-term mean population size, and temporal and spatial variation in recruit production, affects dispersal dynamics. The spatial structure of this metapopulation is therefore best described by a spatially explicit model in which the exchange of individuals within each habitat type is strongly affected by the degree of geographical isolation, population size and recruit production. However, these relationships differed between the two habitat types; non-farm islands showing similarities to a mainland-island model type of structure, whereas farm islands showed features more associated with source-sink or balanced dispersal models. Such differential dispersal dynamics between habitat types are expected to have important consequences for the ecological and evolutionary dynamics within this metapopulation.

Variation in generation time reveals density regulation as an important driver of pace of life in a bird metapopulation

Generation time determines the pace of key demographic and evolutionary processes. Quantified as the weighted mean age at reproduction, it can be studied as a life-history trait that varies within and among populations and may evolve in response to ecological conditions. We combined quantitative genetic analyses with age- and density-dependent models to study generation time variation in a bird metapopulation. Generation time was heritable, and males had longer generation times than females. Individuals with longer generation times had greater lifetime reproductive success but not a higher expected population growth rate. Density regulation acted on recruit production, suggesting that longer generation times should be favoured when populations are closer to carrying capacity. Furthermore, generation times were shorter when populations were growing and longer when populations were closer to equilibrium or declining. These results support classic theory predicting that density regulation is an important driver of the pace of life-history strategies.

Dispersal in a house sparrow metapopulation: An integrative case study of genetic assignment calibrated with ecological data and pedigree information

Dispersal has a crucial role determining ecoevolutionary dynamics through both gene flow and population size regulation. However, to study dispersal and its consequences, one must distinguish immigrants from residents. Dispersers can be identified using telemetry, capture-mark-recapture (CMR) methods, or genetic assignment methods. All of these methods have disadvantages, such as high costs and substantial field efforts needed for telemetry and CMR surveys, and adequate genetic distance required in genetic assignment. In this study, we used genome-wide 200K Single Nucleotide Polymorphism data and two different genetic assignment approaches (GSI_SIM, Bayesian framework; BONE, network-based estimation) to identify the dispersers in a house sparrow (Passer domesticus) metapopulation sampled over 16 years. Our results showed higher assignment accuracy with BONE. Hence, we proceeded to diagnose potential sources of errors in the assignment results from the BONE method due to variation in levels of interpopulation genetic differentiation, intrapopulation genetic variation and sample size. We show that assignment accuracy is high even at low levels of genetic differentiation and that it increases with the proportion of a population that has been sampled. Finally, we highlight that dispersal studies integrating both ecological and genetic data provide robust assessments of the dispersal patterns in natural populations.

Assessing the evolutionary persistence of ecological relationships: A review and preview

Species interactions, such as pollination, parasitism and predation, form the basis of functioning ecosystems. The origins and resilience of such interactions therefore merit attention. However, fossils only occasionally document ancient interactions, and phylogenetic methods are blind to recent interactions. Is there some other way to track shared species experiences? "Comparative demography" examines when pairs of species jointly thrived or declined. By forging links between ecology, epidemiology, and evolutionary biology, this method sheds light on biological adaptation, species resilience, and ecosystem health. Here, we describe how this method works, discuss examples, and suggest future directions in hopes of inspiring interest, imitators, and critics.

Consistent scaling of inbreeding depression in space and time in a house sparrow metapopulation

Inbreeding may increase the extinction risk of small populations. Yet, studies using modern genomic tools to investigate inbreeding depression in nature have been limited to single populations, and little is known about the dynamics of inbreeding depression in subdivided populations over time. Natural populations often experience different environmental conditions and differ in demographic history and genetic composition, characteristics that can affect the severity of inbreeding depression. We utilized extensive long-term data on more than 3,100 individuals from eight islands in an insular house sparrow metapopulation to examine the generality of inbreeding effects. Using genomic estimates of realized inbreeding, we discovered that inbred individuals had lower survival probabilities and produced fewer recruiting offspring than noninbred individuals. Inbreeding depression, measured as the decline in fitness-related traits per unit inbreeding, did not vary appreciably among populations or with time. As a consequence, populations with more resident inbreeding (due to their demographic history) paid a higher total fitness cost, evidenced by a larger variance in fitness explained by inbreeding within these populations. Our results are in contrast to the idea that effects of inbreeding generally depend on ecological factors and genetic differences among populations, and expand the understanding of inbreeding depression in natural subdivided populations.

Decomposing demographic contributions to the effective population size with moose as a case study

Levels of random genetic drift are influenced by demographic factors, such as mating system, sex ratio and age structure. The effective population size (N_e ) is a useful measure for quantifying genetic drift. Evaluating relative contributions of different demographic factors to N_e is therefore important to identify what makes a population vulnerable to loss of genetic variation. Until recently, models for estimating N_e have required many simplifying assumptions, making them unsuitable for this task. Here, using data from a small, harvested moose population, we demonstrate the use of a stochastic demographic framework allowing for fluctuations in both population size and age distribution to estimate and decompose the total demographic variance and hence the ratio of effective to total population size (N_e /N) into components originating from sex, age, survival and reproduction. We not only show which components contribute most to N_e /N currently, but also which components have the greatest potential for changing N_e /N. In this relatively long-lived polygynous system we show that N_e /N is most sensitive to the demographic variance of older males, and that both reproductive autocorrelations (i.e., a tendency for the same individuals to be successful several years in a row) and covariance between survival and reproduction contribute to decreasing N_e /N (increasing genetic drift). These conditions are common in nature and can be caused by common hunting strategies. Thus, the framework presented here has great potential to increase our understanding of the demographic processes that contribute to genetic drift and viability of populations, and to inform management decisions.

Population Genomic Signatures of Genetic Structure and Environmental Selection in the Catadromous Roughskin Sculpin Trachidermus fasciatus

Understanding the patterns of genetic diversity and adaptation across species' range is crucial to assess its long-term persistence and determine appropriate conservation measures. The impacts of human activities on the genetic diversity and genetic adaptation to heterogeneous environments remain poorly understood in the marine realm. The roughskin sculpin (Trachidermus fasciatus) is a small catadromous fish, and has been listed as a second-class state protected aquatic animal since 1988 in China. To elucidate the underlying mechanism of population genetic structuring and genetic adaptations to local environments, RAD tags were sequenced for 202 individuals in nine populations across the range of T. fasciatus in China. The pairwise FST values over 9,271 filtered SNPs were significant except that between Dongying and Weifang. All the genetic clustering analysis revealed significant population structure with high support for eight distinct genetic clusters. Both the minor allele frequency spectra and Ne estimations suggested extremely small Ne in some populations (e.g., Qinhuangdao, Rongcheng, Wendeng, and Qingdao), which might result from recent population bottleneck. The strong genetic structure can be partly attributed to genetic drift and habitat fragmentation, likely due to the anthropogenic activities. Annotations of candidate adaptive loci suggested that genes involved in metabolism, development, and osmoregulation were critical for adaptation to spatially heterogenous environment of local populations. In the context of anthropogenic activities and environmental change, results of the present population genomic work provided important contributions to the understanding of genetic differentiation and adaptation to changing environments.

Animal models with group-specific additive genetic variances: extending genetic group models

BACKGROUND

The animal model is a key tool in quantitative genetics and has been used extensively to estimate fundamental parameters, such as additive genetic variance or heritability. An implicit assumption of animal models is that all founder individuals derive from a single population. This assumption is commonly violated, for instance in crossbred livestock or when a meta-population is split into genetically differentiated subpopulations. Ignoring that base populations are genetically heterogeneous and thus split into different 'genetic groups' may lead to biased parameter estimates, especially for additive genetic variance. To avoid such biases, genetic group animal models, which account for the presence of more than one genetic group, have been proposed. Unfortunately, the method to date is only computationally feasible when the breeding values of the groups are allowed to differ in their means, but not in their variances.

RESULTS

We present an extension of the animal model that permits estimation of group-specific additive genetic variances. This is achieved by employing group-specific relatedness matrices for the breeding value components to different genetic groups. We derive these matrices by decomposing the full relatedness matrix via the generalized Cholesky decomposition, and by scaling the respective matrix components for each group. We propose a computationally convenient approximation for the matrix component that encodes for the Mendelian sampling variance, and show that this approximation is not critical. In addition, we explain why segregation variances are often negligible when analyzing the complex polygenic traits that are frequently the focus of evolutionary ecologists and animal breeders. Simulations and an example from an insular meta-population of house sparrows in Norway with three distinct genetic groups illustrate that the method is successful in estimating group-specific additive genetic variances, and that segregation variances are indeed negligible in the empirical example.

CONCLUSIONS

Quantifying differences in additive genetic variance within and among populations is of major biological interest in ecology, evolution, and animal and plant breeding. The proposed method allows to estimate such differences for subpopulations that form a connected set of populations, and may thus also be useful to study temporal or spatial variation of additive genetic variances.

Estimating effective population size for a cestode parasite infecting three-spined sticklebacks

Remarkably few attempts have been made to estimate contemporary effective population size (Ne) for parasitic species, despite the valuable perspectives it can offer on the tempo and pace of parasite evolution as well as coevolutionary dynamics of host-parasite interactions. In this study, we utilized multi-locus microsatellite data to derive single-sample and temporal estimates of contemporary Ne for a cestode parasite (Schistocephalus solidus) as well as three-spined stickleback hosts (Gasterosteus aculeatus) in lakes across Alaska. Consistent with prior studies, both approaches recovered small and highly variable estimates of parasite and host Ne. We also found that estimates of host Ne and parasite Ne were sensitive to assumptions about population genetic structure and connectivity. And, while prior work on the stickleback-cestode system indicates that physiographic factors external to stickleback hosts largely govern genetic variation in S. solidus, our findings indicate that stickleback host attributes and factors internal to the host - namely body length, genetic diversity and infection - shape contemporary Ne of cestode parasites.

Measures of effective population size in sea otters reveal special considerations for wide-ranging species

Conservation genetic techniques and considerations of the evolutionary potential of a species are increasingly being applied to species conservation. For example, effective population size (N e) estimates are useful for determining the conservation status of species, yet accurate estimates of current N e remain difficult to obtain. The effective population size can contribute to setting federal delisting criteria, as was done for the southern sea otter (Enhydra lutris nereis). After being hunted to near extinction during the North Pacific fur trade, the southern sea otter has recovered over part of its former range, but remains at relatively low numbers, making it desirable to obtain accurate and consistent estimates of N e. Although theoretical papers have compared the validity of several methods, comparisons of estimators using empirical data in applied conservation settings are limited. We combined thirteen years of demographic and genetic data from 1,006 sea otters to assess multiple N e estimators, as well as temporal trends in genetic diversity and population genetic structure. Genetic diversity was low and did not increase over time. There was no evidence for distinct genetic units, but some evidence for genetic isolation by distance. In particular, estimates of N e based on demographic data were much larger than genetic estimates when computed for the entire range of the population, but were similar at smaller spatial scales. The discrepancy between estimates at large spatial scales could be driven by cryptic population structure and/or individual differences in reproductive success. We recommend the development of new delisting criteria for the southern sea otter. We advise the use of multiple estimates of N e for other wide-ranging species, species with overlapping generations, or with sex-biased dispersal, as well as the development of improved metrics of genetic assessments of populations.

Frontiers in Metapopulation Biology: The Legacy of Ilkka Hanski

This review of metapopulation biology has a special focus on Professor Ilkka Hanski's (1953–2016) research. Hanski made seminal contributions to both empirical and theoretical metapopulation biology throughout his scientific career. Hanski's early research focused on ecological aspects of metapopulation biology, in particular how the spatial structure of a landscape influences extinction thresholds and how habitat loss and fragmentation can result in extinction debt. Hanski then used the Glanville fritillary system as a natural laboratory within which he studied genetic and evolutionary processes, such as the influence of inbreeding on extinction risk and variation in selection for dispersal traits generated by landscape variation. During the last years of his career, Hanski's work was in the forefront of the rapidly developing field of eco-evolutionary dynamics. Hanski was a pioneer in showing how molecular-level underpinnings of trait variation can explain why evolutionary change can occur rapidly in natural populations and how these changes can subsequently influence ecological dynamics.

Genetic substructure and admixture as important factors in linkage disequilibrium-based estimation of effective number of breeders in recovering wildlife populations

The number of effective breeders (Nb ) and effective population size (Ne ) are population parameters reflective of evolutionary potential, susceptibility to stochasticity, and viability. We have estimated these parameters using the linkage disequilibrium-based approach with LDNE through the latest phase of population recovery of the brown bears (Ursus arctos) in Finland (1993-2010; N = 621). This phase of the recovery was recently documented to be associated with major changes in genetic composition. In particular, differentiation between the northern and the southern genetic cluster declined rapidly within 1.5 generations. Based on this, we have studied effects of the changing genetic structure on Nb and Ne , by comparing estimates for whole Finland with the estimates for the two genetic clusters. We expected a potentially strong relationship between estimate sizes and genetic differentiation, which should disappear as the population recovers and clusters merge. Consistent with this, our estimates for whole Finland were lower than the sum of the estimates of the two genetic clusters and both approaches produced similar estimates in the end. Notably, we also found that admixed genotypes strongly increased the estimates. In all analyses, our estimates for Ne were larger than Nb and likely reflective for brown bears of the larger region of Finland and northwestern Russia. Conclusively, we find that neglecting genetic substructure may lead to a massive underestimation of Nb and Ne . Our results also suggest the need for further empirical analysis focusing on individuals with admixed genotypes and their potential high influence on Nb and Ne .

Estimating demographic contributions to effective population size in an age-structured wild population experiencing environmental and demographic stochasticity

A population's effective size (N_e ) is a key parameter that shapes rates of inbreeding and loss of genetic diversity, thereby influencing evolutionary processes and population viability. However, estimating N_e , and identifying key demographic mechanisms that underlie the N_e to census population size (N) ratio, remains challenging, especially for small populations with overlapping generations and substantial environmental and demographic stochasticity and hence dynamic age-structure. A sophisticated demographic method of estimating N_e /N, which uses Fisher's reproductive value to account for dynamic age-structure, has been formulated. However, this method requires detailed individual- and population-level data on sex- and age-specific reproduction and survival, and has rarely been implemented. Here, we use the reproductive value method and detailed demographic data to estimate N_e /N for a small and apparently isolated red-billed chough (Pyrrhocorax pyrrhocorax) population of high conservation concern. We additionally calculated two single-sample molecular genetic estimates of N_e to corroborate the demographic estimate and examine evidence for unobserved immigration and gene flow. The demographic estimate of N_e /N was 0.21, reflecting a high total demographic variance (σ2dg) of 0.71. Females and males made similar overall contributions to σ2dg. However, contributions varied among sex-age classes, with greater contributions from 3 year-old females than males, but greater contributions from ≥5 year-old males than females. The demographic estimate of N_e was ~30, suggesting that rates of increase of inbreeding and loss of genetic variation per generation will be relatively high. Molecular genetic estimates of N_e computed from linkage disequilibrium and approximate Bayesian computation were approximately 50 and 30, respectively, providing no evidence of substantial unobserved immigration which could bias demographic estimates of N_e . Our analyses identify key sex-age classes contributing to demographic variance and thus decreasing N_e /N in a small age-structured population inhabiting a variable environment. They thereby demonstrate how assessments of N_e can incorporate stochastic sex- and age-specific demography and elucidate key demographic processes affecting a population's evolutionary trajectory and viability. Furthermore, our analyses show that N_e for the focal chough population is critically small, implying that management to re-establish genetic connectivity may be required to ensure population viability.

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.

Nestedness across biological scales

Biological networks pervade nature. They describe systems throughout all levels of biological organization, from molecules regulating metabolism to species interactions that shape ecosystem dynamics. The network thinking revealed recurrent organizational patterns in complex biological systems, such as the formation of semi-independent groups of connected elements (modularity) and non-random distributions of interactions among elements. Other structural patterns, such as nestedness, have been primarily assessed in ecological networks formed by two non-overlapping sets of elements; information on its occurrence on other levels of organization is lacking. Nestedness occurs when interactions of less connected elements form proper subsets of the interactions of more connected elements. Only recently these properties began to be appreciated in one-mode networks (where all elements can interact) which describe a much wider variety of biological phenomena. Here, we compute nestedness in a diverse collection of one-mode networked systems from six different levels of biological organization depicting gene and protein interactions, complex phenotypes, animal societies, metapopulations, food webs and vertebrate metacommunities. Our findings suggest that nestedness emerge independently of interaction type or biological scale and reveal that disparate systems can share nested organization features characterized by inclusive subsets of interacting elements with decreasing connectedness. We primarily explore the implications of a nested structure for each of these studied systems, then theorize on how nested networks are assembled. We hypothesize that nestedness emerges across scales due to processes that, although system-dependent, may share a general compromise between two features: specificity (the number of interactions the elements of the system can have) and affinity (how these elements can be connected to each other). Our findings suggesting occurrence of nestedness throughout biological scales can stimulate the debate on how pervasive nestedness may be in nature, while the theoretical emergent principles can aid further research on commonalities of biological networks.

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.

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.

Is my study system good enough? A case study for identifying maternal effects

In this paper, we demonstrate how simulation studies can be used to answer questions about identifiability and consequences of omitting effects from a model. The methodology is presented through a case study where identifiability of genetic and/or individual (environmental) maternal effects is explored. Our study system is a wild house sparrow (Passer domesticus) population with known pedigree. We fit pedigree‐based (generalized) linear mixed models (animal models), with and without additive genetic and individual maternal effects, and use deviance information criterion (DIC) for choosing between these models. Pedigree and R‐code for simulations are available. For this study system, the simulation studies show that only large maternal effects can be identified. The genetic maternal effect (and similar for individual maternal effect) has to be at least half of the total genetic variance to be identified. The consequences of omitting a maternal effect when it is present are explored. Our results indicate that the total (genetic and individual) variance are accounted for. When an individual (environmental) maternal effect is omitted from the model, this only influences the estimated (direct) individual (environmental) variance. When a genetic maternal effect is omitted from the model, both (direct) genetic and (direct) individual variance estimates are overestimated.

Repeated Habitat Disturbances by Fire Decrease Local Effective Population Size

Effective population size is a fundamental parameter in population genetics, and factors that alter effective population size will shape the genetic characteristics of populations. Habitat disturbance may have a large effect on genetic characteristics of populations by influencing immigration and gene flow, particularly in fragmented habitats. We used the Florida Sand Skink (Plestiodon reynoldsi) to investigate the effect of fire-based habitat disturbances on the effective population size in the highly threatened, severely fragmented, and fire dependent Florida scrub habitat. We screened 7 microsatellite loci in 604 individuals collected from 12 locations at Archbold Biological Station. Archbold Biological Station has an active fire management plan and detailed records of fires dating to 1967. Our objective was to determine how the timing, number, and intervals between fires affect effective population size, focusing on multiple fires in the same location. Effective population size was higher in areas that had not been burned for more than 10 years and decreased with number of fires and shorter time between fires. A similar pattern was observed in abundance: increasing abundance with time-since-fire and decreasing abundance with number of fires. The ratio of effective population size to census size was higher at sites with more recent fires and tended to decrease with time-since-last-fire. These results suggest that habitat disturbances, such as fire, may have a large effect in the genetic characteristics of local populations and that Florida Sand Skinks are well adapted to the natural fire dynamics required to maintain Florida scrub.

Analysis of genetic diversity and population structure of Bellamya quadrata from lakes of middle and lower Yangtze River

As an endemic species of freshwater gastropods in China, Bellamya quadrata plays an important role in ecosystem service provision and commercial importance. However, the species is overharvested and its natural habitats are under severe threat due to fragmentation and loss. To estimate the genetic diversity and population structure of B. quadrata, 285 individuals from eight lake populations across middle and lower Yangtze River were sampled. Seven microsatellite loci were genotyped. Our results showed that (i) the genetic diversity of B. quadrata was high in most of the studied populations, yet effective population sizes appear to be rather small in some populations; (ii) low levels of genetic differentiation exists among populations but gene flow was generally high; (iii) no clear geographic or genetic structure was observed in the studied region, implying mechanisms (zoochoric dispersal and anthropogenic translocations) that enhance dispersal and gene flow have promoted population connectivity. However, the comparatively high genetic diversity of B. quadrata could be attributed to a lag phase, suggesting that the genetic diversity of this species may be lost in the future and the priorities for conservation of B. quadrata are necessary.