Estimating effective population size and migration rates from genetic samples over space and time

Temporal genomics help in deciphering neutral and adaptive patterns in the contemporary evolution of kelp populations

The impact of climate change on populations will be contingent upon their contemporary adaptive evolution. In this study, we investigated the contemporary evolution of 4 populations of the cold-water kelp Laminaria digitata by analyzing their spatial and temporal genomic variations using ddRAD-sequencing. These populations were sampled from the center to the southern margin of its north-eastern Atlantic distribution at 2 time points, spanning at least 2 generations. Through genome scans for local adaptation at a single time point, we identified candidate loci that showed clinal variation correlated with changes in sea surface temperature (SST) along latitudinal gradients. This finding suggests that SST may drive the adaptive response of these kelp populations, although factors such as species' demographic history should also be considered. Additionally, we performed a simulation approach to distinguish the effect of selection from genetic drift in allele frequency changes over time. This enabled the detection of loci in the southernmost population that exhibited temporal differentiation beyond what would be expected from genetic drift alone: these are candidate loci which could have evolved under selection over time. In contrast, we did not detect any outlier locus based on temporal differentiation in the population from the North Sea, which also displayed low and decreasing levels of genetic diversity. The diverse evolutionary scenarios observed among populations can be attributed to variations in the prevalence of selection relative to genetic drift across different environments. Therefore, our study highlights the potential of temporal genomics to offer valuable insights into the contemporary evolution of marine foundation species facing climate change.

Approximate Bayesian Computation applied to time series of population genetic data disentangles rapid genetic changes and demographic variations in a pathogen population

Adaptation can occur at remarkably short timescales in natural populations, leading to drastic changes in phenotypes and genotype frequencies over a few generations only. The inference of demographic parameters can allow understanding how evolutionary forces interact and shape the genetic trajectories of populations during rapid adaptation. Here we propose a new Approximate Bayesian Computation (ABC) framework that couples a forward and individual-based model with temporal genetic data to disentangle genetic changes and demographic variations in a case of rapid adaptation. We test the accuracy of our inferential framework and evaluate the benefit of considering a dense versus sparse sampling. Theoretical investigations demonstrate high accuracy in both model and parameter estimations, even if a strong thinning is applied to time series data. Then, we apply our ABC inferential framework to empirical data describing the population genetic changes of the poplar rust pathogen following a major event of resistance overcoming. We successfully estimate key demographic and genetic parameters, including the proportion of resistant hosts deployed in the landscape and the level of standing genetic variation from which selection occurred. Inferred values are in accordance with our empirical knowledge of this biological system. This new inferential framework, which contrasts with coalescent-based ABC analyses, is promising for a better understanding of evolutionary trajectories of populations subjected to rapid adaptation.

Temporal genetic variation mediated by climate change-induced salinity decline, a study on Artemia (Crustacea: Anostraca) from Kyêbxang Co, a high altitude salt lake on the Qinghai-Tibet Plateau

The Qinghai-Tibet Plateau is one of the areas the richest in salt lakes and Artemia sites. As a result of climate warming and wetting, the areas of salt lakes on the plateau have been increasing, and the salinities have decreased considerably since 1990s. However, the impact of salinity change on the genetic diversity of Artemia is still unknown. Kyêbxang Co is the highest (4620 m above sea level) salt lake currently with commercial harvesting of Artemia resting eggs in the world, and harbors the largest Artemia population on the plateau. Its salinity had dropped from ∼67 ppt in 1998 to ∼39 ppt in 2019. Using 13 microsatellite markers and the mitochondrial cytochrome oxidase submit I (COI) gene, we analyzed the temporal changes of genetic diversity, effective population size and genetic structure of this Artemia population based on samples collected in 1998, 2007 and 2019. Our results revealed a steady decline of genetic diversity and significant genetic differentiation among the sampling years, which may be a consequence of genetic drift and the selection of decreased salinity. A decline of effective population size was also detected, which may be relative to the fluctuation in census population size, skewed sex ratio, and selection of the declined salinity. In 2007 and 2019, the Artemia population showed an excess of heterozygosity and significant deviation from Hardy-Weinberg Equilibrium (p < 0.001), which may be associated with the heterozygote advantage under low salinity. To comprehensively understand the impact of climate warming and wetting on Artemia populations on the plateau, further investigation with broad and intensive sampling are needed.

Planning and implementing genetic rescue of an endangered freshwater fish population in a regulated river, where low flow reduces breeding opportunities and may trigger inbreeding depression

Augmenting depleted genetic diversity can improve the fitness and evolutionary potential of wildlife populations, but developing effective management approaches requires genetically monitored test cases. One such case is the small, isolated and inbred Cotter River population of an endangered Australian freshwater fish, the Macquarie perch Macquaria australasica, which over 3 years (2017-2019) received 71 translocated migrants from a closely related, genetically more diverse population. We used genetic monitoring to test whether immigrants bred, interbred with local fish and augmented population genetic diversity. We also investigated whether levels of river flow affected recruitment, inbreeding depression and juvenile dispersal. Fish length was used to estimate the age, birth year cohort and growth of 524 individuals born between 2016 and 2020 under variable flow conditions. DArT genome-wide genotypes were used to assess individual ancestry, heterozygosity, short-term effective population size and identify parent-offspring and full-sibling families. Of 442 individuals born after translocations commenced, only two (0.45%) were of mixed ancestry; these were half-sibs with one translocated parent in common. Numbers of breeders and genetic diversity for five birth year cohorts of the Cotter River fish were low, especially in low-flow years. Additionally, individuals born in the year of lowest flow evidently suffered from inbreeding depression for juvenile growth. The year of highest flow was associated with the largest number of breeders, lowest inbreeding in the offspring and greatest juvenile dispersal distances. Genetic diversity decreased in the upstream direction, flagging restricted access of breeders to the most upstream breeding sites, exacerbated by low river flow. Our results suggest that the effectiveness of translocations could be increased by focussing on upstream sites and moving more individuals per year; using riverine sources should be considered. Our results indicate that river flow sufficient to facilitate fish movement through the system would increase the number of breeders, promote individuals' growth, reduce inbreeding depression and promote genetic rescue.

Limited impact of vector control on the population genetic structure of Glossina fuscipes fuscipes from the sleeping sickness focus of Maro, Chad

Tsetse flies (genus Glossina) transmit deadly trypanosomes to human populations and domestic animals in sub-Saharan Africa. Some foci of Human African Trypanosomiasis due to Trypanosoma brucei gambiense (g-HAT) persist in southern Chad, where a program of tsetse control was implemented against the local vector Glossina fuscipes fuscipes in 2018 in Maro. We analyzed the population genetics of G. f. fuscipes from the Maro focus before control (T0), one year (T1), and 18 months (T2) after the beginning of control efforts. Most flies captured displayed a local genetic profile (local survivors), but a few flies displayed outlier genotypes. Moreover, disturbance of isolation by distance signature (increase of genetic distance with geographic distance) and effective population size estimates, absence of any genetic signature of a bottleneck, and an increase of genetic diversity between T0 and T2 strongly suggest gene flows from various origins, and a limited impact of the vector control efforts on this tsetse population. Continuous control and surveillance of g-HAT transmission is thus recommended in Maro. Particular attention will need to be paid to the border with the Central African Republic, a country where the entomological and epidemiological status of g-HAT is unknown.

Genetic erosion in an endangered desert fish during a megadrought despite long-term supportive breeding

Human water use combined with a recent megadrought have reduced river and stream flow through the southwest United States and led to periodic drying of formerly perennial river segments. Reductions in snowmelt runoff and increased extent of drying collectively threaten short-lived, obligate aquatic species, including the endangered Rio Grande silvery minnow (Hybognathus amarus). This species is subject to boom-and-bust population dynamics, under which large fluctuations in abundance are expected to lower estimates of effective population size and erode genetic diversity over time. Rates of diversity loss are also affected by additions of hatchery-origin fish used to supplement the wild population. We used demographic and genetic data from wild and hatchery individuals to examine the relationship of genetic diversity and effective population size to abundance over the last two decades. Genetic diversity was low during the early 2000s, but diversity and demographic metrics stabilized after the hatchery program was initiated and environmental conditions improved. Yet, from 2017 onward, allelic diversity declined (Cohen's d = 1.34) and remained low despite hatchery stocking and brief wild population recovery. Across the time series, single-sample estimates of effective population size based on linkage disequilibrium (LD Ne ) were positively associated (r = 0.53) with wild abundance and total abundance, but as the proportion of hatchery-origin spawners increased, LD Ne declined (r = -0.55). Megadrought limited wild spawner abundance and precluded refreshment of hatchery brood stocks with wild fish; hence, we predict a riverine population increasingly dominated by hatchery-origin individuals and accelerated loss of genetic diversity despite supplementation. We recommend an adaptive and accelerated management plan that integrates river flow management and hatchery operations to slow the pace of genetic diversity loss exacerbated by megadrought.

Impact of population structure in the estimation of recent historical effective population size by the software GONE

BACKGROUND

Effective population size (Ne) is a crucial parameter in conservation genetics and animal breeding. A recent method, implemented by the software GONE, has been shown to be rather accurate in estimating recent historical changes in Ne from a single sample of individuals. However, GONE estimations assume that the population being studied has remained isolated for a period of time, that is, without migration or confluence of other populations. If this occurs, the estimates of Ne can be heavily biased. In this paper, we evaluate the impact of migration and admixture on the estimates of historical Ne provided by GONE through a series of computer simulations considering several scenarios: (a) the mixture of two or more ancestral populations; (b) subpopulations that continuously exchange individuals through migration; (c) populations receiving migrants from a large source; and (d) populations with balanced systems of chromosomal inversions, which also generate genetic structure.

RESULTS

Our results indicate that the estimates of historical Ne provided by GONE may be substantially biased when there has been a recent mixture of populations that were previously separated for a long period of time. Similarly, biases may occur when the rate of continued migration between populations is low, or when chromosomal inversions are present at high frequencies. However, some biases due to population structuring can be eliminated by conducting population structure analyses and restricting the estimation to the differentiated groups. In addition, disregarding the genomic regions that are involved in inversions can also remove biases in the estimates of Ne.

CONCLUSIONS

Different kinds of deviations from isolation and panmixia of the populations can generate biases in the recent historical estimates of Ne. Therefore, estimation of past demography could benefit from performing population structure analyses beforehand, by mitigating the impact of these biases on historical Ne estimates.

Effects of subpopulation extinction on effective size (Ne) of metapopulations

Population extinction is ubiquitous in all taxa. Such extirpations can reduce intraspecific diversity, but the extent to which genetic diversity of surviving populations are affected remains largely unclear. A key concept in this context is the effective population size (Ne), which quantifies the rate at which genetic diversity within populations is lost. Ne was developed for single, isolated populations while many natural populations are instead connected to other populations via gene flow. Recent analytical approaches and software permit modelling of Ne of interconnected populations (metapopulations). Here, we apply such tools to investigate how extinction of subpopulations affects Ne of the metapopulation (NeMeta) and of separate surviving subpopulations (NeRx) under different rates and patterns of genetic exchange between subpopulations. We assess extinction effects before and at migration-drift equilibrium. We find that the effect of extinction on NeMeta increases with reduced connectivity, suggesting that stepping stone models of migration are more impacted than island-migration models when the same number of subpopulations are lost. Furthermore, in stepping stone models, after extinction and before a new equilibrium has been reached, NeRx can vary drastically among surviving subpopulations and depends on their initial spatial position relative to extinct ones. Our results demonstrate that extinctions can have far more complex effects on the retention of intraspecific diversity than typically recognized. Metapopulation dynamics need heightened consideration in sustainable management and conservation, e.g., in monitoring genetic diversity, and are relevant to a wide range of species in the ongoing extinction crisis.

Effective population size in a partially clonal plant is not predicted by the number of genetic individuals

Estimating effective population size (N _e) is important for theoretical and practical applications in evolutionary biology and conservation. Nevertheless, estimates of N _e in organisms with complex life-history traits remain scarce because of the challenges associated with estimation methods. Partially clonal plants capable of both vegetative (clonal) growth and sexual reproduction are a common group of organisms for which the discrepancy between the apparent number of individuals (ramets) and the number of genetic individuals (genets) can be striking, and it is unclear how this discrepancy relates to N _e. In this study, we analysed two populations of the orchid Cypripedium calceolus to understand how the rate of clonal versus sexual reproduction affected N _e. We genotyped >1000 ramets at microsatellite and SNP loci, and estimated contemporary N _e with the linkage disequilibrium method, starting from the theoretical expectation that variance in reproductive success among individuals caused by clonal reproduction and by constraints on sexual reproduction would lower N _e. We considered factors potentially affecting our estimates, including different marker types and sampling strategies, and the influence of pseudoreplication in genomic data sets on N _e confidence intervals. The magnitude of N _e/N _ramets and N _e/N _genets ratios we provide may be used as reference points for other species with similar life-history traits. Our findings demonstrate that N _e in partially clonal plants cannot be predicted based on the number of genets generated by sexual reproduction, because demographic changes over time can strongly influence N _e. This is especially relevant in species of conservation concern in which population declines may not be detected by only ascertaining the number of genets.

Evolutionary history and global spatiotemporal pattern of alfalfa mosaic virus

Alfalfa mosaic virus (AMV) is an important plant virus causing considerable economic loss to alfalfa production. Knowledge of the evolutionary and demographic history of the pathogen is limited but essential to the development of effective and sustainable pathogen management schemes. In this study, we performed worldwide phylodynamic analyses of AMV based on 154 nucleotide sequences of the coat protein gene, sampled from 1985 to 2020, to understand the epidemiology of this pathogen. Bayesian phylogenetic reconstruction estimates that the crown group of AMV dates back to 1840 (95% credibility interval, 1687-1955). We revealed that AMV continuously evolves at a rate of 4.14 × 10^-4 substitutions/site/year (95% credibility interval, 1.04 × 10^-4 - 6.68 × 10^-4). Our phylogeographic analyses identified multiple migration links between Europe and other regions, implying that Europe played a key role in spreading the virus worldwide. Further analyses showed that the clustering pattern of AMV isolates is significantly correlated to geographic regions, indicating that geography-driven adaptation may be a factor that affects the evolution of AMV. Our findings may be potentially used in the development of effective control strategies for AMV.

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

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

Potential drivers for schistosomiasis persistence: Population genetic analyses from a cluster-randomized urogenital schistosomiasis elimination trial across the Zanzibar islands

The World Health Organization's revised NTD Roadmap and the newly launched Guidelines target elimination of schistosomiasis as a public health problem in all endemic areas by 2030. Key to meeting this goal is elucidating how selective pressures imposed by interventions shape parasite populations. Our aim was to identify any differential impact of a unique cluster-randomized tri-armed elimination intervention (biannual mass drug administration (MDA) applied alone or in association with either mollusciciding (snail control) or behavioural change interventions) across two Zanzibarian islands (Pemba and Unguja) on the population genetic composition of Schistosoma haematobium over space and time. Fifteen microsatellite loci were used to analyse individual miracidia collected from infected individuals across islands and intervention arms at the start (2012 baseline: 1,522 miracidia from 176 children; 303 from 43 adults; age-range 6-75, mean 12.7 years) and at year 5 (2016: 1,486 miracidia from 146 children; 214 from 25 adults; age-range 9-46, mean 12.4 years). Measures of genetic diversity included allelic richness (Ar), Expected (He) and Observed heterozygosity (Ho), inbreeding coefficient (FST), parentage analysis, estimated worm burden, worm fecundity, and genetic sub-structuring. There was little evidence of differential selective pressures on population genetic diversity, inbreeding or estimated worm burdens by treatment arm, with only the MDA+snail control arm within Unguja showing trends towards reduced diversity and altered inbreeding over time. The greatest differences overall, both in terms of parasite fecundity and genetic sub-structuring, were observed between the islands, consistent with Pemba's persistently higher mean infection intensities compared to neighbouring Unguja, and within islands in terms of infection hotspots (across three definitions). These findings highlight the important contribution of population genetic analyses to elucidate extensive genetic diversity and biological drivers, including potential gene-environmental factors, that may override short term selective pressures imposed by differential disease control strategies. Trial Registration: ClinicalTrials.gov ISRCTN48837681.

MLNe: Simulating and Estimating Effective Size and Migration Rate from Temporal Changes in Allele Frequencies

In studies of molecular ecology, conservation biology and evolutionary biology, the current or recent effective size (Ne) of a population is frequently estimated from the marker genotype data of two or more temporally spaced samples of individuals taken from the population. Despite the developments of numerous Bayesian, likelihood and moment estimators, only a couple of them can use both temporally and spatially spaced samples of individuals to estimate jointly the effective size (Ne) of and the migration rate (m) into a population. In this note I describe new implementations of these joint estimators of Ne and m in software MLNe which runs on multiple platforms (Windows, Mac, Linux) with or without a graphical user interface (GUI), has an integrated simulation module to simulate genotype data for investigating the impacts of various factors (such as sample size and sampling interval) on estimation precision and accuracy, exploits both Message Passing Interface (MPI) and openMP for parallel computations using multiple cores and nodes to speed up analysis. The program does not require data pre-processing and accepts multiple formats of a file of original genotype data and a file of parameters as input. The GUI facilitates data and parameter inputs and produces publication-quality output graphs, while the non-GUI version of software is convenient for batch analysis of multiple datasets as in simulations. MLNe will help advance the analysis of temporal genetic marker data for estimating Ne of and m between populations, which are important parameters that will help biologists for the conservation management of natural and managed populations. MLNe can be downloaded free from the website http://www.zsl.org/science/research/software/.

Analysis of the global origin, evolution and transmission dynamics of the emerging novel variant IBDV (A2dB1b): The accumulation of critical aa-residue mutations and commercial trade contributes to the emergence and transmission of novel variants

The Chinese IBDV novel variant (nvIBDV), belonging to the genotype A2dB1b, an emerging pathotype that can cause subclinical disease with severe, prolonged immunosuppression, poses a new threat to the poultry industry. The process of the global origin, evolution and transmission dynamics of nvIBDV, however, is poorly understood. In this study, phylogenetic trees, site substitutions of amino acid (aa) and highly accurate protein structure modelling, selection pressure, evolutionary and transmission dynamics of nvIBDV were analysed. Interestingly, nvIBDV was classified into the same genogroup with the early US antigenic variants (avIBDV) but in a new lineage with a markedly different and specific pattern of 17 aa-residual substitutions: 13 in VP2 (77D, 213N, 221K, 222T, 249K, 252I, 253Q, 254N, 284A, 286I, 299S, 318D and 323E) and four in VP1 (141I, 163V, 240E and 508K). Importantly, the aa-residues 299S and 163V may play a key role in cell binding and polymerase activity, respectively. The effective population size of the circulating avIBDV experienced two growth phases, respectively, in the years 1999-2007 (in North America) and 2015-2021 (in Asia), which is consistent with the observed trend of the epidemic outbreaks. The most recent common ancestor (tMRCA) of avIBDV most first originated in the USA and was dated around the 1970s. After its emergence, the ancestor virus of this group probably spread to China around the 1990s and the variants experienced a long-term latent circulation with the accumulation of several critical aa-residue mutations in VP2 until re-emerging in 2016. At present, central China has become the epicentre of nvIBDV spread to other parts of China and Asian countries. Importantly, a strong correlation seems to exist between the transmission patterns of virus and the flow of commercial trade of live poultry and products. These findings provide important insights into the origin, evolution and transmission of the nvIBDV and will assist in the development of programs for control strategies for these emerging viruses.

Evolution of flowering time in a selfing annual plant: Roles of adaptation and genetic drift

Resurrection studies are a useful tool to measure how phenotypic traits have changed in populations through time. If these trait modifications correlate with the environmental changes that occurred during the time period, it suggests that the phenotypic changes could be a response to selection. Selfing, through its reduction of effective size, could challenge the ability of a population to adapt to environmental changes. Here, we used a resurrection study to test for adaptation in a selfing population of Medicago truncatula, by comparing the genetic composition and flowering times across 22 generations. We found evidence for evolution toward earlier flowering times by about two days and a peculiar genetic structure, typical of highly selfing populations, where some multilocus genotypes (MLGs) are persistent through time. We used the change in frequency of the MLGs through time as a multilocus fitness measure and built a selection gradient that suggests evolution toward earlier flowering times. Yet, a simulation model revealed that the observed change in flowering time could be explained by drift alone, provided the effective size of the population is small enough (<150). These analyses suffer from the difficulty to estimate the effective size in a highly selfing population, where effective recombination is severely reduced.

Relative Precision of the Sibship and LD Methods for Estimating Effective Population Size With Genomics-Scale Datasets

Computer simulations were used to compare relative precision of 2 widely used single-sample methods for estimating effective population size (Ne)-the sibship method and the linkage disequilibrium (LD) method. Emphasis is on performance when thousands of gene loci are used, which now can easily be achieved even for nonmodel species. Results show that unless Ne is very small, if at least 500-2000 diallelic loci are used, precision of the LD method is higher than the maximum possible precision for the sibship method, which occurs when all sibling relationships have been correctly identified. Results also show that when precision is high for both methods, their estimates of Ne are highly and positively correlated, which limits additional gains in precision that might be obtained by combining information from the 2 estimators.

Predator-Prey Dynamics of Intra-Host Simian Immunodeficiency Virus Evolution Within the Untreated Host

The dynamic nature of the SIV population during disease progression in the SIV/macaque model of AIDS and the factors responsible for its behavior have not been documented, largely owing to the lack of sufficient spatial and temporal sampling of both viral and host data from SIV-infected animals. In this study, we detail Bayesian coalescent inference of the changing collective intra-host viral effective population size (N_e ) from various tissues over the course of infection and its relationship with what we demonstrate is a continuously changing immune cell repertoire within the blood. Although the relative contribution of these factors varied among hosts and time points, the adaptive immune response best explained the overall periodic dynamic behavior of the effective virus population. Data exposing the nature of the relationship between the virus and immune cell populations revealed the plausibility of an eco-evolutionary mathematical model, which was able to mimic the large-scale oscillations in N_e through virus escape from relatively few, early immunodominant responses, followed by slower escape from several subdominant and weakened immune populations. The results of this study suggest that SIV diversity within the untreated host is governed by a predator-prey relationship, wherein differing phases of infection are the result of adaptation in response to varying immune responses. Previous investigations into viral population dynamics using sequence data have focused on single estimates of the effective viral population size (N_e ) or point estimates over sparse sampling data to provide insight into the precise impact of immune selection on virus adaptive behavior. Herein, we describe the use of the coalescent phylogenetic frame- work to estimate the relative changes in N_e over time in order to quantify the relationship with empirical data on the dynamic immune composition of the host. This relationship has allowed us to expand on earlier simulations to build a predator-prey model that explains the deterministic behavior of the virus over the course of disease progression. We show that sequential viral adaptation can occur in response to phases of varying immune pressure, providing a broader picture of the viral response throughout the entire course of progression to AIDS.

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.

Muskrats as a bellwether of a drying delta

Wetlands worldwide are under threat from anthropogenic impacts. In large protected North American areas such as Yellowstone and Wood Buffalo National Parks, aquatic habitats are disappearing and wetland-dependent fauna are in decline^1-3. Here we investigate population dynamics of an indicator species in Canada's Peace-Athabasca Delta ("the delta"), a World Heritage Site. Based on population surveys, habitat mapping and genetic data from 288 muskrats, we use agent-based modeling and genetic analyses to explain population expansion and decline of the semi-aquatic muskrat (Ondatra zibethicus). Simulations quantify a large population (~500,000 individuals) following flood-induced habitat gains, with decreased size (~10,000 individuals) during drying. Genetic analyses show extremely low long-term effective population size (N_e: 60-127), supporting a legacy of population bottlenecks. Our simulations indicate that the muskrat population in the delta is a metapopulation with individuals migrating preferentially along riparian pathways. Related individuals found over 40 km apart imply dispersal distances far greater than their typical home range (130 m). Rapid metapopulation recovery is achieved via riparian corridor migration and passive flood-transport of individuals. Source-sink dynamics show wetland loss impacts on the muskrat metapopulation's spatial extent. Dramatic landscape change is underway, devastating local fauna, including this generalist species even in a protected ecosystem.

A century of genetic homogenization in Baltic salmon-evidence from archival DNA

Intra-species genetic homogenization arising from anthropogenic impacts is a major threat to biodiversity. However, few taxa have sufficient historical material to systematically quantify long-term genetic changes. Using archival DNA collected over approximately 100 years, we assessed spatio-temporal genetic change in Atlantic salmon populations across the Baltic Sea, an area heavily impacted by hydropower exploitation and associated with large-scale mitigation stocking. Analysis was carried out by screening 82 SNPs in 1680 individuals from 13 Swedish rivers. We found an overall decrease in genetic divergence and diminished isolation by distance among populations, strongly indicating genetic homogenization over the past century. We further observed an increase in genetic diversity within populations consistent with increased gene flow. The temporal genetic change was lower in larger wild populations than in smaller wild and hatchery-reared ones, indicating that larger populations have been able to support a high number of native spawners in relation to immigrants. Our results demonstrate that stocking practices of salmon in the Baltic Sea have led to the homogenization of populations over the last century, potentially compromising their ability to adapt to environmental change. Stocking of reared fish is common worldwide, and our study is a cautionary example of the potentially long-term negative effects of such activities.

Genetic structure of recently fragmented suburban populations of European stag beetle

Habitat loss and fragmentation due to urbanization can negatively affect metapopulation persistence when gene flow among populations is reduced and population sizes decrease. Inference of patterns and processes of population connectivity derived from spatial genetic analysis has proven invaluable for conservation and management. However, a more complete account of population dynamics may be obtained by combining spatial and temporal sampling. We, therefore, performed a genetic study on European stag beetle (Lucanus cervus L.) populations in a suburban context using samples collected in three locations and during the period 2002-2016. The sampling area has seen recent landscape changes which resulted in population declines. Through the use of a suite of F ST, clustering analysis, individual assignment, and relatedness analysis, we assessed fine scale spatiotemporal genetic variation within and among habitat patches using 283 individuals successfully genotyped at 17 microsatellites. Our findings suggested the three locations to hold demographically independent populations, at least over time scales of relevance to conservation, though with higher levels of gene flow in the past. Contrary to expectation from tagging studies, dispersal appeared to be mainly female-biased. Although the life cycle of stag beetle suggests its generations to be discrete, no clear temporal structure was identified, which could be attributed to the varying duration of larval development. Since population bottlenecks were detected and estimates of effective number of breeders were low, conservation actions are eminent which should include the establishment of suitable dead wood for oviposition on both local and regional scales to increase (re)colonization success and connectivity among current populations.

Insights from Population Genomics to Enhance and Sustain Biological Control of Insect Pests

Biological control-the use of organisms (e.g., nematodes, arthropods, bacteria, fungi, viruses) for the suppression of insect pest species-is a well-established, ecologically sound and economically profitable tactic for crop protection. This approach has served as a sustainable solution for many insect pest problems for over a century in North America. However, all pest management tactics have associated risks. Specifically, the ecological non-target effects of biological control have been examined in numerous systems. In contrast, the need to understand the short- and long-term evolutionary consequences of human-mediated manipulation of biological control organisms for importation, augmentation and conservation biological control has only recently been acknowledged. Particularly, population genomics presents exceptional opportunities to study adaptive evolution and invasiveness of pests and biological control organisms. Population genomics also provides insights into (1) long-term biological consequences of releases, (2) the ecological success and sustainability of this pest management tactic and (3) non-target effects on native species, populations and ecosystems. Recent advances in genomic sequencing technology and model-based statistical methods to analyze population-scale genomic data provide a much needed impetus for biological control programs to benefit by incorporating a consideration of evolutionary consequences. Here, we review current technology and methods in population genomics and their applications to biological control and include basic guidelines for biological control researchers for implementing genomic technology and statistical modeling.

Social Support and Health Services Use in People Aged over 65 Years Migrating within China: A Cross-Sectional Study

Background: Due to the household registration system, Chinese elderly migrants have insufficient access to health services and social support. Thus, this study examined the use of health services, the access to social support, and the interaction among the elderly migrating within China. Methods: Data were obtained from the China Migrant Dynamic Monitoring Survey in 2015, adopting probability proportionate to size as the sampling strategy. Structural equation modeling and mediating effect tests were employed to explore the associations. Results: Approximately 45.9% of elderly migrants did not seek health services when needed. The use of outpatient and inpatient services was more common than free essential public health services. The use of health services was negatively associated with migrating duration and migrating for offspring, while it was positively associated with outer social support. The mediating effects of outer social support were discovered on the relationships between the use of health services and independent variables such as migrating duration and migrating for offspring, respectively. Conclusion: Elderly migrants with a longer migrating duration or migrated for offspring seem to obtain less outer social support, resulting in a decreased use of health services. Outer social support was suggested as a key effort to improve the equalization of health services in Chinese elderly migrants.

Demographic fluctuations lead to rapid and cyclic shifts in genetic structure among populations of an alpine butterfly, Parnassius smintheus

Many populations, especially in insects, fluctuate in size, and periods of particularly low population size can have strong effects on genetic variation. Effects of demographic bottlenecks on genetic diversity of single populations are widely documented. Effects of bottlenecks on genetic structure among multiple interconnected populations are less studied, as are genetic changes across multiple cycles of demographic collapse and recovery. We take advantage of a long-term data set comprising demographic, genetic and movement data from a network of populations of the butterfly, Parnassius smintheus, to examine the effects of fluctuating population size on spatial genetic structure. We build on a previous study that documented increased genetic differentiation and loss of spatial genetic patterns (isolation by distance and by intervening forest cover) after a network-wide bottleneck event. Here, we show that genetic differentiation was reduced again and spatial patterns returned to the system extremely rapidly, within three years (i.e. generations). We also show that a second bottleneck had similar effects to the first, increasing differentiation and erasing spatial patterns. Thus, bottlenecks consistently drive random divergence of allele frequencies among populations in this system, but these effects are rapidly countered by gene flow during demographic recovery. Our results reveal a system in which the relative influence of genetic drift and gene flow continually shift as populations fluctuate in size, leading to cyclic changes in genetic structure. Our results also suggest caution in the interpretation of patterns of spatial genetic structure, and its association with landscape variables, when measured at only a single point in time.

Genetic structure and variability of tobacco vein banding mosaic virus populations

Tobacco vein banding mosaic virus (TVBMV) is of increasing importance in tobacco production. Knowledge of the genetic structure and variability of the virus population is vital for developing sustainable management. In this study, 24 new TVBMV isolates from Sichuan Province together with 46 previous isolates were studied based on their coat protein sequences. Two distinguishable clades were supported by phylogenetic analysis. The summary statistics PS, AI and MC showed a strong TVBMV-geography association between the isolates from Southwest China (SW) and Mainland China (MC). Further analysis indicated that the spatial genetic structure of TVBMV populations is likely to have been caused by natural selection. Phylogeographic analysis provided strong support for spatial diffusion pathways between the Southwest and Northwest tobacco-producing regions. The TVBMV CP gene was found to be under negative selection, and no significant positive selection of amino acids was detected in the SW group; however, the isolates of the MC group experienced significant positive selection pressure at the first and third amino acid sites of CP. This study suggests that natural selection and habitat heterogeneity are important evolutionary mechanisms affecting the genetic structure of the TVBMV population.

Sporadic Genetic Connectivity among Small Insular Populations of the Rare Geoendemic Plant Caulanthus amplexicaulis var. barbarae (Santa Barbara Jewelflower)

Globally, a small number of plants have adapted to terrestrial outcroppings of serpentine geology, which are characterized by soils with low levels of essential mineral nutrients (N, P, K, Ca, Mo) and toxic levels of heavy metals (Ni, Cr, Co). Paradoxically, many of these plants are restricted to this harsh environment. Caulanthus ampexlicaulis var. barbarae (Brassicaceae) is a rare annual plant that is strictly endemic to a small set of isolated serpentine outcrops in the coastal mountains of central California. The goals of the work presented here were to 1) determine the patterns of genetic connectivity among all known populations of C. ampexlicaulis var. barbarae, and 2) estimate contemporary effective population sizes (Ne), to inform ongoing genomic analyses of the evolutionary history of this taxon, and to provide a foundation upon which to model its future evolutionary potential and long-term viability in a changing environment. Eleven populations of this taxon were sampled, and population-genetic parameters were estimated using 11 nuclear microsatellite markers. Contemporary effective population sizes were estimated using multiple methods and found to be strikingly small (typically Ne < 10). Further, our data showed that a substantial component of genetic connectivity of this taxon is not at equilibrium, and instead showed sporadic gene flow. Several lines of evidence indicate that gene flow between isolated populations is maintained through long-distance seed dispersal (e.g., >1 km), possibly via zoochory.

Negative Density-dependent Dispersal in Tsetse Flies: A Risk for Control Campaigns?

Tsetse flies are vectors of parasites that cause diseases responsible for significant economic losses and health issues in sub-Saharan Africa, including sleeping sickness in humans and nagana in domestic animals. Efficient vector-control campaigns require good knowledge of the demographic parameters of the targeted populations. In the last decade, population genetics emerged as a convenient way to measure population densities and dispersal in tsetse flies. Here, by revealing a strong negative density-dependent dispersal in two dimensions, we suggest that control campaigns might unleash dispersal from untreated areas. If confirmed by direct measurement of dispersal before and after control campaigns, area-wide and/or sequential treatments of neighboring sites will be necessary to prevent this issue.

Do estimates of contemporary effective population size tell us what we want to know?

Estimation of effective population size (N_e) from genetic marker data is a major focus for biodiversity conservation because it is essential to know at what rates inbreeding is increasing and additive genetic variation is lost. But are these the rates assessed when applying commonly used N_e estimation techniques? Here we use recently developed analytical tools and demonstrate that in the case of substructured populations the answer is no. This is because the following: Genetic change can be quantified in several ways reflecting different types of N_e such as inbreeding (N_eI), variance (N_eV), additive genetic variance (N_eAV), linkage disequilibrium equilibrium (N_eLD), eigenvalue (N_eE) and coalescence (N_eCo) effective size. They are all the same for an isolated population of constant size, but the realized values of these effective sizes can differ dramatically in populations under migration. Commonly applied N_e‐estimators target N_eV or N_eLD of individual subpopulations. While such estimates are safe proxies for the rates of inbreeding and loss of additive genetic variation under isolation, we show that they are poor indicators of these rates in populations affected by migration. In fact, both the local and global inbreeding (N_eI) and additive genetic variance (N_eAV) effective sizes are consistently underestimated in a subdivided population. This is serious because these are the effective sizes that are relevant to the widely accepted 50/500 rule for short and long term genetic conservation.  The bias can be infinitely large and is due to inappropriate parameters being estimated when applying theory for isolated populations to subdivided ones.

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.

Bayesian phylodynamic analysis reveals the dispersal patterns of tobacco mosaic virus in China

Tobacco mosaic virus (TMV) is widespread in China and causes considerable economic losses to tobacco production. The molecular epidemiology of this virus is, however, poorly understood. In this study, we sequenced the genomes of 51 TMV isolates from five tobacco-producing regions in China and investigated the dispersal patterns of this virus. Our phylogenetic analysis showed that TMV might have been introduced to China in the early 1900s, probably first to southwest China. However, TMV then moved to the north of the country, where it expanded. The north became the main seeding region for the subsequent movements of the virus within China. The north-to-south movement of TMV coincides with a shift of major tobacco-producing areas from north to south in this century, suggesting a link between human activities and the dispersal of TMV in China.

Exploring the causes of small effective population sizes in cyst nematodes using artificial Globodera pallida populations

The effective size of a population is the size of an ideal population which would undergo genetic drift at the same rate as the real population. The balance between selection and genetic drift depends on the effective population size ( Ne), rather than the real numbers of individuals in the population ( N). The objectives of the present study were to estimate Ne in the potato cyst nematode Globodera pallida and to explore the causes of a low Ne/ N ratio in cyst nematodes using artificial populations. Using a temporal analysis of 24 independent populations, the median Ne was 58 individuals (min Ne = 25 and max Ne = 228). Ne is commonly lower than N but in the case of cyst nematodes, the Ne/ N ratio was extremely low. Using artificial populations showed that this low ratio did not result from migration, selection and overlapping generations, but could be explain by the fact that G. pallida populations deviate in structure from the assumptions of the ideal population by having unequal sex ratios, high levels of inbreeding and a high variance in family sizes. The consequences of a low Ne, resulting in a strong intensity of genetic drift, could be important for their control because G. pallida populations will have a low capacity to adapt to changing environments.

The effect of sample size on estimates of genetic differentiation and effective population size for Schistosoma mansoni populations

Eradication or local extinction of the human parasite Schistosoma mansoni is a goal for many control programs. Population genetic analyses are helping to evaluate and guide these efforts, yet what to sample, how to sample and how densely to sample is not well established. We determined the S. mansoni allele frequency profile of nearly all infected inhabitants in two small Brazilian communities and created sub-samples representing 5-50% of all detected human infections (infrapopulations). Samples were selected at random with replacement, and each size class was replicated 100 times. Mean pairwise differentiation for all infrapopulations (Di) and the variance effective population size (Ne) were calculated for each sample. Prior to community-wide treatment, the true mean Di was moderate (0.095-0.123) and Ne large (>30,000). Most samples of <50% of those infected produced estimates outside of 5% of the true value. For estimates within 10%, sample sizes of >15% of all infrapopulations were required. At the 3 year follow-up after treatment, the Di increased and Ne was reduced by >15 fold. At this time sampling of >30-45% was needed to achieve the same accuracy. Following a second treatment and 4 years from baseline, the Di further increased and Ne decreased with little change in the sampling effort required. Extensive sampling is required for accurate estimates of these important population parameters. Characteristics such as population census size, infection prevalence, the community's treatment history and the degree of infrapopulation differentiation should be taken into account. The intensity of infection was weakly correlated with the ability of a single infrapopulation to represent the component population (Dic), indicating a tendency toward random acquisition of parasite genotypes. This also suggests that targeted sampling from those most heavily infected will better represent the genetic diversity of the whole community than a random sample of infrapopulations.

Spatio-temporal population genetic structure, relative to demographic and ecological characteristics, in the freshwater snail Biomphalaria pfeifferi in Man, western Côte d'Ivoire

Combining the analysis of spatial and temporal variation when investigating population structure enhances our capacity for unravelling the biotic and abiotic factors responsible for microevolutionary change. This work aimed at measuring the spatial and temporal genetic structure of populations of the freshwater snail Biomphalaria pfeifferi (the intermediate host of the trematode Schistosoma mansoni) in relation to the mating system (self-fertilization), demography, parasite prevalence and some ecological parameters. Snail populations were sampled four times in seven human-water contact sites in the Man region, western Côte d'Ivoire, and their variability was measured at five microsatellite loci. Limited genetic diversity and high selfing rates were observed in the populations studied. We failed to reveal an effect of demographic and ecological parameters on within-population diversity, perhaps as a result of a too small number of populations. A strong spatial genetic differentiation was detected among populations. The temporal differentiation within populations was high in most populations, though lower than the spatial differentiation. All estimates of effective population size were lower than seven suggesting a strong effect of genetic drift. However, the genetic drift was compensated by high gene flow. The genetic structure within and among populations reflected that observed in other selfing snail species, relying on high selfing rates, low effective population sizes, environmental stochasticity and high gene flow.

Population connectivity and larval dispersal of the exploited mangrove crab Ucides cordatus along the Brazilian coast

BACKGROUND

The mangrove crab Ucides cordatus is considered a key species for the ecological balance of mangrove forests and a major source of employment and income for traditional crab collectors in Brazil. Several studies evidenced weak genetic variation among populations due to an efficient larval transport. However, gene flow patterns of the species is poorly understood, with no information about migration rates. The influence of the two main Brazilian currents in larval dispersion is also not clear. In order to provide baseline information for conservation, planning and management of this important fishery resource, the present study aimed to estimate and evaluate spatial distribution of genetic diversity, migration rates and gene flow directivity among populations of U. cordatus in Brazil.

METHODS

Nine microsatellites were used to resolve population structure of 319 crabs collected from six sites located along the Brazilian coast. The degree of geographical differentiation included estimates of genetic diversity, population structure and gene flow models, with spatial analysis of shared alleles (SAShA), isolation by distance tests, AMOVA, discriminant analysis of principal components (DAPC) and Bayesian clustering. We estimated the amount of ongoing gene flow between clusters using the coalescent-based method implemented in Migrate-N.

RESULTS

Loci were highly polymorphic (average of 12.4 alleles per locus) evidencing high genetic variability. There was significant differentiation among localities, despite of the low value of FST (= 0.019; P < 0.001). FST and Jost's D indexes were also estimated in pairwise comparisons and showed significant differences between most of the surveyed site pairs (P < 0.05). Structure evidenced a single genetic group among samples, however SAShA pointed to a non-panmictic condition (P = 0.011). AMOVA detected four statistical significant clusters with low level of differentiation (FCT = 0.037; P = 0.023). The gene flow model that best described the population connectivity was the island model, with ∼24 crabs being exchanged among localities per generation.

DISCUSSION

The high migration rates found among localities seem to be the main force acting to sustain the distribution of the genetic diversity of U. cordatus. Despite the high gene flow and the weak population structure among samples, the significant genetic differences found suggest that gene flow alone does not bypass the effects of genetic drift, natural selection and/or human exploitation. These findings are vital for the establishment of a database to be used in the development of conservation programs.

Development and Characterization of Novel Genic-SSR Markers in Apple-Juniper Rust Pathogen Gymnosporangium yamadae (Pucciniales: Pucciniaceae) Using Next-Generation Sequencing

The Apple-Juniper rust, Gymnosporangium yamadae, is an economically important pathogen of apples and junipers in Asia. The absence of markers has hampered the study of the genetic diversity of this widespread pathogen. In our study, we developed twenty-two novel microsatellite markers for G. yamadae from randomly sequenced regions of the transcriptome, using next-generation sequencing methods. These polymorphic markers were also tested on 96 G. yamadae individuals from two geographical populations. The allele numbers ranged from 2 to 9 with an average value of 6 per locus. The polymorphism information content (PIC) values ranged from 0.099 to 0.782 with an average value of 0.48. Furthermore, the observed (H_O) and expected (H_E) heterozygosity ranged from 0.000 to 0.683 and 0.04 to 0.820, respectively. These novel developed microsatellites provide abundant molecular markers for investigating the genetic structure and genetic diversity of G. yamadae, which will help us to better understand disease epidemics and the origin and migration routes of the Apple-Juniper rust pathogen. Further studies will also be completed to dissect how human activities influence the formation of current population structures. Furthermore, these SSR (simple sequence repeat) markers can also be used as tools to identify virulence by mapping the whole genomes of different virulent populations. These markers will, thus, assist the development of effective risk-assessment models and management systems for the Apple-Juniper rust pathogen.

Statistical Inference in the Wright-Fisher Model Using Allele Frequency Data

The Wright–Fisher model provides an elegant mathematical framework for understanding allele frequency data. In particular, the model can be used to infer the demographic history of species and identify loci under selection. A crucial quantity for inference under the Wright–Fisher model is the distribution of allele frequencies (DAF). Despite the apparent simplicity of the model, the calculation of the DAF is challenging. We review and discuss strategies for approximating the DAF, and how these are used in methods that perform inference from allele frequency data. Various evolutionary forces can be incorporated in the Wright–Fisher model, and we consider these in turn. We begin our review with the basic bi-allelic Wright–Fisher model where random genetic drift is the only evolutionary force. We then consider mutation, migration, and selection. In particular, we compare diffusion-based and moment-based methods in terms of accuracy, computational efficiency, and analytical tractability. We conclude with a brief overview of the multi-allelic process with a general mutation model.

Evaluating methods to visualize patterns of genetic differentiation on a landscape

With advances in sequencing technology, research in the field of landscape genetics can now be conducted at unprecedented spatial and genomic scales. This has been especially evident when using sequence data to visualize patterns of genetic differentiation across a landscape due to demographic history, including changes in migration. Two recent model-based visualization methods that can highlight unusual patterns of genetic differentiation across a landscape, SpaceMix and EEMS, are increasingly used. While SpaceMix's model can infer long-distance migration, EEMS' model is more sensitive to short-distance changes in genetic differentiation, and it is unclear how these differences may affect their results in various situations. Here, we compare SpaceMix and EEMS side by side using landscape genetics simulations representing different migration scenarios. While both methods excel when patterns of simulated migration closely match their underlying models, they can produce either un-intuitive or misleading results when the simulated migration patterns match their models less well, and this may be difficult to assess in empirical data sets. We also introduce unbundled principal components (un-PC), a fast, model-free method to visualize patterns of genetic differentiation by combining principal components analysis (PCA), which is already used in many landscape genetics studies, with the locations of sampled individuals. Un-PC has characteristics of both SpaceMix and EEMS and works well with simulated and empirical data. Finally, we introduce msLandscape, a collection of tools that streamline the creation of customizable landscape-scale simulations using the popular coalescent simulator ms and conversion of the simulated data for use with un-PC, SpaceMix and EEMS.

Performance of IUCN proxies for generation length

One of the criteria used by the International Union for Conservation of Nature (IUCN) to assess threat status is the rate of decline in abundance over 3 generations or 10 years, whichever is longer. The traditional method for calculating generation length (T) uses age-specific survival and fecundity, but these data are rarely available. Consequently, proxies that require less information are often used, which introduces potential biases. The IUCN recommends 2 proxies based on adult mortality rate, T̂d = α + 1/d, and reproductive life span, T̂z = α + z^* RL, where α is age at first reproduction, d is adult mortality rate, RL is reproductive life span, and z is a coefficient derived from data for comparable species. We used published life tables for 78 animal and plant populations to evaluate precision and bias of these proxies by comparing T̂d and T̂z with true generation length. Mean error rates in estimating T were 31% for T̂d and 20% for T̂z, but error rates for T̂d were 16% when we subtracted 1 year ( T̂d( adj )=T̂d-1 ), as suggested by theory; T̂d( adj ) also provided largely unbiased estimates regardless of the true generation length. Performance of T̂z depends on compilation of detailed data for comparable species, but our results suggest taxonomy is not a reliable indicator of comparability. All 3 proxies depend heavily on a reliable estimate of age at first reproduction, as we illustrated with 2 test species. The relatively large mean errors for all proxies emphasized the importance of collecting the detailed life-history information necessary to calculate true generation length. Unfortunately, publication of such data is less common than it was decades ago. We identified generic patterns of age-specific change in vital rates that can be used to predict expected patterns of bias from applying T̂d( adj ).