Sexual selection has minimal impact on effective population sizes in species with high rates of random offspring mortality: An empirical demonstration using fitness distributions

The effective population size (N_e) is a fundamental parameter in population genetics that influences the rate of loss of genetic diversity. Sexual selection has the potential to reduce N_e by causing the sex‐specific distributions of individuals that successfully reproduce to diverge. To empirically estimate the effect of sexual selection on N_e, we obtained fitness distributions for males and females from an outbred, laboratory‐adapted population of Drosophila melanogaster. We observed strong sexual selection in this population (the variance in male reproductive success was ～14 times higher than that for females), but found that sexual selection had only a modest effect on N_e, which was 75% of the census size. This occurs because the substantial random offspring mortality in this population diminishes the effects of sexual selection on N_e, a result that necessarily applies to other high fecundity species. The inclusion of this random offspring mortality creates a scaling effect that reduces the variance/mean ratios for male and female reproductive success and causes them to converge. Our results demonstrate that measuring reproductive success without considering offspring mortality can underestimate N_e and overestimate the genetic consequences of sexual selection. Similarly, comparing genetic diversity among different genomic components may fail to detect strong sexual selection.     

Effective size of an Atlantic salmon (Salmo salar L.) metapopulation in Northern Spain

The genetic diversity of metapopulations is influenced not only by the effective sizes (N _e ) of individual subpopulations, but also by the total effective size of the metapopulation (meta-N _e ). We estimated meta-N _e of four neighbouring Atlantic salmon populations connected by gene flow using genetic estimates of subpopulation N _e s and migration rates derived from capture–recapture data. The meta-[^(N)]_e meta{\hbox{-}}\hat{N}_{e} was lower than the sum of [^(N)]_e \hat{N}_{e} s of the subpopulations, suggesting that genetic diversity harboured by the four river salmon metapopulation is lower than what would have been expected by viewing individual subpopulations separately. In addition, meta-[^(N)]_e meta{\hbox{-}}\hat{N}_{e} was found to be sensitive to changes in [^(N)]_e \hat{N}_{e} of the subpopulation from which net emigration rate was largest, so as that the genetic diversity of the metapopulation would be best preserved by avoiding any reductions in N _e of this subpopulation. Yet, this subpopulation is the one that has historically—and still is—experiencing the highest exploitation rate in the metapopulation system.     

INCREASED PROBABILITY OF EXTINCTION DUE TO DECREASED GENETIC EFFECTIVE POPULATION SIZE: EXPERIMENTAL POPULATIONS OF CLARKIA PULCHELLA

We established replicated experimental populations of the annual plant Clarkia pulchella to evaluate the existence of a causal relationship between loss of genetic variation and population survival probability. Two treatments differing in the relatedness of the founders, and thus in the genetic effective population size (N_e), were maintained as isolated populations in a natural environment. After three generations, the low N_e treatment had significantly lower germination and survival rates than did the high N_e treatment. These lower germination and survival rates led to decreased mean fitness in the low N_e populations: estimated mean fitness in the low N_e populations was only 21% of the estimated mean fitness in the high N_e populations. This inbreeding depression led to a reduction in population survival: at the conclusion of the experiment, 75% of the high N_e populations were still extant, whereas only 31% of the low N_e populations had survived. Decreased genetic effective population size, which leads to both inbreeding and the loss of alleles by genetic drift, increased the probability of population extinction over that expected from demographic and environmental stochasticity alone. This demonstrates that the genetic effective population size can strongly affect the probability of population persistence.     

Comparisons of genetic parameters and clonal value predictions from clonal trials and seedling base population trials of radiata pine

Different methods for predicting clonal values were explored for diameter growth (diameter at breast height (DBH)) in a radiata pine clonal forestry program: (1) clones were analyzed with a full model in which the total genetic variation was partitioned into additive, dominance, and epistasis (Clone Only—Full Model); (2) clones were analyzed together with seedling base population data (Clone Plus Seedling (CPS)), and (3) clones were analyzed with a reduced model in which the only genetic term was the total genetic variance (Clone Only—Reduced Model). DBH was assessed at age 5 for clones and between ages 4 to 13 at the seedling trials. Significant additive, dominance, and epistatic genetic effects were estimated for DBH using the CPS model. Nonadditive genetic effects for DBH were 87% as large as additive genetic effects. Narrow-sense () and broad-sense () heritability estimates for DBH using the CPS model were 0.14 ± 0.01 and 0.26 ± 0.01, respectively. Accuracy of predicted clonal values increased 4% by combining the clone and seedling data over using clonal data alone, resulting in greater confidence in the predicted genetic performance of clones. Our results indicate that exploiting nonadditive genetic effects in clonal varieties will generate greater gains than that typically obtainable from conventional family-based forestry of radiata pine. The predicted genetic gain for DBH from deployment of the top 5% of clones was 24.0%—an improvement of more than 100% over family forestry at the same selection intensity. We conclude that it is best practice to predict clonal values by incorporating seedling base population data in the clonal analysis.     

Population Size and Selection Intensity Effects on Long-Term Selection Response in Mice

Long-term response to within full-sib family selection for increased postweaning gain was evaluated in lines having different effective population sizes (N_e) and selection intensities (i). Line designations were I4(4), I8(2), I16(2), M4(4), M8(2) and M16(2), where I and M indicate selection of the top 50% and 25%, respectively; 4, 8 and 16 represent the number of parental pairs per replicate and number of replicates is given in parentheses. Realized within full-sib family heritabilities (h_R²) in the first phase of selection (0-14 generations) were larger in 16-pair lines than in 4- and 8-pair lines. In the second phase of selection (>14 generations), h_R² declined significantly (P<.01) in all lines, and only the I16 and M16 lines had h_R² values significantly (P<.01) greater than zero. Realized genetic correlations involving number born, 12-day litter weight, weaning weight and six-week weight tended to decline in the second phase of selection. The I16, M16 and control (C16) replicates were crossed in all combinations at generation 14. Crosses were then selected within litters for high postweaning gain. The h_R² values in the crossbred lines were all larger than those in the second selection phase for M16-1, M16-2 and I16-1, but not for I16-2. Within each N_e level, total response was significantly (P<.01) less for I lines compared with M lines. Total response increased as N_e increased, within each level of i. Relatively small differences in realized i values among N_e lines could not account for this result. The difference in total response among the N_e lines at a given selection intensity may be due to inbreeding depression and a combination of interactions involving "drift" and selection. By crossing replicates of the M lines with the C16 control, the effects of inbreeding depression were removed. Inbreeding depression and genetic drift, as defined herein, were equally important in accounting for differences among N_e lines in total response.     

Estimating effective population size using RADseq: Effects of SNP selection and sample size

Effective population size (N_e) is a key parameter of population genetics. However, N_e remains challenging to estimate for natural populations as several factors are likely to bias estimates. These factors include sampling design, sequencing method, and data filtering. One issue inherent to the restriction site‐associated DNA sequencing (RADseq) protocol is missing data and SNP selection criteria (e.g., minimum minor allele frequency, number of SNPs). To evaluate the potential impact of SNP selection criteria on N_e estimates (Linkage Disequilibrium method) we used RADseq data for a nonmodel species, the thornback ray. In this data set, the inbreeding coefficient F_IS was positively correlated with the amount of missing data, implying data were missing nonrandomly. The precision of N_eestimates decreased with the number of SNPs. Mean N_e estimates (averaged across 50 random data sets with2000 SNPs) ranged between 237 and 1784. Increasing the percentage of missing data from 25% to 50% increased N_e estimates between 82% and 120%, while increasing the minor allele frequency (MAF) threshold from 0.01 to 0.1 decreased estimates between 71% and 75%. Considering these effects is important when interpreting RADseq data‐derived estimates of effective population size in empirical studies.     

EFFECTIVE POPULATION SIZE AND GENETIC DRIFT IN TRISTYLOUS EICHHORNIA PANICULATA (PONTEDERIACEAE)

Populations of the tristylous, annual Eichhornia paniculata are markedly differentiated with respect to frequency of mating types. This variation is associated with evolutionary changes in mating system, from predominant outcrossing to high self-fertilization. To assess the potential influence of genetic drift acting on this variation, we estimated effective population size in 10 populations from northeastern Brazil using genetic and demographic methods. Effective size (N_e) was inferred from temporal changes in allele frequency at two to eight isozyme loci and also calculated using five demographic variables: 1) the number of flowering individuals (N); 2) temporal fluctuations in N; 3) variance in flower number; 4) frequency of mating types; and 5) selfing rate. Average N_e based on isozyme data was 15.8, range 3.4–70.6, and represented a fraction (mean N_e/N = 0.106) of the census number of individuals (mean N = 762.8; range: 30.5–5,040). Temporal variation in N and variance in flower number each reduced N_e to about a half of N whereas mating type frequencies and selfing rate caused only small reductions in N_e relative to N. All estimates of N_e based on demographic variables were considerably larger than those obtained from genetic data. The two kinds of estimates were in general agreement, however, when all demographic variables were combined into a single measure. Monte Carlo simulations indicated that effective size must be fewer than about 40 for drift to overcome the frequency-dependent selection that maintains the polymorphism for mating type. Applying the average N_e/N value to 167 populations censused in northeastern Brazil indicated that 72% had effective sizes below this number. This suggests that genetic drift is likely to play a dominant role in natural populations of E. paniculata.     

Effective population size does not predict codon usage bias in mammals

Synonymous codons are not used at equal frequency throughout the genome, a phenomenon termed codon usage bias (CUB). It is often assumed that interspecific variation in the intensity of CUB is related to species differences in effective population sizes (N_e), with selection on CUB operating less efficiently in species with small N_e. Here, we specifically ask whether variation in N_e predicts differences in CUB in mammals and report two main findings. First, across 41 mammalian genomes, CUB was not correlated with two indirect proxies of N_e (body mass and generation time), even though there was statistically significant evidence of selection shaping CUB across all species. Interestingly, autosomal genes showed higher codon usage bias compared to X‐linked genes, and high‐recombination genes showed higher codon usage bias compared to low recombination genes, suggesting intraspecific variation in N_e predicts variation in CUB. Second, across six mammalian species with genetic estimates of N_e (human, chimpanzee, rabbit, and three mouse species: Mus musculus, M. domesticus, and M. castaneus), N_e and CUB were weakly and inconsistently correlated. At least in mammals, interspecific divergence in N_e does not strongly predict variation in CUB. One hypothesis is that each species responds to a unique distribution of selection coefficients, confounding any straightforward link between N_e and CUB.     

Temporal genetic samples indicate small effective population size of the endangered yellow-eyed penguin

There is an increasing awareness that the long-term viability of endemic island populations is negatively affected by genetic factors associated with population bottlenecks and/or persistence at small population size. Here we use contemporary samples and historic museum specimens (collected 1888–1938) to estimate the effective population size (N _e) for the endangered yellow-eyed penguin (Megadyptes antipodes) in South Island, New Zealand, and evaluate the genetic concern for this iconic species. The South Island population of M. antipodes—constituting almost half of the species’ census size—is thought to be descended from a small number of founders that reached New Zealand just a few hundred years ago. Despite intensive conservation measures, this population has shown dramatic fluctuations in size over recent decades. We compare estimates of the harmonic mean N _e for this population, obtained using one moment and three likelihood based-temporal methods, including one method that simultaneously estimates migration rate. Evaluation of the N _e estimates reveals a harmonic mean N _e in the low hundreds. Additionally, the inferred low immigration rates (m = 0.003) agree well with contemporary migration rate estimates between the South Island and subantarctic populations of M. antipodes. The low N _e of South Island M. antipodes is likely affected by strong fluctuations in population size, and high variance in reproductive success. These results show that genetic concerns for this population are valid and that the long-term viability of this species may be compromised by reduced adaptive potential.     

Breeding without breeding: minimum fingerprinting effort with respect to the effective population size

We present a probabilistic model to minimize the fingerprinting effort associated with the implementation of the “breeding without breeding” scheme under partial pedigree reconstruction. Our approach is directed at achieving a declared target population’s minimum effective population size (N _e ), following the pedigree reconstruction and genotypic selection and is based on the graph theory algorithm. The primary advantage of the proposed method is to reduce the cost associated with fingerprinting before the implementation of the pedigree reconstruction for seed parent–offspring derived from breeding arboreta and production or natural populations. Stochastic simulation was conducted to test the method’s efficiency assuming a simple polygenic model and a single trait. Hypothetical population consisted of 30 parental trees that were paired at random (selfing excluded), resulting in 600 individuals (potential candidates for forwards selection). The male parentage was assumed initially unknown. The model was used to estimate the minimum genotyping sample size needed to reaching the prescribed N _e . Results were compared with the known pedigree data. The model was successful in revealing the true relationship pattern over the whole range of N _e . Two to three offspring entered genotyping to meet the N _e  = 2 while 41 to 43 were required to satisfy the N _e  = 14. Importantly, genetic gain was affected at the lower limits of the genotyping effort. Doubling the number of parents resulted in considerable reduction of the genotyping effort at higher N _e values.     

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

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

Contemporary effective population size and predicted maintenance of genetic diversity in the endangered kea (Nestor notabilis)

Population size and the potential for maintenance of genetic diversity are critical information for the monitoring of species of conservation concern. However, direct estimates of population size are not always feasible, making indirect genetic approaches a valuable alternative. We estimated contemporary effective population size (N_e) in the endangered kea (Nestor notabilis) using three different methods. We then inferred the census size (N_C) using published N_e/N_C ratios and modelled the future maintenance of genetic diversity assuming a number of demographic parameters. Short-term N_e was small with a range-wide N_e?N_C was within the range of the current estimate (c. 1000–5000). Forward simulations showed low probability of retaining 90% of rare alleles without immigration. However, the probability of maintaining genetic diversity was high with immigration, juvenile survival of?≥?30%, and an initial sex ratio of c. 0.5–0.6. Despite the low N_e in kea, predator control and/or artificial immigration might be sufficient to maintain the present genetic diversity.     

Reconciling Genetic and Demographic Estimators of Effective Population Size in the Anuran Amphibian Bufo Calamita

We used genetic and demographic methods to estimate the variance effective population sizes (N _e) of three populations of natterjack toads Bufo calamita in Britain. This amphibian breeds in temporary pools where survival rates can vary among families. Census population sizes (N) were derived from spawn string counts. Point and coalescent-based maximum likelihood estimates of N _e based on microsatellite allele distributions were similar. N _e/N ratios based on genetic estimates of N _e ranged between 0.02 and 0.20. Mean demographic estimates of N _e were consistently higher (2.7–8.0-fold) than genetic estimates for all three populations when variance in breeding success was evaluated at the point where females no longer influence their progeny. However, discrepancies between genetic and demographic estimators could be removed by using a model that included extra variance in survivorship (above to Poisson expectations) among families. The implications of these results for the estimation of N _e in wild populations are discussed.     

The influence of variation in female fecundity on effective population size

Understanding the relationship between effective population size (N_e) and the number of adults in a population (N) is important for predicting genetic change in small populations. In general, N_e is expected to be close to N/2, i.e. in the range N/4-3N/4, provided that the powerful effect of population bottlenecks on reducing N_e is factored out (using the harmonic mean of N). However, some very low published estimates of N_e/N(< 0.1) raise the possibility that other factors acting to reduce N_e have been underestimated. Here one such factor, variation in female fecundity, is investigated. Its effect on N_e depends on the standardized variance in fecundity (per breeding season), a measure that is generally independent of mean fecundity. Empirical estimates of this standardized variance from 16 animal studies yielded an average value of 0.44, and a maximum value less than 1.5. To investigate the effect of such values, three kinds of fecundity variation were modelled: random (seasonal): individual; and age-related. Fixed individual differences among females reduce N_e the most. However, to reduce N_e to N/10, the resulting standardized variance must usually be 10 or more. Random differences need to be even larger to achieve the same reduction. One possible mechanism, the random loss of whole families, requires very high family mortality (90% or more). The third model, fecundity that increases linearly with age, is ineffective at causing a marked decrease in N_e. Given the finding that very unusual conditions are required to reduce N_e below N_e/10, low estimates of N_e/N need to be examined critically: the lowest published ratio, for a natural population of oysters, was found to be questionable because of possible immigration into the population by cultivated oysters.     

Small effective population sizes of two remnant ocelot populations (<Emphasis Type="Italic">Leopardus pardalis albescens</Emphasis>) in the United States

Threatened populations are vulnerable to the effects of genetic drift and inbreeding, particularly when gene flow is low and the effective population size is small. Estimates of effective population size (N _e ) provide important information on the status of endangered populations that have experienced severe fragmentation and serve as indicators of genetic viability. Genetic data from microsatellite loci were used to estimate N _e for the 2 remaining populations of the endangered ocelot (Leopardus pardalis albescens) occurring in the United States. Several methods were used to calculate N _e , resulting in estimates ranging from N _e  = 8.0 (95% CI: 3.2–23.1) to 13.9 (95% CI: 7.7–25.1) for the population located at the Laguna Atascosa Wildlife Refuge in Cameron County, Texas. The ocelot population in Willacy County, Texas, had N _e estimates of 2.9 (95% CI: 1.7–5.6) and 3.1 (95% CI: 1.9–13.5), respectively. Estimates of N _e in both populations were below the critical value recommended for short-term viability.     

GENE FLOW AND MITOCHONDRIAL DNA VARIATION IN THE KILLIFISH,FUNDULUS HETEROCLITUS

Two subspecies of killifish, Fundulus heteroclitus, inhabit the Atlantic coast of the United States. The contact zones between them are typified by morphological, physiological, nuclear gene, and mitochondrial DNA clines. Considerable debate exists about the importance of restricted gene flow and natural selection in maintaining these clines. To evaluate the relative importance of these two evolutionary forces we employed analysis of mtDNA as an independent measure of gene flow. Solutions of equilibrium diffusion equations suggested that killifish dispersal must be less than 2 km to maintain previously observed allozyme frequency clines in the absence of strong selection. To determine whether populations separated by distances greater than 2 km accumulate significant genetic differences we examined a total of N = 480 individuals from five killifish populations spanning a continuous shoreline distance of 8.4 km. Distribution of the 25 detected haplotypes indicated that most of the variation was within rather than between sampling locations. No evidence of geographic structure was detected, nor were there any significant genetic differences between killifish populations. With these data, gene flow was evaluated by estimating effective migration rate (N_em) between the populations. N_em was estimated from G_st(N_em = 49.4), from F_st (N_em = 24.1), by the private alleles approach (N_em = 18.5) and via four phylogenetic analyses (N_em ranged from 11.4 to 16.9). Regardless of the analysis, N_em was greater than one; the threshold level at which gene flow is strong enough to prevent differentiation due to genetic drift. This suggests that while the characteristics that distinguish Fundulus subspecies may have arisen in isolation, the current clinal distributions exhibited along the Atlantic coast are most likely maintained by selection.     

Genomewide patterns of variation in genetic diversity are shared among populations,species and higher‐order taxa

Genomewide screens of genetic variation within and between populations can reveal signatures of selection implicated in adaptation and speciation. Genomic regions with low genetic diversity and elevated differentiation reflective of locally reduced effective population sizes (N_e) are candidates for barrier loci contributing to population divergence. Yet, such candidate genomic regions need not arise as a result of selection promoting adaptation or advancing reproductive isolation. Linked selection unrelated to lineage‐specific adaptation or population divergence can generate comparable signatures. It is challenging to distinguish between these processes, particularly when diverging populations share ancestral genetic variation. In this study, we took a comparative approach using population assemblages from distant clades assessing genomic parallelism of variation in N_e. Utilizing population‐level polymorphism data from 444 resequenced genomes of three avian clades spanning 50 million years of evolution, we tested whether population genetic summary statistics reflecting genomewide variation in N_e would covary among populations within clades, and importantly, also among clades where lineage sorting has been completed. All statistics including population‐scaled recombination rate (ρ), nucleotide diversity (π) and measures of genetic differentiation between populations (F_ST, PBS, d_xy) were significantly correlated across all phylogenetic distances. Moreover, genomic regions with elevated levels of genetic differentiation were associated with inferred pericentromeric and subtelomeric regions. The phylogenetic stability of diversity landscapes and stable association with genomic features support a role of linked selection not necessarily associated with adaptation and speciation in shaping patterns of genomewide heterogeneity in genetic diversity.     

Effects of population characteristics and structure on estimates of effective population size in a house sparrow metapopulation

Effective population size (N_e) is a key parameter to understand evolutionary processes and the viability of endangered populations as it determines the rate of genetic drift and inbreeding. Low N_e can lead to inbreeding depression and reduced population adaptability. In this study, we estimated contemporary N_e using genetic estimators (LDNE, ONeSAMP, MLNE and CoNe) as well as a demographic estimator in a natural insular house sparrow metapopulation. We investigated whether population characteristics (population size, sex ratio, immigration rate, variance in population size and population growth rate) explained variation within and among populations in the ratio of effective to census population size (N_e/N_c). In general, N_e/N_c ratios increased with immigration rates. Genetic N_e was much larger than demographic N_e, probably due to a greater effect of immigration on genetic than demographic processes in local populations. Moreover, although estimates of genetic N_e seemed to track N_c quite well, the genetic N_e‐estimates were often larger than N_c within populations. Estimates of genetic N_e for the metapopulation were however within the expected range (<N_c). Our results suggest that in fragmented populations, even low levels of gene flow may have important consequences for the interpretation of genetic estimates of N_e. Consequently, further studies are needed to understand how N_e estimated in local populations or the total metapopulation relates to actual rates of genetic drift and inbreeding.     

Inbreeding and extinction: Effects of rate of inbreeding

Deleterious alleles may be removed (purged) bynatural selection in populations undergoinginbreeding. However, there is controversyregarding the effectiveness of selection inreducing the risk of extinction due toinbreeding, especially in relation to the rateof inbreeding. We evaluated the effect of therate of inbreeding on reducing extinction risk,in populations of Drosophila melanogastermaintained using full-sib mating (160replicates), or at effective population sizes(N _e) of 10 (80) or 20 (80).Extinction rates in the populations maintainedusing full-sib mating occurred at lower levelsof inbreeding than in the larger populations,whereas the two larger populations did notdiffer significantly from each other.Inbreeding coefficients at 50% extinction were0.62, 0.79 and 0.77 for the full-sib (N _e = 2.6), N _e = 10 and N _e = 20 treatments, respectively. Populations of N _e = 20 that remained extant after 60 generations, showed inbreeding depression, with the mean fitness of these populations being only 45% of the outbredcontrols. There was considerable variationamong the 31 inbred populations in fitness, butnone of the N _e = 20 populations hadfitness that was higher than the outbredcontrol. We conclude that purging may slow therate of extinction slightly, but it cannot berelied on to eliminate the deleterious effectsof inbreeding.     

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.