Estimation of census and effective population sizes: the increasing usefulness of DNA-based approaches

Luikart, Gordon; Ryman, Nils; Tallmon, David A.; Schwartz, Michael K.; Allendorf, Fred W.

doi:10.1007/s10592-010-0050-7

Cited by 502 publications

(717 citation statements)

References 120 publications

(134 reference statements)

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“…As a result, measures of LD between independently-segregating loci can be used to provide an estimate of N e (Sved, 1971;Hill, 1981;Waples, 1991). Over the past decades, many studies have leveraged data sets consisting of a few dozen loci for genetic estimates of N e (Luikart et al, 2010). While these studies continue to be useful, especially for long-running…”

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confidence: 99%

Estimating contemporary effective population size in non-model species using linkage disequilibrium across thousands of loci

2016

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Contemporary effective population size (N e ) can be estimated using linkage disequilibrium (LD) observed across pairs of loci presumed to be selectively neutral and unlinked. This method has been commonly applied to data sets containing 10-100 loci to inform conservation and study population demography. Performance of these N e estimates could be improved by incorporating data from thousands of loci. However, these thousands of loci exist on a limited number of chromosomes, ensuring that some fraction will be physically linked. Linked loci have elevated LD due to limited recombination, which if not accounted for can cause N e estimates to be downwardly biased. Here, we present results from coalescent and forward simulations designed to evaluate the bias of LD-based N e estimates (N e ). Contrary to common perceptions, increasing the number of loci does not increase the magnitude of linkage. Although we show it is possible to identify some pairs of loci that produce unusually large r 2 values, simply removing large r 2 values is not a reliable way to eliminate bias. Fortunately, the magnitude of bias inN e is strongly and negatively correlated with the process of recombination, including the number of chromosomes and their length, and this relationship provides a general way to adjust for bias. Additionally, we show that with thousands of loci, precision ofN e is much lower than expected based on the assumption that each pair of loci provides completely independent information. Heredity (Wright, 1931), which determines the rate of evolutionary change due to genetic drift and informs the equilibrium level of genetic variation and the effectiveness of selection. N e is often much lower than census size (Frankham, 1995), demonstrating that simply counting individuals is insufficient to predict rates of evolutionary change. In addition to the number of mating individuals, N e is affected by sex ratio, variation in reproductive success, age structure, migration and other demographic factors. It is an extremely relevant metric in conservation biology, with low N e leading to inbreeding and reduced genetic diversity (Ellstrand and Elam, 1993). See Charlesworth (2009) for a primer on N e , and Wang (2005) for a review of estimation methods.Populations with smaller N e undergo more genetic drift than larger populations. This genetic drift randomly generates associations between alleles at different loci, known as linkage (or gametic) disequilibrium (LD) at a rate inversely proportional to N e . As a result, measures of LD between independently-segregating loci can be used to provide an estimate of N e (Sved, 1971;Hill, 1981;Waples, 1991). Over the past decades, many studies have leveraged data sets consisting of a few dozen loci for genetic estimates of N e (Luikart et al., 2010). While these studies continue to be useful, especially for long-running

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confidence: 99%

Estimating contemporary effective population size in non-model species using linkage disequilibrium across thousands of loci

2016

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“…Traditionally, animal populations have been assessed by means of direct census counts for conservation and management purposes (Luikart et al, 2010). However, an influential contribution of evolutionary theory to conservation biology has been the development of a framework for predicting the fate of small populations (Palstra and Ruzzante, 2008).…”

Section: Introductionmentioning

confidence: 99%

“…Although ascertaining N e is crucial to conservation and management, it is still rather difficult to obtain reliable estimates in real populations because of constraints on collecting enough demographic data to directly measure N e (Waples, 2005;Luikart et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

“…A variety of different approaches are now available to estimate N e from genetic marker data (reviewed by Leberg, 2005;Wang, 2005;Palstra and Ruzzante, 2008;Luikart et al, 2010). These can be broadly classified into single-sample and temporal approaches.…”

Section: Introductionmentioning

confidence: 99%

“…Temporal approaches are often considered to be the most accurate, assuming that samples can be gathered sufficiently far apart in time (Leberg, 2005;Luikart et al, 2010). However, they require at least two non-overlapping generations to be sampled, and this is often impossible for species with long generation times such as many large vertebrates (Luikart et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

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Long-term effective population size dynamics of an intensively monitored vertebrate population

et al. 2016

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Long-term genetic data from intensively monitored natural populations are important for understanding how effective population sizes (N e ) can vary over time. We therefore genotyped 1622 common buzzard (Buteo buteo) chicks sampled over 12 consecutive years (2002-2013 inclusive) at 15 microsatellite loci. This data set allowed us to both compare single-sample with temporal approaches and explore temporal patterns in the effective number of parents that produced each cohort in relation to the observed population dynamics. We found reasonable consistency between linkage disequilibrium-based single-sample and temporal estimators, particularly during the latter half of the study, but no clear relationship between annual N e estimates (N e ) and census sizes. We also documented a 14-fold increase inN e between 2008 and 2011, a period during which the census size doubled, probably reflecting a combination of higher adult survival and immigration from further afield. Our study thus reveals appreciable temporal heterogeneity in the effective population size of a natural vertebrate population, confirms the need for long-term studies and cautions against drawing conclusions from a single sample.

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Estimating current effective sizes of large populations from a single sample of genomic marker data: A comparison of estimators by simulations

Wang

2023

Population Ecology

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Genome‐wide single nucleotide polymorphisms (SNPs) data are increasingly used in estimating the current effective population sizes (Ne) for informing the conservation of endangered species and guiding the management of exploited species. Previous assessments of sibship frequency (SF) and linkage disequilibrium (LD) estimators of Ne focused on small populations where genetic drift is strong and thus Ne is easy to estimate. Genomic single nucleotide polymorphism (SNP) data provide ample information and hold the potential for application of these estimators to large populations where genetic drift is rather weak and thus Ne is difficult to estimate. In this study, I simulated very large populations and sampled a widely variable number of individuals (genotyped at 10,000 SNPs) for estimating Ne by both SF and LD methods. I also considered the more realistic situation where a population experiences a bottleneck, and where marker data suffer from genotyping errors. The simulations show that both SF and LD methods can yield accurate Ne estimates of very large populations when sampled individuals are sufficiently numerous. When n is much smaller than Ne, however, Ne estimates are in a bimodal distribution with a substantial proportion of the estimates being infinitely large. For a population with a bottleneck, LD estimator overestimates and underestimates the Ne of the parental population from samples taken at and after the bottleneck, respectively. LD estimator also overestimates Ne substantially when applied to data suffering from allelic dropouts and false alleles. In contrast, SF estimator is unbiased and accurate when populations are changing in size or markers suffer from genotyping errors.

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Estimation of census and effective population sizes: the increasing usefulness of DNA-based approaches

Cited by 502 publications

References 120 publications

Estimating contemporary effective population size in non-model species using linkage disequilibrium across thousands of loci

Estimating contemporary effective population size in non-model species using linkage disequilibrium across thousands of loci

Long-term effective population size dynamics of an intensively monitored vertebrate population

Estimating current effective sizes of large populations from a single sample of genomic marker data: A comparison of estimators by simulations

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