David A. Tallmon

THE POWER AND PROMISE OF POPULATION GENOMICS: FROM GENOTYPING TO GENOME TYPING

Population genomics has the potential to improve studies of evolutionary genetics, molecular ecology and conservation biology, by facilitating the identification of adaptive molecular variation and by improving the estimation of important parameters such as population size, migration rates and phylogenetic relationships. There has been much excitement in the recent literature about the identification of adaptive molecular variation using the population-genomic approach. However, the most useful contribution of the genomics model to population genetics will be improving inferences about population demography and evolutionary history.

ONeSAMP: a program to estimate effective population size using approximate Bayesian computation

The estimation of effective population size from one sample of genotypes has been problematic because most estimators have been proven imprecise or biased. We developed a web‐based program, onesamp that uses approximate Bayesian computation to estimate effective population size from a sample of microsatellite genotypes. onesamp requires an input file of sampled individuals’ microsatellite genotypes along with information about several sampling and biological parameters. onesamp provides an estimate of effective population size, along with 95% credible limits. We illustrate the use of onesamp with an example data set from a re‐introduced population of ibex Capra ibex.

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

Population census size (NC) and effective population sizes (Ne) are two crucial parameters that influence population viability, wildlife management decisions, and conservation planning. Genetic estimators of both NC and Ne are increasingly widely used because molecular markers are increasingly available, statistical methods are improving rapidly, and genetic estimators complement or improve upon traditional demographic estimators. We review the kinds and applications of estimators of both NC and Ne, and the often undervalued and misunderstood ratio of effective-to-census size (Ne/NC). We focus on recently improved and well evaluated methods that are most likely to facilitate conservation. Finally, we outline areas of future research to improve Ne and NC estimation in wild populations.

COMPUTER PROGRAMS: onesamp: a program to estimate effective population size using approximate Bayesian computation

The estimation of effective population size from one sample of genotypes has been problematic because most estimators have been proven imprecise or biased. We developed a web‐based program, onesamp that uses approximate Bayesian computation to estimate effective population size from a sample of microsatellite genotypes. onesamp requires an input file of sampled individuals’ microsatellite genotypes along with information about several sampling and biological parameters. onesamp provides an estimate of effective population size, along with 95% credible limits. We illustrate the use of onesamp with an example data set from a re‐introduced population of ibex Capra ibex.

Genetic rescue to the rescue

Genetic rescue can increase the fitness of small, imperiled populations via immigration. A suite of studies from the past decade highlights the value of genetic rescue in increasing population fitness. Nonetheless, genetic rescue has not been widely applied to conserve many of the threatened populations that it could benefit. In this review, we highlight recent studies of genetic rescue and place it in the larger context of theoretical and empirical developments in evolutionary and conservation biology. We also propose directions to help shape future research on genetic rescue. Genetic rescue is a tool that can stem biodiversity loss more than has been appreciated, provides population resilience, and will become increasingly useful if integrated with molecular advances in population genomics.

Estimating effective population size from linkage disequilibrium: severe bias in small samples

Effective population size (Ne) is a central concept in evolutionary biology and conservation genetics. It predicts rates of loss of neutral genetic variation, fixation of deleterious and favourable alleles, and the increase of inbreeding experienced by a population. A method exists for the estimation of Ne from the observed linkage disequilibrium between unlinked loci in a population sample. While an increasing number of studies have applied this method in natural and managed populations, its reliability has not yet been evaluated. We developed a computer program to calculate this estimator of Ne using the most widely used linkage disequilibrium algorithm and used simulations to show that this estimator is strongly biased when the sample size is small (<‰100) and below the true Ne. This is probably due to the linkage disequilibrium generated by the sampling process itself and the inadequate correction for this phenomenon in the method. Results suggest that Ne estimates derived using this method should be regarded with caution in many cases. To improve the method’s reliability and usefulness we propose a way to determine whether a given sample size exceeds the population Ne and can therefore be used for the computation of an unbiased estimate.

Neglect of Genetic Diversity in Implementation of the Convention on Biological Diversity

Genetic diversity is the foundation for all biological diversity; the persistence and evolutionary potential of species depend on it. World leaders have agreed on the conservation of genetic diversity as an explicit goal of the Convention on Biological Diversity (CBD). Nevertheless, actions to protect genetic diversity are largely lacking. With only months left to the 2010-biodiversity target, when the 191 parties to the CBD have agreed on achieving a significant reduction of the rate of biodiversity loss, gene-level diversity is still not being monitored, and indicators and thresholds that can be used to devise strategies to conserve this important component of biodiversity are missing. Immediate action is needed to ensure that genetic diversity is not neglected in conservation targets beyond 2010.

Simple life-history traits explain key effective population size ratios across diverse taxa.

Effective population size (Ne) controls both the rate of random genetic drift and the effectiveness of selection and migration, but it is difficult to estimate in nature. In particular, for species with overlapping generations, it is easier to estimate the effective number of breeders in one reproductive cycle (Nb) than Ne per generation. We empirically evaluated the relationship between life history and ratios of Ne, Nb and adult census size (N) using a recently developed model (agene) and published vital rates for 63 iteroparous animals and plants. Nb/Ne varied a surprising sixfold across species and, contrary to expectations, Nb was larger than Ne in over half the species. Up to two-thirds of the variance in Nb/Ne and up to half the variance in Ne/N was explained by just two life-history traits (age at maturity and adult lifespan) that have long interested both ecologists and evolutionary biologists. These results provide novel insights into, and demonstrate a close general linkage between, demographic and evolutionary processes across diverse taxa. For the first time, our results also make it possible to interpret rapidly accumulating estimates of Nb in the context of the rich body of evolutionary theory based on Ne per generation.

Genetic change for earlier migration timing in a pink salmon population

To predict how climate change will influence populations, it is necessary to understand the mechanisms, particularly microevolution and phenotypic plasticity, that allow populations to persist in novel environmental conditions. Although evidence for climate-induced phenotypic change in populations is widespread, evidence documenting that these phenotypic changes are due to microevolution is exceedingly rare. In this study, we use 32 years of genetic data (17 complete generations) to determine whether there has been a genetic change towards earlier migration timing in a population of pink salmon that shows phenotypic change; average migration time occurs nearly two weeks earlier than it did 40 years ago. Experimental genetic data support the hypothesis that there has been directional selection for earlier migration timing, resulting in a substantial decrease in the late-migrating phenotype (from more than 30% to less than 10% of the total abundance). From 1983 to 2011, there was a significant decrease—over threefold—in the frequency of a genetic marker for late-migration timing, but there were minimal changes in allele frequencies at other neutral loci. These results demonstrate that there has been rapid microevolution for earlier migration timing in this population. Circadian rhythm genes, however, did not show any evidence for selective changes from 1993 to 2009.

When are genetic methods useful for estimating contemporary abundance and detecting population trends

The utility of microsatellite markers for inferring population size and trend has not been rigorously examined, even though these markers are commonly used to monitor the demography of natural populations. We assessed the ability of a linkage disequilibrium estimator of effective population size (Ne) and a simple capture‐recapture estimator of abundance (N) to quantify the size and trend of stable or declining populations (true N = 100–10,000), using simulated Wright–Fisher populations. Neither method accurately or precisely estimated abundance at sample sizes of S = 30 individuals, regardless of true N. However, if larger samples of S = 60 or 120 individuals were collected, these methods provided useful insights into abundance and trends for populations of N = 100–500. At small population sizes (N = 100 or 250), precision of the Ne estimates was improved slightly more by a doubling of loci sampled than by a doubling of individuals sampled. In general, monitoring Ne proved a more robust means of identifying stable and declining populations than monitoring N over most of the parameter space we explored, and performance of the Ne estimator is further enhanced if the Ne/N ratio is low. However, at the largest population size (N = 10,000), N estimation outperformed Ne. Both methods generally required ≥ 5 generations to pass between sampling events to correctly identify population trend.