Genomic signatures and correlates of widespread population declines in salmon.

Global losses of biodiversity are occurring at an unprecedented rate, but causes are often unidentified. Genomic data provide an opportunity to isolate drivers of change and even predict future vulnerabilities. Atlantic salmon (Salmo salar) populations have declined range-wide, but factors responsible are poorly understood. Here, we reconstruct changes in effective population size (Ne) in recent decades for 172 range-wide populations using a linkage-based method. Across the North Atlantic, Ne has significantly declined in >60% of populations and declines are consistently temperature-associated. We identify significant polygenic associations with decline, involving genomic regions related to metabolic, developmental, and physiological processes. These regions exhibit changes in presumably adaptive diversity in declining populations consistent with contemporary shifts in body size and phenology. Genomic signatures of widespread population decline and associated risk scores allow direct and potentially predictive links between population fitness and genotype, highlighting the power of genomic resources to assess population vulnerability.

Tiny estimates of the Ne /N ratio in marine fishes: Are they real?

Theory and empirical estimates agree that the ratio of effective size (Ne ) to census size (N) falls roughly in the range 0·1-0·5 for most populations. In a number of marine species, however, genetic estimates of contemporary Ne /N are as much as 5-6 orders of magnitude lower. Although some mechanisms that could produce such tiny Ne /N ratios have been proposed, the subject remains controversial. This issue is important to resolve: if Ne /N can be 10-3 or smaller, marine fish populations that are quite large could be at genetic risk. Based on a recently-improved understanding of factors that influence Ne and Ne /N in species with overlapping generations, this paper evaluates conditions necessary to produce tiny Ne /N ratios in actual populations. These analyses show that although increased longevity, fecundity and variance in reproductive success that increase with age, and increased egg quality with age [the big old fat fecund female fish (BOFFFF) hypothesis] all reduce Ne /N, extreme scenarios are required to reduce Ne /N below about 0·01. Therefore, tiny Ne /N ratios require some version of Hedgecock's 'sweepstakes' hypothesis, whereby only a few families reproduce successfully. Simulations using common genetically-based estimators show that, when true Ne is very large (≥106 ), a substantial fraction of point estimates of Ne /N can be 10-3 or smaller. These results mean that tiny, genetically-based point estimates of Ne /N in large marine populations are expected to be quite common, even when the true Ne /N ratio is 'normal' (∼0·1 or higher). Very large samples of individuals can reduce, but not eliminate, this problem. The simulation results also emphasize the importance of considering deviations from model assumptions (e.g. non-random sampling; weak selection or migration) that may be relatively small (and hence can generally be ignored when the signal is strong) but can lead to substantial biases when the drift signal is weak, as is likely for large marine populations. Empirical studies of this topic need to be able to distinguish between episodes of sweepstakes reproductive success that are ephemeral and lead to chaotic genetic patchiness, and those that are consistent enough across space and time to produce persistent evolutionary consequences.

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

Contemporary effective population size (Ne) 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 Ne 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 Ne estimates to be downwardly biased. Here, we present results from coalescent and forward simulations designed to evaluate the bias of LD-based Ne estimates ([Ncirc ]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 in [Ncirc ]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 of [Ncirc ]e is much lower than expected based on the assumption that each pair of loci provides completely independent information.

Sex change and effective population size: implications for population genetic studies in marine fish.

Large variance in reproductive success is the primary factor that reduces effective population size (Ne) in natural populations. In sequentially hermaphroditic (sex-changing) fish, the sex ratio is typically skewed and biased towards the 'first' sex, while reproductive success increases considerably after sex change. Therefore, sex-changing fish populations are theoretically expected to have lower Ne than gonochorists (separate sexes), assuming all other parameters are essentially equal. In this study, we estimate Ne from genetic data collected from two ecologically similar species living along the eastern coast of South Africa: one gonochoristic, the 'santer' sea bream Cheimerius nufar, and one protogynous (female-first) sex changer, the 'slinger' sea bream Chrysoblephus puniceus. For both species, no evidence of genetic structuring, nor significant variation in genetic diversity, was found in the study area. Estimates of contemporary Ne were significantly lower in the protogynous species, but the same pattern was not apparent over historical timescales. Overall, our results show that sequential hermaphroditism may affect Ne differently over varying time frames, and that demographic signatures inferred from genetic markers with different inheritance modes also need to be interpreted cautiously, in relation to sex-changing life histories.

Life-history traits and effective population size in species with overlapping generations revisited: the importance of adult mortality.

The relationship between life-history traits and the key eco-evolutionary parameters effective population size (Ne) and Ne/N is revisited for iteroparous species with overlapping generations, with a focus on the annual rate of adult mortality (d). Analytical methods based on populations with arbitrarily long adult lifespans are used to evaluate the influence of d on Ne, Ne/N and the factors that determine these parameters: adult abundance (N), generation length (T), age at maturity (α), the ratio of variance to mean reproductive success in one season by individuals of the same age (φ) and lifetime variance in reproductive success of individuals in a cohort (Vk•). Although the resulting estimators of N, T and Vk• are upwardly biased for species with short adult lifespans, the estimate of Ne/N is largely unbiased because biases in T are compensated for by biases in Vk• and N. For the first time, the contrasting effects of T and Vk• on Ne and Ne/N are jointly considered with respect to d and φ. A simple function of d and α based on the assumption of constant vital rates is shown to be a robust predictor (R(2)=0.78) of Ne/N in an empirical data set of life tables for 63 animal and plant species with diverse life histories. Results presented here should provide important context for interpreting the surge of genetically based estimates of Ne that has been fueled by the genomics revolution.

Combining demographic and genetic factors to assess population vulnerability in stream species.

Accelerating climate change and other cumulative stressors create an urgent need to understand the influence of environmental variation and landscape features on the connectivity and vulnerability of freshwater species. Here, we introduce a novel modeling framework for aquatic systems that integrates spatially explicit, individual-based, demographic and genetic (demogenetic) assessments with environmental variables. To show its potential utility, we simulated a hypothetical network of 19 migratory riverine populations (e.g., salmonids) using a riverscape connectivity and demogenetic model (CDFISH). We assessed how stream resistance to movement (a function of water temperature, fluvial distance, and physical barriers) might influence demogenetic connectivity, and hence, population vulnerability. We present demographic metrics (abundance, immigration, and change in abundance) and genetic metrics (diversity, differentiation, and change in differentiation), and combine them into a single vulnerability index for identifying populations at risk of extirpation. We considered four realistic scenarios that illustrate the relative sensitivity of these metrics for early detection of reduced connectivity: (1) maximum resistance due to high water temperatures throughout the network, (2) minimum resistance due to low water temperatures throughout the network, (3) increased resistance at a tributary junction caused by a partial barrier, and (4) complete isolation of a tributary, leaving resident individuals only. We then applied this demogenetic framework using empirical data for a bull trout (Salvelinus confluentus) metapopulation in the upper Flathead River system, Canada and USA, to assess how current and predicted future stream warming may influence population vulnerability. Results suggest that warmer water temperatures and associated barriers to movement (e.g., low flows, dewatering) are predicted to fragment suitable habitat for migratory salmonids, resulting in the loss of genetic diversity and reduced numbers in certain vulnerable populations. This demogenetic simulation framework, which is illustrated in a web-based interactive mapping prototype, should be useful for evaluating population vulnerability in a wide variety of dendritic and fragmented riverscapes, helping to guide conservation and management efforts for freshwater species.

NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (Ne ) from genetic data.

NeEstimator v2 is a completely revised and updated implementation of software that produces estimates of contemporary effective population size, using several different methods and a single input file. NeEstimator v2 includes three single-sample estimators (updated versions of the linkage disequilibrium and heterozygote-excess methods, and a new method based on molecular coancestry), as well as the two-sample (moment-based temporal) method. New features include the following: (i) an improved method for accounting for missing data; (ii) options for screening out rare alleles; (iii) confidence intervals for all methods; (iv) the ability to analyse data sets with large numbers of genetic markers (10 000 or more); (v) options for batch processing large numbers of different data sets, which will facilitate cross-method comparisons using simulated data; and (vi) correction for temporal estimates when individuals sampled are not removed from the population (Plan I sampling). The user is given considerable control over input data and composition, and format of output files. The freely available software has a new JAVA interface and runs under MacOS, Linux and Windows.

Secondary contact and changes in coastal habitat availability influence the nonequilibrium population structure of a salmonid (Oncorhynchus keta).

Numerous empirical studies have reported lack of migration-drift equilibrium in wild populations. Determining the causes of nonequilibrium population structure is challenging because different evolutionary processes acting at a variety of spatiotemporal scales can produce similar patterns. Studies of contemporary populations in northern latitudes suggest that nonequilibrium population structure is probably caused by recent colonization of the region after the last Pleistocene ice age ended ~13,000 years ago. The chum salmon's (Oncorhynchus keta) range was fragmented by dramatic environmental changes during the Pleistocene. We investigated the population structure of chum salmon on the North Alaska Peninsula (NAP) and, using both empirical data and simulations, evaluated the effects of colonization timing and founder population heterogeneity on patterns of genetic differentiation. We screened 161 single nucleotide polymorphisms and found evidence of nonequilibrium population structure when the slope of the isolation-by-distance relationship was examined at incremental spatial scales. In addition, simulations suggested that this pattern closely matched models of recent colonization of the NAP by secondary contact. Our results agree with geological and archaeological data indicating that the NAP was a dynamic landscape that may have been more recently colonized than during the last deglaciation because of dramatic changes in coastal hydrology over the last several thousand years.

Estimation of effective population size in continuously distributed populations: there goes the neighborhood.

Use of genetic methods to estimate effective population size (Ne) is rapidly increasing, but all approaches make simplifying assumptions unlikely to be met in real populations. In particular, all assume a single, unstructured population, and none has been evaluated for use with continuously distributed species. We simulated continuous populations with local mating structure, as envisioned by Wright's concept of neighborhood size (NS), and evaluated performance of a single-sample estimator based on linkage disequilibrium (LD), which provides an estimate of the effective number of parents that produced the sample (Nb). Results illustrate the interacting effects of two phenomena, drift and mixture, that contribute to LD. Samples from areas equal to or smaller than a breeding window produced estimates close to the NS. As the sampling window increased in size to encompass multiple genetic neighborhoods, mixture LD from a two-locus Wahlund effect overwhelmed the reduction in drift LD from incorporating offspring from more parents. As a consequence, never approached the global Ne, even when the geographic scale of sampling was large. Results indicate that caution is needed in applying standard methods for estimating effective size to continuously distributed populations.

Accounting for missing data in the estimation of contemporary genetic effective population size (N(e) ).

Theoretical models are often applied to population genetic data sets without fully considering the effect of missing data. Researchers can deal with missing data by removing individuals that have failed to yield genotypes and/or by removing loci that have failed to yield allelic determinations, but despite their best efforts, most data sets still contain some missing data. As a consequence, realized sample size differs among loci, and this poses a problem for unbiased methods that must explicitly account for random sampling error. One commonly used solution for the calculation of contemporary effective population size (N(e) ) is to calculate the effective sample size as an unweighted mean or harmonic mean across loci. This is not ideal because it fails to account for the fact that loci with different numbers of alleles have different information content. Here we consider this problem for genetic estimators of contemporary effective population size (N(e) ). To evaluate bias and precision of several statistical approaches for dealing with missing data, we simulated populations with known N(e) and various degrees of missing data. Across all scenarios, one method of correcting for missing data (fixed-inverse variance-weighted harmonic mean) consistently performed the best for both single-sample and two-sample (temporal) methods of estimating N(e) and outperformed some methods currently in widespread use. The approach adopted here may be a starting point to adjust other population genetics methods that include per-locus sample size components.

Effective size of a wild salmonid population is greatly reduced by hatchery supplementation.

Many declining and commercially important populations are supplemented with captive-born individuals that are intentionally released into the wild. These supplementation programs often create large numbers of offspring from relatively few breeding adults, which can have substantial population-level effects. We examined the genetic effects of supplementation on a wild population of steelhead (Oncorhynchus mykiss) from the Hood River, Oregon, by matching 12 run-years of hatchery steelhead back to their broodstock parents. We show that the effective number of breeders producing the hatchery fish (broodstock parents; N(b)) was quite small (harmonic mean N(b)=25 fish per brood-year vs 373 for wild fish), and was exacerbated by a high variance in broodstock reproductive success among individuals within years. The low N(b) caused hatchery fish to have decreased allelic richness, increased average relatedness, more loci in linkage disequilibrium and substantial levels of genetic drift in comparison with their wild-born counterparts. We also documented a substantial Ryman-Laikre effect whereby the additional hatchery fish doubled the total number of adult fish on the spawning grounds each year, but cut the effective population size of the total population (wild and hatchery fish combined) by nearly two-thirds. We further demonstrate that the Ryman-Laikre effect is most severe in this population when (1) >10% of fish allowed onto spawning grounds are from hatcheries and (2) the hatchery fish have high reproductive success in the wild. These results emphasize the trade-offs that arise when supplementation programs attempt to balance disparate goals (increasing production while maintaining genetic diversity and fitness).

A generalized approach for estimating effective population size from temporal changes in allele frequency.

The temporal method for estimating effective population size (Ne) from the standardized variance in allele frequency change (F) is presented in a generalized form. Whereas previous treatments of this method have adopted rather limiting assumptions, the present analysis shows that the temporal method is generally applicable to a wide variety of organisms. Use of a revised model of gene sampling permits a more generalized interpretation of Ne than that used by some other authors studying this method. It is shown that two sampling plans (individuals for genetic analysis taken before or after reproduction) whose differences have been stressed by previous authors can be treated in a uniform way. Computer simulations using a wide variety of initial conditions show that different formulas for computing F have much less effect on Ne than do sample size (S), number of generations between samples (t), or the number of loci studied (L). Simulation results also indicate that (1) bias of F is small unless alleles with very low frequency are used; (2) precision is typically increased by about the same amount with a doubling of S, t, or L; (3) confidence intervals for Ne computed using a chi 2 approximation are accurate and unbiased under most conditions; (4) the temporal method is best suited for use with organisms having high juvenile mortality and, perhaps, a limited effective population size.

Estimation of allele frequencies at isoloci.

In some polyploid animals and plants, pairs of duplicated loci occur that share alleles encoding proteins with identical electrophoretic mobilities. Except in cases where these "isoloci" are known to be inherited tetrasomically, individual genotypes cannot be determined unambiguously, and there is no direct way to assign observed variation to a particular locus of the pair. For a pair of diallelic isoloci, nine genotypes are possible but only five phenotypes can be identified, corresponding to individuals with 0-4 doses of the variant allele. A maximum likelihood (ML) approach is used here to identify the set of allele frequencies (p, q) at the individual gene loci with the highest probability of producing the observed phenotypic distribution. A likelihood ratio test is used to generate the asymmetrical confidence intervals around ML estimates. Simulations indicate that the standard error of p is typically about twice the binomial sampling error associated with single locus allele frequency estimates. ML estimates can be used in standard indices of genetic diversity and differentiation and in goodness-of-fit tests of genetic hypotheses. The noncentral chi 2 distribution is used to evaluate the power of a test of apparent heterozygote deficiency that results from attributing all variation to one locus when both loci are polymorphic.