In defence of model‐based inference in phylogeography

Recent papers have promoted the view that model‐based methods in general, and those based on Approximate Bayesian Computation (ABC) in particular, are flawed in a number of ways, and are therefore inappropriate for the analysis of phylogeographic data. These papers further argue that Nested Clade Phylogeographic Analysis (NCPA) offers the best approach in statistical phylogeography. In order to remove the confusion and misconceptions introduced by these papers, we justify and explain the reasoning behind model‐based inference. We argue that ABC is a statistically valid approach, alongside other computational statistical techniques that have been successfully used to infer parameters and compare models in population genetics. We also examine the NCPA method and highlight numerous deficiencies, either when used with single or multiple loci. We further show that the ages of clades are carelessly used to infer ages of demographic events, that these ages are estimated under a simple model of panmixia and population stationarity but are then used under different and unspecified models to test hypotheses, a usage the invalidates these testing procedures. We conclude by encouraging researchers to study and use model‐based inference in population genetics.     

Genetic diversity and recombination in natural populations of the nematode‐trapping fungus Arthrobotrys oligospora from China

Nematophagous fungi can trap and capture nematodes and other small invertebrates. This unique ability has made them ideal organisms from which to develop biological control agents against plant‐ and animal‐parasitic nematodes. However, effective application of biocontrol agents in the field requires a comprehensive understanding about the ecology and population genetics of the nematophagous fungi in natural environments. Here, we genotyped 228 strains of the nematode‐trapping fungus Arthrobotrys oligospora using 12 single nucleotide polymorphic markers located on eight random DNA fragments. The strains were from different ecological niches and geographical regions from China. Our analyses identified that ecological niche separations contributed significantly, whereas geographic separation contributed relatively little to the overall genetic variation in our samples of A. oligospora. Interestingly, populations from stressful environments seemed to be more variable and showed more evidence for recombination than those from benign environments at the same geographic areas. We discussed the implications of our results to the conservation and biocontrol application of A. oligospora in agriculture and forestry.     

Inferring past demographic changes from contemporary genetic data: A simulation‐based evaluation of the ABC methods implemented in diyabc

Inferring the demographic history of species and their populations is crucial to understand their contemporary distribution, abundance and adaptations. The high computational overhead of likelihood‐based inference approaches severely restricts their applicability to large data sets or complex models. In response to these restrictions, approximate Bayesian computation (ABC) methods have been developed to infer the demographic past of populations and species. Here, we present the results of an evaluation of the ABC‐based approach implemented in the popular software package diyabc using simulated data sets (mitochondrial DNA sequences, microsatellite genotypes and single nucleotide polymorphisms). We simulated population genetic data under five different simple, single‐population models to assess the model recovery rates as well as the bias and error of the parameter estimates. The ability of diyabc to recover the correct model was relatively low (0.49): 0.6 for the simplest models and 0.3 for the more complex models. The recovery rate improved significantly when reducing the number of candidate models from five to three (from 0.57 to 0.71). Among the parameters of interest, the effective population size was estimated at a higher accuracy compared to the timing of events. Increased amounts of genetic data did not significantly improve the accuracy of the parameter estimates. Some gains in accuracy and decreases in error were observed for scaled parameters (e.g., N_eμ) compared to unscaled parameters (e.g., N_e and μ). We concluded that diyabc ‐based assessments are not suited to capture a detailed demographic history, but might be efficient at capturing simple, major demographic changes.     

A test of the central–marginal hypothesis using population genetics and ecological niche modelling in an endemic salamander (Ambystoma barbouri)

The central–marginal hypothesis (CMH) predicts that population size, genetic diversity and genetic connectivity are highest at the core and decrease near the edges of species' geographic distributions. We provide a test of the CMH using three replicated core‐to‐edge transects that encompass nearly the entire geographic range of the endemic streamside salamander (Ambystoma barbouri). We confirmed that the mapped core of the distribution was the most suitable habitat using ecological niche modelling (ENM) and via genetic estimates of effective population sizes. As predicted by the CMH, we found statistical support for decreased genetic diversity, effective population size and genetic connectivity from core to edge in western and northern transects, yet not along a southern transect. Based on our niche model, habitat suitability is lower towards the southern range edge, presumably leading to conflicting core‐to‐edge genetic patterns. These results suggest that multiple processes may influence a species' distribution based on the heterogeneity of habitat across a species' range and that replicated sampling may be needed to accurately test the CMH. Our work also emphasizes the importance of identifying the geographic range core with methods other than using the Euclidean centre on a map, which may help to explain discrepancies among other empirical tests of the CMH. Assessing core‐to‐edge population genetic patterns across an entire species' range accompanied with ENM can inform our general understanding of the mechanisms leading to species' geographic range limits.     

Divergence with gene flow in a population of thermophilic bacteria: a potential role for spatially varying selection

A fundamental goal of evolutionary biology is to understand how ecological diversity arises and is maintained in natural populations. We have investigated the contributions of gene flow and divergent selection to the distribution of genetic variation in an ecologically differentiated population of a thermophilic cyanobacterium (Mastigocladus laminosus) found along the temperature gradient of a nitrogen‐limited stream in Yellowstone National Park. For most loci sampled, gene flow appears to be sufficient to prevent substantial genetic divergence. However, one locus (rfbC) exhibited a comparatively low migration rate as well as other signatures expected for a gene experiencing spatially varying selection, including an excess of common variants, an elevated level of polymorphism and extreme genetic differentiation along the gradient. rfbC is part of an expression island involved in the production of the polysaccharide component of the protective envelope of the heterocyst, the specialized nitrogen‐fixing cell of these bacteria. SNP genotyping in the vicinity of rfbC revealed a ~5‐kbp region including a gene content polymorphism that is tightly associated with environmental temperature and therefore likely contains the target of selection. Two genes have been deleted both in the predominant haplotype found in the downstream region of White Creek and in strains from other Yellowstone populations of M. laminosus, which may result in the production of heterocysts with different envelope properties. This study implicates spatially varying selection in the maintenance of variation related to thermal performance at White Creek despite on‐going or recent gene flow.     

Demographic inferences using short‐read genomic data in an approximate Bayesian computation framework: in silico evaluation of power,biases and proof of concept in Atlantic walrus

Approximate Bayesian computation (ABC) is a powerful tool for model‐based inference of demographic histories from large genetic data sets. For most organisms, its implementation has been hampered by the lack of sufficient genetic data. Genotyping‐by‐sequencing (GBS) provides cheap genome‐scale data to fill this gap, but its potential has not fully been exploited. Here, we explored power, precision and biases of a coalescent‐based ABC approach where GBS data were modelled with either a population mutation parameter (θ) or a fixed site (FS) approach, allowing single or several segregating sites per locus. With simulated data ranging from 500 to 50 000 loci, a variety of demographic models could be reliably inferred across a range of timescales and migration scenarios. Posterior estimates were informative with 1000 loci for migration and split time in simple population divergence models. In more complex models, posterior distributions were wide and almost reverted to the uninformative prior even with 50 000 loci. ABC parameter estimates, however, were generally more accurate than an alternative composite‐likelihood method. Bottleneck scenarios proved particularly difficult, and only recent bottlenecks without recovery could be reliably detected and dated. Notably, minor‐allele‐frequency filters – usual practice for GBS data – negatively affected nearly all estimates. With this in mind, we used a combination of FS and θ approaches on empirical GBS data generated from the Atlantic walrus (Odobenus rosmarus rosmarus), collectively providing support for a population split before the last glacial maximum followed by asymmetrical migration and a high Arctic bottleneck. Overall, this study evaluates the potential and limitations of GBS data in an ABC‐coalescence framework and proposes a best‐practice approach.     

Genetic diversity of small populations: Not always “doom and gloom”?

Is a key theory of evolutionary and conservation biology—that loss of genetic diversity can be predicted from population size—on shaky ground? In the face of increasing human‐induced species depletion and habitat fragmentation, this question and the study of genetic diversity in small populations are paramount to understanding the limits of species’ responses to environmental change and to providing remedies to endangered species conservation. Few empirical studies have investigated to what degree some small populations might be buffered against losses of genetic diversity. Even fewer studies have experimentally tested the potential underlying mechanisms. The study of Schou, Loeschcke, Bechsgaard, Schlotterer, and Kristensen ( 2017 ) in this issue of Molecular Ecology is elegant in combining classic common garden experimentation with population genomics on an iconic experimental model species (Drosophila melanogaster). The authors reveal a slower rate of loss of genetic diversity in small populations under varying thermal regimes than theoretically expected and hence an unexpected retention of genetic diversity. They are further able to hone in on a plausible mechanism: associative overdominance, wherein homozygosity of deleterious recessive alleles is especially disfavoured in genomic regions of low recombination. These results contribute to a budding literature on the varying mechanisms underlying genetic diversity in small populations and encourage further such research towards the effective management and conservation of fragmented or endangered populations.     

Unraveling the evolutionary history of the nematode Pristionchus pacificus: from lineage diversification to island colonization

The hermaphroditic nematode Pristionchus pacificus is a model organism with a range of fully developed genetic tools. The species is globally widespread and highly diverse genetically, consisting of four major independent lineages (lineages A, B, C, and D). Despite its young age (~2.1 Ma), volcanic La Réunion Island harbors all four lineages. Ecological and population genetic research studies suggest that this diversity is due to repeated independent island colonizations by P. pacificus. Here, we use model‐based statistical methods to rigorously test hypotheses regarding the evolutionary history of P. pacificus. First, we employ divergence analyses to date diversification events among the four “world” lineages. Next, we examine demographic properties of a subset of four populations (“a”, “b”, “c”, and “d”), present on La Réunion Island. Finally, we use the results of the divergence and demographic analyses to inform a modeling‐based approximate Bayesian computation (ABC) approach, where we test hypotheses about the order and timing of establishment of the Réunion populations. Our dating estimates place the recent common ancestor of P. pacificus lineages at nearly 500,000 generations past. Our demographic analysis supports recent (<150,000 generations) spatial expansion for the island populations, and our ABC approach supports c>a>b>d as the most likely colonization order of the island populations. Collectively, our study comprehensively improves previous inferences about the evolutionary history of P. pacificus.     

Sampling related individuals within ponds biases estimates of population structure in a pond‐breeding amphibian

Effective conservation and management of pond‐breeding amphibians depends on the accurate estimation of population structure, demographic parameters, and the influence of landscape features on breeding‐site connectivity. Population‐level studies of pond‐breeding amphibians typically sample larval life stages because they are easily captured and can be sampled nondestructively. These studies often identify high levels of relatedness between individuals from the same pond, which can be exacerbated by sampling the larval stage. Yet, the effect of these related individuals on population genetic studies using genomic data is not yet fully understood. Here, we assess the effect of within‐pond relatedness on population and landscape genetic analyses by focusing on the barred tiger salamanders (Ambystoma mavortium) from the Nebraska Sandhills. Utilizing genome‐wide SNPs generated using a double‐digest RADseq approach, we conducted standard population and landscape genetic analyses using datasets with and without siblings. We found that reduced sample sizes influenced parameter estimates more than the inclusion of siblings, but that within‐pond relatedness led to the inference of spurious population structure when analyses depended on allele frequencies. Our landscape genetic analyses also supported different models across datasets depending on the spatial resolution analyzed. We recommend that future studies not only test for relatedness among larval samples but also remove siblings before conducting population or landscape genetic analyses. We also recommend alternative sampling strategies to reduce sampling siblings before sequencing takes place. Biases introduced by unknowingly including siblings can have significant implications for population and landscape genetic analyses, and in turn, for species conservation strategies and outcomes.     

ABC as a flexible framework to estimate demography over space and time: some cons,many pros

The analysis of genetic variation to estimate demographic and historical parameters and to quantitatively compare alternative scenarios recently gained a powerful and flexible approach: the Approximate Bayesian Computation (ABC). The likelihood functions does not need to be theoretically specified, but posterior distributions can be approximated by simulation even assuming very complex population models including both natural and human‐induced processes. Prior information can be easily incorporated and the quality of the results can be analysed with rather limited additional effort. ABC is not a statistical analysis per se, but rather a statistical framework and any specific application is a sort of hybrid between a simulation and a data‐analysis study. Complete software packages performing the necessary steps under a set of models and for specific genetic markers are already available, but the flexibility of the method is better exploited combining different programs. Many questions relevant in ecology can be addressed using ABC, but adequate amount of time should be dedicated to decide among alternative options and to evaluate the results. In this paper we will describe and critically comment on the different steps of an ABC analysis, analyse some of the published applications of ABC and provide user guidelines.     

Combining capture–recapture data and pedigree information to assess heritability of demographic parameters in the wild

Quantitative genetic analyses have been increasingly used to estimate the genetic basis of life‐history traits in natural populations. Imperfect detection of individuals is inherent to studies that monitor populations in the wild, yet it is seldom accounted for by quantitative genetic studies, perhaps leading to flawed inference. To facilitate the inclusion of imperfect detection of individuals in such studies, we develop a method to estimate additive genetic variance and assess heritability for binary traits such as survival, using capture–recapture (CR) data. Our approach combines mixed‐effects CR models with a threshold model to incorporate discrete data in a standard ‘animal model’ approach. We employ Markov chain Monte Carlo sampling in a Bayesian framework to estimate model parameters. We illustrate our approach using data from a wild population of blue tits (Cyanistes caeruleus) and present the first estimate of heritability of adult survival in the wild. In agreement with the prediction that selection should deplete additive genetic variance in fitness, we found that survival had low heritability. Because the detection process is incorporated, capture–recapture animal models (CRAM) provide unbiased quantitative genetics analyses of longitudinal data collected in the wild.     

Genetic rescue: a safe or risky bet?

Small and isolated populations face threats from genetic drift and inbreeding. To rescue populations from these threats, conservation biologists can augment gene flow into small populations to increase variation and reduce inbreeding depression. Spectacular success stories include greater prairie chickens in Illinois (Westermeier et al. 1998 ), adders in Sweden (Madsen et al. 1999 ) and panthers in Florida (Johnson et al. 2010 ). However, we also know that performing such crosses risks introducing genes that may be poorly adapted to local conditions or genetic backgrounds. A classic example of such ‘outbreeding depression’ occurred when different subspecies of ibex from Turkey and the Sinai were introduced to assist recovery of an ibex population in Czechoslovakia (Templeton 1986 ). Despite being fertile, the hybrids birthed calves too early, causing the whole population to disappear. In the face of uncertainty, conservation biologists have tended to respect genetic identity, shying away from routinely crossing populations. In this issue of Molecular Ecology, Frankham ( 2015 ) compiles empirical data from experimental studies to assess the costs and benefits of between‐population crosses (Fig.  1 ). Crosses screened to exclude those involving highly divergent populations or distinct habitats show large heterosis with few apparent risks of outbreeding depression. This leads Frankham to advocate for using assisted gene flow more widely. But do the studies analysed in this meta‐analysis adequately test for latent outcrossing depression?     

ABC inference of multi‐population divergence with admixture from unphased population genomic data

Rapidly developing sequencing technologies and declining costs have made it possible to collect genome‐scale data from population‐level samples in nonmodel systems. Inferential tools for historical demography given these data sets are, at present, underdeveloped. In particular, approximate Bayesian computation (ABC) has yet to be widely embraced by researchers generating these data. Here, we demonstrate the promise of ABC for analysis of the large data sets that are now attainable from nonmodel taxa through current genomic sequencing technologies. We develop and test an ABC framework for model selection and parameter estimation, given histories of three‐population divergence with admixture. We then explore different sampling regimes to illustrate how sampling more loci, longer loci or more individuals affects the quality of model selection and parameter estimation in this ABC framework. Our results show that inferences improved substantially with increases in the number and/or length of sequenced loci, while less benefit was gained by sampling large numbers of individuals. Optimal sampling strategies given our inferential models included at least 2000 loci, each approximately 2 kb in length, sampled from five diploid individuals per population, although specific strategies are model and question dependent. We tested our ABC approach through simulation‐based cross‐validations and illustrate its application using previously analysed data from the oak gall wasp, Biorhiza pallida.     

Considerations for monitoring population trends of colonial waterbirds using the effective number of breeders and census estimates

Detecting trends in population size fluctuations is a major focus in ecology, evolution, and conservation biology. Populations of colonial waterbirds have been monitored using demographic approaches to determine annual census size (N_a). We propose the addition of genetic estimates of the effective number of breeders (N_b) as indirect measures of the risk of loss of genetic diversity to improve the evaluation of demographics and increase the accuracy of trend estimates in breeding colonies. Here, we investigated which methods of the estimation of N_b are more precise under conditions of moderate genetic diversity, limited sample sizes and few microsatellite loci, as often occurs with natural populations. We used the wood stork as a model species and we offered a workflow that researchers can follow for monitoring bird breeding colonies. Our approach started with simulations using five estimators of N_b and the theoretical results were validated with empirical data collected from breeding colonies settled in the Brazilian Pantanal wetland. In parallel, we estimated census size using a corrected method based on counting active nests. Both in simulations and in natural populations, the approximate Bayesian computation (ABC) and sibship assignment (SA) methods yielded more precise estimates than the linkage disequilibrium, heterozygosity excess, and molecular coancestry methods. In particular, the ABC method performed best with few loci and small sample sizes, while the other estimators required larger sample sizes and at least 13 loci to not underestimate N_b. Moreover, according to our N_b/N_a estimates (values were often ≤0.1), the wood stork colonies evaluated could be facing the loss of genetic diversity. We demonstrate that the combination of genetic and census estimates is a useful approach for monitoring natural breeding bird populations. This methodology has been recommended for populations of rare species or with a known history of population decline to support conservation efforts.     

Population genomics as a new tool for wildlife management

Admixture and introgression have varied effects on population viability and fitness. Admixture might be an important source of new alleles, particularly for small, geographically isolated populations. However, admixture might also cause outbreeding depression if populations are adapted to different ecological or climatic conditions. Because of the emerging use of translocation and admixture as a conservation and wildlife management strategy to reduce genetic load (termed genetic rescue), the possible effects of admixture have practical consequences ( Bouzat et al. 2009 ; Hedrick & Fredrickson 2010 ). Importantly, genetic load and local adaptation are properties of individual loci and epistatic interactions among loci rather than properties of genomes. Likewise, the outcome and consequences of genetic rescue depend on the fitness effects of individual introduced alleles. In this issue of Molecular Ecology, Miller et al. (2012) use model‐based, population genomic analyses to document locus‐specific effects of a recent genetic rescue in the bighorn sheep population within the National Bison Range wildlife refuge (NBR; Montana, USA). They find a subset of introduced alleles associated with increased fitness in NBR bighorn sheep, some of which experienced accelerated introgression following their introduction. These loci mark regions of the genome that could constitute the genetic basis of the successful NBR bighorn sheep genetic rescue. Although population genomic analyses are frequently used to study local adaptation and selection (e.g. Hohenlohe et al. 2010 ; Lawniczak et al. 2010 ), this study constitutes a novel application of this analytical framework for wildlife management. Moreover, the detailed demographic data available for the NBR bighorn sheep population provide a rare and powerful source of information and allow more robust population genomic inference than is often possible.     

Habitat continuity and stepping‐stone oceanographic distances explain population genetic connectivity of the brown alga Cystoseira amentacea

Effective predictive and management approaches for species occurring in a metapopulation structure require good understanding of interpopulation connectivity. In this study, we ask whether population genetic structure of marine species with fragmented distributions can be predicted by stepping‐stone oceanographic transport and habitat continuity, using as model an ecosystem‐structuring brown alga, Cystoseira amentacea var. stricta. To answer this question, we analysed the genetic structure and estimated the connectivity of populations along discontinuous rocky habitat patches in southern Italy, using microsatellite markers at multiple scales. In addition, we modelled the effect of rocky habitat continuity and ocean circulation on gene flow by simulating Lagrangian particle dispersal based on ocean surface currents allowing multigenerational stepping‐stone dynamics. Populations were highly differentiated, at scales from few metres up to thousands of kilometres. The best possible model fit to explain the genetic results combined current direction, rocky habitat extension and distance along the coast among rocky sites. We conclude that a combination of variable suitable habitat and oceanographic transport is a useful predictor of genetic structure. This relationship provides insight into the mechanisms of dispersal and the role of life‐history traits. Our results highlight the importance of spatially explicit modelling of stepping‐stone dynamics and oceanographic directional transport coupled with habitat suitability, to better describe and predict marine population structure and differentiation. This study also suggests the appropriate spatial scales for the conservation, restoration and management of species that are increasingly affected by habitat modifications.     

An enhanced expression of ABC 1 transporter in circulating leukocytes as a potential molecular marker for the diagnostics of glaucoma

Summary. Objective: Glaucoma is a neurodegenerative disease. Since vascular dysregulation is supposed to be a risk factor for the development of glaucomatous damage, the preventive treatment might slow down the disease development. The efficiency of the therapeutic treatment depends particularly on a drug efflux pump regulated by ABC transporters. ABC 1 is also known to participate on the vascular regulation. This study was focused on the comparative analysis of ABC 1 expression levels in circulating leukocytes of non-glaucomatous individuals and glaucoma patients.Results and conclusions: The expression rates of ABC 1 were significantly increased in leukocytes of glaucoma patients compared to non-glaucomatous individuals. The expression level of ABC 1 was, furthermore, highly homogeneous in glaucoma patients. In contrast, these expression levels in non-glaucomatous individuals were extremely heterogeneous. This transporter acts as the energy-dependent unidirectional transmembrane cholesterol efflux pump and can export a wide range of hydrophobic drugs. Additionally an observed enhanced ABC 1 expression in circulating leukocytes may be implicated in the vascular regulation mechanisms of glaucoma. We proposed the enhanced expression of ABC 1 in leukocytes as a potential marker for the diagnostics and ex vivo molecular monitoring of glaucoma.