Repetitive sequences in phylogeographic inference: a reply to Saltonstall and Lambertini (2012)

In 2011, Vachon and Freeland presented the results of a study that illustrated the importance of considering mutation patterns, including the potential for homoplasy, when deciding whether to include or exclude repetitive sequences from phylogeographic inferences. Saltonstall and Lambertini (2012) criticized this study by suggesting that some of the analyses and interpretations were flawed. In this reply, we explain why we disagree with most of their criticisms and identify some inconsistencies in their analyses. Most importantly, we reiterate the need to examine underlying assumptions, particularly with respect to mutation patterns, when using molecular genetic data to untangle evolutionary relationships.     

Statistical methods in spatial genetics

The joint analysis of spatial and genetic data is rapidly becoming the norm in population genetics. More and more studies explicitly describe and quantify the spatial organization of genetic variation and try to relate it to underlying ecological processes. As it has become increasingly difficult to keep abreast with the latest methodological developments, we review the statistical toolbox available to analyse population genetic data in a spatially explicit framework. We mostly focus on statistical concepts but also discuss practical aspects of the analytical methods, highlighting not only the potential of various approaches but also methodological pitfalls.     

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.     

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 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?