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In a recent review, Zink Zink et al. 2008), and including their re-analysis of Bensch et al.’s (2006) data in their own review—have resisted the urge to comment on avian phylogeographic process. Next, we point out that even when the focus of phylogeographic studies is on pattern, statistical common sense suggests that when the desire is to make statements about populations or taxa—entities at a higher level of organization than the gene—one must sample multiple loci, even though we acknowledge that the field has for many years been comfortable doing so with a single locus. Drawing on recently published examples of multilocus studies in humans, we show that by describing nuclear genes as lagging indicators, ZB08 ignore the primary power of these markers—their multiplicity. In doing so, they fail to acknowledge that combining information from multiple nuclear genes can provide much finer descriptions of phylogeographic pattern than can the single locus provided by mtDNA. In summary, we suggest that the view of phylogeography espoused by ZB08 is a backward-looking one, one that ignores the ease with which nuclear sequence data can be collected even now—notwithstanding the imminent flood of nuDNA sequence data to be unleashed by modern sequencing technologies, especially for non-model species. Zink a temporally restricted pulse of hybridization or the type of ongoing and temporally uniform gene flow usually estimated in stepping-stone models? On its own, the observed pattern is very limited in its utility, for example, in understanding biogeography or species limits or for informing conservation. To ZB08, a well-resolved reciprocally monophyletic mitochondrial gene tree implies a history of isolation without gene flow—the most common process associated with this pattern. But is genetic distinctiveness useful on its own without any reference to process? For example, should we be comfortable delimiting species based on monophyly or lack thereof of mtDNA, without speculating as to how the pattern arose? As a case in point, in the greenish warbler, mtDNA exhibits two very distinct clades breaking the ring both north and south of the Himalayan range, but nuclear markers demonstrate smooth isolation by distance (Irwin et al. 2005), suggesting that the sharp mtDNA breaks are the result of stochastic processes. In addition to the fact that reciprocal monophyly can sometimes be driven by forces other than geographical isolation (e.g. natural selection or stochastic events), we suggest that the utility of pattern without process in cases of mtDNA monophyly is low and that even the most rudimentary interpretations of mtDNA pattern require statements of process, something that ZB08 suggest requires nuclear genes. We regard as unrealistic ZB08’s suggestion that the uses of mtDNA can be addressed by restricting inferences solely to pattern. In most early phylogeographic studies in birds, including those published by us (Edwards 1993; Bensch when we do, our assumption is that other markers will follow the mtDNA pattern. Early researchers in the field, such as Avise and others, knew this and routinely proffered the caveat that mtDNA does not record, for example, the history of males in the case of species with maternal inheritance of mtDNA. As another example of this point, when one achieves a high bootstrap support on a mitochondrial gene tree, most researchers are tempted to claim that the population harbouring that gene tree is also monophyletic, yet such an inference would not be warranted for both inferential and statistical reasons. The contrast between inferences of genes and populations when using mtDNA is also illustrated by the availability of multilocus methods now for estimating species trees, as opposed to gene trees (Edwards 2008; Liu et al. 2008); analysis of data with species tree methods suggests that the power of claims about population and lineage monophyly rests not on a single highly resolved gene tree but on the genealogical patterns at many loci and the accumulated signal among them, even in the face of extensive incomplete lineage sorting. In addition, there is always the possibility that the gene and species trees will differ; striking examples of mtDNA clades inferring groups wrongly come from the many examples of displaced clines for mtDNA and morphology or nuclear genes (see Ruegg 2008, for a recent example in birds). Directly extrapolating from the gene to the species was forgivable in the early days of phylogeography, but we suggest that, given the relative ease of assaying variation at nuclear markers now, making inferences from a single gene to statements about populations or species is unwarranted today, and that ZB08 have become unduly complacent with such inferences. Zink mtDNA is the leading indicator, nuDNA the trailing one’. However, this contrast of mtDNA vs. nuclear genes is misleading because it focuses only on gene-by-gene contrasts. In doing so, it fails to acknowledge (i) that the most useful measures of population differentiation rely specifically on the accumulated signals from many genes and (ii) that mtDNA is only a single gene in a population genetic sense. What one supposedly loses in the signal in any one nuclear gene relative to mtDNA one gains back by many orders of magnitude by adding additional nuclear genes to this signal. Many popular phylogeographic methods, especially those that focus appropriately on estimating parameters of populations and species rather than genes, are known to deliver more accurate and reliable estimates of population parameters with multiple than with single loci (Edwards Hey Maddison indeed, in humans, mtDNA (and Y-chromosome) monophyly is known only for the major branches in the human phylogeographic gene tree. Thus, the accumulated signal of multiple nuclear genes reveals details of phylogeographic pattern that far exceed what is provided by mtDNA alone (Rosenberg 2009). This is particularly the case when the among-population variation of any one nuclear marker is slight (FST among European geographical regions in their study was only 0.004); indeed formulas for estimating the number of markers required to differentiate populations with a given FST are known (Patterson et al. 2006). We acknowledge that most studies in birds or other non-model groups have yet to accumulate as many markers as are available in humans, but the number of accessible markers for birds and other groups is rapidly increasing (Backström et al. 2008) and will no doubt further increase as sequencing technology evolves. On the other hand, humans are among the most unstructured of vertebrate species, and it is likely that the population structure of most nonhuman animals will be resolvable with far fewer markers than are required by human phylogeography. The number of nuclear markers employed in avian phylogeographic studies has been steadily climbing and now rivals the 30–40 that were routinely characterized in allozyme studies of birds in the 1980s (Lee although we acknowledge that this is an unresolved issue of importance to phylogeography, the point that nuclear genes together have more resolving power than does mtDNA still stands. Many studies in humans and other groups now use multivariate, multilocus statistical methods other than gene trees to delimit and describe phylogeographic pattern. For example, when there are no multiple hits, the frequency spectra of SNPs for single populations or the joint spectra for multiple populations are sufficient statistics for data from single or multiple populations, respectively (i.e. they contain all the information present in the original data). ZB08 presumably failed to acknowledge the higher resolving power of nuclear genes because of their focus on gene trees, which as they and others have shown will often exhibit monophyly for mtDNA but not for nuDNA. Although gene trees are a useful way of describing phylogeographic diversity, they are not the only tools available and indeed many recent studies are moving away from gene trees as the main tool for describing phylogeographic pattern. There are many ways to diagnose species and populations other than via gene trees, and, for example, the accumulated signal of allele frequency shifts across many nuclear loci—a signal that mtDNA alone cannot possess—is now becoming the most powerful and sensitive means for delimiting diversity and pattern within species. To suggest that nonphylogenetic methods such as PCA or STRUCTURE have no place in phylogeography is to unnecessarily restrict the purview and methods that enrich the field. ZB08 point to other challenges of nuclear genes, such as the need for phasing unresolved haplotypes with multiple heterozygous loci. Although we acknowledge that phasing is indeed an uncertainty and that errors could lead to misestimation of nuclear gene trees (Hare 2001), the effect of such errors on other types of phylogeographic analysis is not known, and may be minimal. Regardless, because new sequencing technologies such as 454 determine the sequences of single DNA molecules, rather than collections of molecules as in dideoxy sequencing of PCR products, they will eliminate the phasing problem, which will soon be a thing of the past (Brito but the particular level of resolution provided by mtDNA is ultimately arbitrary, and one could just as easily favour the resolving power of a nuclear gene depending on one’s motives, especially given that subspecies boundaries in birds tend not to conform to mtDNA clades (Zink 2004). We believe that the large number of mtDNA-only studies in birds and other groups is a strong first step for these groups. Inevitably, however, if the field is healthy, phylogeography and its methods and tools will change through time. We suggest that the favouritism towards mtDNA displayed in ZB08 encourages becoming comfortable with a tool that has proven extremely useful, but is ultimately limited, and that can now be supplemented relatively easily by the enormous signal available in the many loci of the nuclear genome.
Edwards et al. (Mon,) studied this question.