Indeed, in this paper they attempt to use Batwing to estimate ages using the effective rate. Batwing employs a Bayesian method with coalescent simulations, and thus takes into account "population history", the effects of which are supposedly encapsulated in the effective mutation rate. Thus, they are "correcting" (inappropriately of course) for population history twice.
This is clearly evident in the Table, where the Batwing age estimates exceed significantly those based on Y-STR variance, prompting the authors to reject the Batwing results as not "credible". Not credible indeed, if one blindly picks a "mutation rate" and a piece of software from the literature and combines them to arrive at an "estimate".
The R1a1 age estimates are properly all within a Neolithic time frame. Of course, the network topologies and associated Y-STR variance argue strongly against a simple Out-of-Eastern Europe scenario of the dispersal of R1a1, as non-star topologies with very high variance are found in India and Pakistan. This parallels another recent study in which a substantial subset of Indian R1a1 Y-chromosomes appeared to be distinctive from those of Europe.
Together, with the recent work on horse domestication, these results point to the fact that there is something wrong in the equation of R1a1 "PIE-speaking Bronze Age horse riders from the Pontic-Caspian steppe". Clearly, the picture is more complex, and will only be resolved when new SNPs resolve the phylogeny of this widespread haplogroup.
Also of interest:
As older ages are observed when grouping All Asians versus All Europeans (Table 5) for N1c, the available data suggest that the mutation may have originated in northern China as previously reported,14,15 but may have traversed through a different migratory route than has been postulated elsewhere,15 reaching northeastern European populations before the Urals
European Journal of Human Genetics doi:10.1038/ejhg.2009.6
Y-Chromosome distribution within the geo-linguistic landscape of northwestern Russia
Sheyla Mirabal et al.
Populations of northeastern Europe and the Uralic mountain range are found in close geographic proximity, but they have been subject to different demographic histories. The current study attempts to better understand the genetic paternal relationships of ethnic groups residing in these regions. We have performed high-resolution haplotyping of 236 Y-chromosomes from populations in northwestern Russia and the Uralic mountains, and compared them to relevant previously published data. Haplotype variation and age estimation analyses using 15 Y-STR loci were conducted for samples within the N1b, N1c1 and R1a1 single-nucleotide polymorphism backgrounds. Our results suggest that although most genetic relationships throughout Eurasia are dependent on geographic proximity, members of the Uralic and Slavic linguistic families and subfamilies, yield significant correlations at both levels of comparison making it difficult to denote either linguistics or geographic proximity as the basis for their genetic substrata. Expansion times for haplogroup R1a1 date approximately to 18 000 YBP, and age estimates along with Network topology of populations found at opposite poles of its range (Eastern Europe and South Asia) indicate that two separate haplotypic foci exist within this haplogroup. Data based on haplogroup N1b challenge earlier findings and suggest that the mutation may have occurred in the Uralic range rather than in Siberia and much earlier than has been proposed (12.9plusminus4.1 instead of 5.2plusminus2.7 kya). In addition, age and variance estimates for haplogroup N1c1 suggest that populations from the western Urals may have been genetically influenced by a dispersal from northeastern Europe (eg, eastern Slavs) rather than the converse.