Genetic datasets can be used to date evolutionary events, even on recent time scales if sufficient data are available. We used statistics calculated from multilocus microsatellite datasets to estimate population ages in data generated through coalescent simulations and in samples from populations of known age in a metapopulation of Daphnia magna in Finland. Our simulation results show that age estimates improve with additional loci and define a time frame over which these statistics are most useful. On the most recent time scales, assumptions regarding the model of mutation (infinite sites vs. stepwise mutation) have little influence on estimated ages. In older populations, size homoplasy among microsatellite alleles results in a downwards bias for estimates based on the infinite sites model. In the Finnish D. magna metapopulation, our genetically derived estimated ages were biased upwards. Potential sources of this bias include: the underlying model of mutation, gene flow, founder size, and the possibility of persistent source populations in the system. Our simulated data show that genetic age estimation is possible, even for very young populations, but our empirical data highlight the importance of factors such as migration and founding size when these statistics are applied in natural populations.

Raw Daphnia genotypesRaw (unbinned) genotypes at 14 microsatellite loci for each of 14 sampled populations of Daphnia magna.Raw-Storgrundet.csvRecoded Daphnia genotypesRecoded (binned) genotypes at 14 microsatellite loci for each of 14 sampled Daphnia magna populations.Recoded-Storgrundet.csvSample locationsGPS coordinates for each of the 14 sampled Daphnia magna populations from Storgrundet, a rocky island in the Tvarminne archipelago of Finland.SampleSites.xls