Another paper that addresses the speciation process in apes is:
Becquet and Przeworski
Genome Research 17:1505-1519
How populations diverge and give rise to distinct species remains a fundamental question in evolutionary biology, with important implications for a wide range of fields, from conservation genetics to human evolution. A promising approach is to estimate parameters of simple speciation models using polymorphism data from multiple loci. Existing methods, however, make a number of assumptions that severely limit their applicability, notably, no gene flow after the populations split and no intralocus recombination. To overcome these limitations, we developed a new Markov chain Monte Carlo method to estimate parameters of an isolation-migration model. The approach uses summaries of polymorphism data at multiple loci surveyed in a pair of diverging populations or closely related species and, importantly, allows for intralocus recombination. To illustrate its potential, we applied it to extensive polymorphism data from populations and species of apes, whose demographic histories are largely unknown. The isolation-migration model appears to provide a reasonable fit to the data. It suggests that the two chimpanzee species became reproductively isolated in allopatry ~850 Kya, while Western and Central chimpanzee populations split ~440 Kya but continued to exchange migrants. Similarly, Eastern and Western gorillas and Sumatran and Bornean orangutans appear to have experienced gene flow since their splits ~90 and over 250 Kya, respectively.
The effective population sizes, the Ns, tells us something about the diversity of the species (where NA tells us about the ancestral species). The split time, T, gives us the speciation time, and the migration parameter, m, tells us something about the way the speciation occured (an allopatric vs parapatric model).
As usual for coalescence models, the full likelihood of the parameters is computational demanding to compute, so the authors use summary statistics instead -- somewhat like an Approximate Bayesian Computation (ABC) method if you can call it that when you want to match the summaries exactly -- and then develop a Markov Chain Monte Carlo (MCMC) method to sample from the likelihood function over the summary statistics.
Based on this model, they then estimate speciation times for sub-species of chimps, gorillas and orangutans.
Citation for Research Blogging:Becquet, C., Przeworski, M. (2007). A new approach to estimate parameters of speciation models with application to apes. Genome Research, 17(10), 1505-1519. DOI: 10.1101/gr.6409707