The reliability of molecular clocks in reptile phylogenies?

Hi folks,

I read about molecular clocks and the Neutralist Theory and, the more I read, the more I’m getting curious about how reliable these models are when applied to reptile phylogeny to determine the evolutionary age of lineages (at least when using mtDNA for phylogenies).

I understand that the basic principal on which the molecular clock theory is based is the constant rate of neutral mutations (those that do not affect the phenotyp) in genes. Furthermore, rate of neutral mutation is also independent from population size (sensu Kimura), whereas in advantageous mutations population size has to be considered as well…

Well, today we know that there is nothing like a “universal molecular clock”. Slopes and upswings in mutation rates must be calculated for every lineage and a priori assumptions have to be made to “set” the clock.
I recall some papers on reptile phylogeny worked with the pseudo-standard rate of 2% MYA for mtDNA (e.g. Keogh et al., 2001), although the authors mentioned that more recent studies revealed slower or faster clocks (=levels of gene divergence) (e.g. Zamudio & Greene (1997) for allopatric populations of Lachechis (0.47 – 1.32% /My) or more recently Wüster et al. (2002) with 1.09 – 1.77% for the cyt b of the crotaline genus Porthidium. The latter rates were also used by Malotra and Thorpe (2004) for Trimeresurus.). So, at the end, how relieable is the usage of the 2% rate in Keogh et al. (2001). I recall a paper (ARBOGAST, B. S. and J. B. SLOWINSKI 1998) taking apart a priviously published paper from Klicka and Zink due to errornous assumptions and for not providing measures of errors...

What about all these side-effects that may have more or less impact on the rate of mutation in genes such as the negative body size correlation and some life-history traits (temperature), gene repair capabilities, selective pressure, advantageous mutations rather than neutral mutations and implied within population size, evolving geographic barriers and diseases that may kill most of a population, other traits of population dynamics, high UV-radiation causing more mutations, and others). How do we handle these? There are lots of stochastic models around but, who decides which of these side-effects (if any) may have taken place?

Cheers,
Wulf
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