I imagine they're using genome size (number of bases in exons) as their measure of complexity, not something ill-defined.
I don't think it's sensitive the way you say, since they're basically just linearly extrapolating the logarithm, but I haven't read the paper. If you somehow manage to shoot high or low by a factor of 100, that's only a temporal error of six or seven doublings. The bigger issue is that they're extrapolating over orders of magnitude that we have no direct evidence about.
> I imagine they're using genome size (number of bases in exons) as their measure of complexity, not something ill-defined.
They're taking genome size and trying to relate it to time. And the way that they're doing that is to take organisms from the present day, and imagine some of them in the past. The less "developed" or "complex" an organism is, the further in the past they put it. That process is the flawed part.
In other words, the y-axis (genome size) is well-defined, but the mapping of organisms onto the x-axis (time) is not.
I don't think it's sensitive the way you say, since they're basically just linearly extrapolating the logarithm, but I haven't read the paper. If you somehow manage to shoot high or low by a factor of 100, that's only a temporal error of six or seven doublings. The bigger issue is that they're extrapolating over orders of magnitude that we have no direct evidence about.