There is no ladder
There’s been a little cluster of blog entries on the erroneous idea that evolution is an increase of complexity from bacterium to man. I work in a pathogen lab, which means we’re all acutely aware that we’re not at the top of the food chain. But I’m going to go one step further and really annoy a lot of people.
There is no biological complexity.
The only definition of complexity I’m aware of which isn’t unobservable handwaving is the concept of algorithmic complexity in computer science, which refers to how much computational power is required to compute something, from computable in constant time, to NP-complete (give up and go home). But there’s a catch: the computational power is that required by a universal Turing machine or equivalent. And you can often approximate the solution to NP-complete problems with statistical approaches much, much more cheaply (there’s a nice sort of introduction to this at the Quantum Pontiff). I have no idea how to define the complexity class of being able to live off of iron ore in a cave, but I don’t think it matters, as we’re dealing with evolution, not a Turing machine. It’s a genetic algorithm, by its very nature. That puts it squarely in the statistical mechanics side of things. (I would appreciate it if an actual complexity theorist would slap me down if I’ve gotten totally confused here.)
The other definitions people try to use are usually from “software complexity,” which is an attempt to measure how much work programmers have done without having to know anything about the programs they wrote. To anecdotally understand how screwed up this can get, go read the Evolution of a Programmer (or for the categorically minded, the Evolution of a Haskell Programmer).
If we stop worrying about complexity, however, we can get some really nice results about how things scale. Stride length, leg length, and running for instance. Giraffes can run. Their legs are just short enough. Elephants can’t. They physically can’t maintain a gait which has all the legs off the ground. Their legs are too long, but they can shuffle so fast that it doesn’t much matter. The blue whale’s circulation is a convective cooling system: when they die they cook because their own body heat can’t diffuse fast enough into the surrounding water.
And when the scaling laws break down, then you’re on to something really interesting. A certain phage geneticist is following one of these leads: DNA viruses usually encode their own DNA polymerase because they want to operate at a higher error rate than their host…but small DNA viruses which don’t have space to encode a DNA polymerase still, as a population, mutate much faster than their host. Here’s a case where simple arguments from genome size fail miserably.
There is a Zen concept that scientists really need to adopt: mu. The answer to a question may not be yes or no. It may be mu: there is no answer. Has complexity increased over the course of evolution from bacterium to man? Mu! Go check your assumptions.