This post is a continuation of a thread that starts here.

The algorithmic evolution models pioneered by Gregory Chaitin (see Proving Darwin,2012 for a very readable introduction) are based on a metaphor of an organism as a K-bit program that takes the original organism A and produces a mutated organism A'. The fitness of the organism/algorithm is measured by the largest integer the algorithm can calculate. Thus a mutation that increases the largest calculable number is retained, while others are rejected. This continues until BB(N), defined as the largest integer that can be produced by a <N-bit program that produces a single integer and then halts. 

This is a plausible analog for biological evolution, in which continuous improvement in fitness is possible, up to some maximum limit. In nature the maximum limits are presumably associated with maximum rates of biological processes rather than algorithmic complexity and information (i.e., BB(N), which has the awesome name of the Busy Beaver Number). 

Recently I had the pleasure of visiting the geography department at Texas A&M, and during my trip I was able to revisit some field sites along the Navasota River I had last been to in 2006. The lower Navasota is basically an anastamosing system--there is a single dominant channel, but multiple subchannels, some active at normal and low flows, at any given valley cross-section. One place is particular, Democrat Crossing, is a particularly confusing locus of recent and ongoing channel change. 

2017 Google Earth^TMimage of Democrat Crossing. Sand Creek is actually a perennial or active Navasota River subchannel (semi-active means, in my lingo, that it usually carries flow, but may dry up in low-flow periods). Some of the subchannels have been highlighted with blue lines I added, as you can't really see them if you don't already know they are there. 

More than one scholarly observer has remarked in the contrast between physics, characterized mostly by deterministic, hard-and-fast laws that operate the same way everywhere and always (at least the Newtonian physics that apply to Earth sciences) and biology. Biology is portrayed as being much more fluid and dynamic, in the sense that chance (e.g., mutations) and environmental adaptations play a major role. As Gregory Chaitin (2012; a mathematician, by the way, not a biologist) puts it, biota and evolution are creative, while physics is not. This tension is sometimes portrayed or exemplified as a Newtonian (as in Isaac Newton) vs. Darwinian (i.e., Charles Darwinian) outlook. 

I have much love for both Newton (left) and Darwin, but have chosen to follow Darwin with respect to my hairstyle.