jdp's blog


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 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 EarthTMimage 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. 


Historical contingency in fluviokarst landscape evolution was just published in Geomorphology 303: 41-52.  When I first came to central Kentucky in 2000 I began noticing the strong contrasts in landscape and landform development on inner vs. outer Kentucky River incised meander bends. Investigating this and related phenomena has occupied me off and on ever since. Only a few years ago I realized that given the nature of bend development over the past 1.5 Ma or so, the bend interiors represent a chronosequence of landforms. This paper exploits those chronosequences, using graph theory, to explore the role of historical contingency.


Chronosequence of strath terraces (T1, T2, T3) and other geomorphic surfaces at Polly’s Bend, Kentucky. The surfaces nearest the river are youngest; those farther away are oldest.


Below is a picture of raindrop impact craters after a rain last month on a beach along the Neuse River estuary, N.C. The spot pictured has no overhanging trees or anything else, so the craters represent direct raindrop impacts. As you can see, assuming crater size is related to drop size, they represent a large range (the largest craters pictured are roughly 10 cm in diameter; the craters must be at least slightly larger than the drops). Rainsplash is a significant factor in soil erosion--even if not directly important, the process is key for dislodging grains or particles that are then transported by runoff. Drop impact also influences surface crusting and sealing, and thereby hydrological response. So, I got to thinking, what is the potential significance of such a large variation in drop size?

Kinetic energy is given by KE = 0.5 m V^2, where m is mass in kg, and V is velocity in m/sec. A 2 mm diameter raindrop has a mass of 4.19 mg and a terminal velocity of about 6.26 m/sec. This gives a kinetic energy of about  0.00008 joules per raindrop.


In my experience, beer cans and bottles discarded as litter in the kinds of places where I recreate and do field work are about 80 percent Bud Light, 17 percent other undrinkable watery American light beers, and 3 percent all other brands combined. Recently, however, at a site along the Neuse River, North Carolina, the two dozen or so trash bottles I saw  on the ground included NO Bud Lights!

I am not well versed enough in contemporary cultural or economic geography to speculate as to whether this is a local anomaly, a shift in taste preferences for the kind of sh*tbag Bud Light drinkers who trash the countryside, or an expansion of litterbug behavior beyond the Lite beer crowd.

Of course, when it comes to beverage container trash, no brand of beer, soda pop, or anything else comes close to the mass or volume of plastic water bottles. Why don't you people use canteens, reusable bottles, or at least recycle these things?

Posted 22 January 2018



Ferricretes are soil or sediments cemented together by iron oxides. In eastern North Carolina, reducing conditions often prevail on the broad, flat interfluves. Under these conditions Fe is reduced, and soluble. Groundwater flow from these areas toward the major river valleys transports this dissolved ferric iron. When the groundwater discharges along the valley side slope it comes in contact with oxygen, and the iron oxidizes to its ferrous form. These iron oxides coat whatever material exists at that location--sand, clay, etc.

Limonite ferricrete at Fishers Landing, NC. The piece at the top is about 40 cm long. 


The development and change over time (evolution) of geomorphic, soil, hydrological, and ecosystems (Earth surface systems; ESS) is often, perhaps mostly, characterized by multiple potential developmental trajectories. That is, rather than an inevitable monotonic progression toward a single stable state or climax or mature form, often there exist multiple stable states or potentially unstable outcomes, and multiple possible developmental pathways. Until late in the 20th century, basic tenets of geosciences, ecology, and pedology emphasized single-path, single-outcome conceptual models such as classical vegetation succession; development of mature, climax, or zonal soils; or attainment of steady-state or some other form of stable equilibrium. As evidence accumulated of ESS evolution with, e.g., nonequilibrium dynamics, alternative stable states, divergent evolution, and path dependency, the "headline" was the existence of > 2 potential pathways, contesting and contrasting with the single-path frameworks. Now it is appropriate to address the question of why the number of actually observed pathways is relatively small.The purpose of this post is to explore why some developmental sequences are rare vs. common; why some are non-recurring (path extinction), and some are reinforced.


In a 2009 article I introduced the concept of a geomorphological niche, defined as the resources available to drive or support a particular geomorphic process (the concept has not caught on). The niche is defined in terms of a landscape evolution space (LES), given by

where H is height above a base level, rho is the density of the geological parent material, g is the gravity constant, and A is surface area. The k’s are factors representing the inputs of solar energy and precipitation, and Pgrepresents the geomorphically significant proportion of biological productivity (see this for the  background and justification).


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