Texas A&M University Press has recently published Texas Riparian Areas. According to TAMU Press's blurb: 

Riparian areas—transitional zones between the aquatic environments of streams, rivers and lakes and the terrestrial environments on and alongside their banks—are special places. They provide almost 200,000 miles of connections through which the waters of Texas flow. Keeping the water flowing, in as natural a way as possible, is key to the careful and wise management of the state’s water resources.

Texas Riparian Areas evolved from a report commissioned by the Texas Water Development Board as Texas faced the reality of over-allocated water resources and long-term if not permanent drought conditions. Its purpose was to summarize the characteristics of riparian areas and to develop a common vocabulary for discussing, studying, and managing them.

For the past five years or so, I have been working on adaptations of algebraic or spectral graph theory to study geomorphic, pedological, and ecological systems. My most recent development (unpublished, for reasons that will become clear in a moment) is some methods for measuring the complexity of historical sequences in Earth surface systems.

The idea is that a historical sequence represents a series of different states or stages—for example, vegetation communities along a successional trajectory; river channel morphological states; different soils in a paleosol sequence; depositional environments in a stratigraphic sequence, nodes of phylogenetic trees in biological evolution, etc.  These are treated as directed graphs. The states or stages are the graph nodes or vertices, and the historical transitions are the edges or links between the nodes.

The standard conceptual model for pedology, soil geomorphology, and soil geography is often called the “clorpt” model, for the way it was portrayed in Hans Jenny’s famous 1941 book The Factors of Soil Formation:

S = f(cl, o, r, p, t) . . . .

This equation states that soil types or soil properties (S) are a function of climate (cl), biotic effects (o for organisms), topography (r for relief), parent material (p), and t for time, conceived as the age of the surface the soils are formed on, or the time period the soil has been developing under a given broad set of environmental controls. This factorial approach, considering soils as a function of the combined, interacting influences of environmental factors such as geology, climate, and biota, was originated by V.V. Dokuchaev in Russia in the 1880s, popularized in English by C.F. Marbut in the 1920s and 1930s, and developed by Jenny into the familiar clorpt form.

Nearly 10 years ago, while pondering complex nonlinear dynamics in geomorphic systems, I was struck by how often we reduce problems to the interplay of opposing forces (e.g. uplift vs. denudation; soil formation vs. soil erosion, etc). I began to wonder how the concept of dialectics might be applicable in Earth sciences, or maybe I just wanted to increase my pseudo-intellectual street cred by using "dialectics" in an article. Anyway, I started work on a manuscript with the working title shown above, and then dropped it. I rediscovered it on the hard drive recently, and while I still can't convince myself it is journal article material, I do think there's some potentially interesting ideas there. 

What you see below is what I wrote in early 2006 (thus the absence of reference to work since then), unmodified except for putting in a few graphics to relieve the visual tedium.

1. Introduction

The title begs at least three questions: what do I mean by dialectics, how am I defining complexity, and how do I propose to link them?

1.1.  Geomorphic Complexity

Everyone knows the classic normal distribution—the “bell curve,” where most observations cluster around the mean, and the frequency falls off toward either end, with well known statistical properties. Lots of things in nature are more-or-less normally distributed, but lots of things are not. In some cases distributions are “heavy-tailed,” such that for example there are many of the small ones, and increasingly fewer as size increases. Famous examples are the distribution of earthquake magnitudes, rank-size distributions of cities, and the distribution of wealth in societies.

Models of avalanche size distributions in (mathematically-simulated) sand piles were seminal in developing ideas about self-organized criticality and power laws, both in geomorphology and in general. Unfortunately even real sandpiles, much less more complex systems, are not necessarily well described by the models.

Scientists, including geographers and geoscientists, are easily seduced by repeated forms and patterns in nature. This is not surprising, as our mission is to detect and explain patterns in nature, ideally arising from some unifying underlying law or principle. Further, in the case of geography and Earth sciences, spatial patterns and form-process relationships are paramount.

Unfortunately, the recurrence of similar shapes, forms, or patterns may not tell us much. Over the years we have made much of, e.g. logarithmic spirals, Fibonacci sequences, fractal geometry, and power-law distributions—all of which recur in numerous phenomena—only to learn that they don’t necessarily tell us anything, other than that several different phenomena or causes can lead to the same form or pattern. The phenomenon whereby different processes, causes, or histories can lead to similar outcomes is called equifinality.

Center pivot irrigation in Kansas, USA (USGS photo).