Tuesday, January 11, 2011

Integrating Economic Gain in Biosocial Systems

A few of the past posts have drawn attention to West's work on scaling rules and, in particular, the distinction between the sublinear scaling properties of biological processes as compared to the superlinear scaling properties of social processes.

A recently published article by Timothy Allen, Joseph Tainter and others (Integrating Economic Gain in Biosocial Systems in Systems Research and Behavioral Science Syst. Res. 27, 537-552 2010) develops a model that has relevance to this situation, though its more explicit focus is on how systems evolve. Specifically, they note that observed hierarchies change their level structure and organization as they pass through time. Think, for example, of the European Union. This is an attempt to reorganized a social system through the insertion of an intermediate hierarchical level (the EU) that sits between the existing hierarchical levels of socio-economic organization at the level of the state and at the global scale. This idea is consistent with the work of Holling and other panarchy theorists who argue that the number of levels in a panarchical hierarchy can increase through time.

Allen et al argue that "The concept of gain and profit is introduced into ecology as a way of summarizing strategies of biological and social structures. High gain systems can be predicted by flux as they take in fuel at a rate. Low gain systems must refine low-quality materials in order to acquire fuel. Low gain systems are predictable from their plans and coded behaviour. Changes from high to low gain mode and vice versa represent a reordering of a hierarchy over time." The model of socio-ecological systems they utilize is described below.

Figure 1 "There are two basic parts to biological and social systems: thermodynamic happenings and coded limitations. The coded information amounts to plans which are executed in some sort of construction process. In biological systems the codes might be embodied in DNA, hormones or even mating dances. The construction might be protein synthesis, but could equally be making a nest for a bird. In social systems, there are many modes of construction, all involving plans. The whole constructed material system is an update on the narrative that the whole tells its mates, predators and prey. The scientist observes the updated whole with its extended story. The scientists tell stories about those stories amongst themselves. The construction may not live up to the plans such that the system must become something else more efficient by creating a new plan. Economists let their systems continue to tell their respective stories as they watch adjustments in plans as the system repeatedly becomes more economical, more flexible or bigger. Ecologists and biologists in general do not wait for their systems to update, and merely note that the old plan fails to work as resources are used up. Economists expect adjustments to be only temporary and simply note that scarcity increases costs that demand ever more efficiency."

Note the role of the observer in the above model. Definition of a system as high gain or low gain is dependent on the level of analysis. Thus, if the boundary of the system is the fuel entering the car, then the system is high gain. But if the system is bounded to include oil drilling, transportation and refinement, with crude oil as the original input, then it is low gain.

And the manner in which work gets done is dependent on whether the system is low or high gain. "High gain takes in high quality material and degrades it without effort put into being efficient: profligate consumption. Low gain efficiently degrades inputs to get more work out of them. The option may then be open for taking in lower quality of inputs. There is not only more quantity of raw lower quality inputs, but they also contain potential for producing a greater quantity of refined material that is of the same quality as the high gain inputs used directly as fuel. Degradation is separate from dissipation, which is input quantity times degradation. Low gain in the end gets more work done by increased degradation opening the door to greatly increased dissipation."

The article ends with a discussion of termites aimed at illustrating the processes of system evolution.
Termites make a very good example of how shifts over evolutionary time follow the patterns of high and low gain. Primitive termites eat good wood in which they live. In the end they literally eat themselves out of house and home. These high gain termites are forced to reproduce and move to a new site where new good wood prevails (Thorne and Traniello, 2003). The forced move amounts to a high gain collapse. More advanced termites eat a wide range of organic materials from the environs (Wilson, 1971). As opposed to the moderate colonies of high gain termites, the large low gain termite colonies live in huge ventilated mounds built of saliva cemented feces. They still eat woody material but they do so by gathering dead and rotting wood from the landscape around them. The large size of these colonies is characteristic of low gain systems. Lower quality woody remains exist in larger quantities over an area than does good wood. Good wood is a local resource, focused on individual chunks. Gathering woody material that is diffuse is clearly low gain and offers economies of scale.

The figure to the left shows "termite evolution from high to low gain on a pleated surface. Starting up in the top left of the surface, high gain termites eat themselves out of house and home, collapsing at point A where the colony must reproduce and move. The shift to low gain always occurs only as the instability is imminent. The course correction at the last minute avoids collapse of the resource base by becoming suddenly much more efficient. The correction may avoid collapse by reaching the continuous surface at point B. The alternative route to B is the dotted line of prudent planning. No system ever does that because it is out-competed by high gain rivals, and there is no incentive to economize anyway. Point B is transitional. It leads to low gain efficiency and increase in size due to economies of scale at point C. Burdened with much infrastructure the low-gainers at C can become too large and demanding, in which case they fall over the front side of the surface. The super low gain strategy of the soil eaters goes to point D with deep adaptation and energy limiting super low gain resources."

This article is both deep and abstract. As I've only started to seriously work my way through it, I've focused more on expanded quotes rather than summary and exposition. Any thoughts?


  1. 1. Just one question for clarification: is there a missing descriptor in this sentence:
    "High gain systems can be predicted by flux as they take in 'xxx' fuel at a rate."

    Would that be a 'high' rate or 'fluctuating' rate?

    2. I had learned the general rule of thumb in systems theory that the degree of complexity in a system is directly related to the amount of energy in a system. High energy input increases organizational complexity.

    This model seems to be saying that there are differences in the quality and spread of energy in a system, and those differences shape the operation of the system. A high-gain system finds scarce, high-quality energy that produces a localized, or specialized, operating system that serves a smaller population, e.g. the wealthy few.

    A low gain system finds lower-grade energy sources that are more abundant but require more processing (labour) and that support a larger population, e.g. the poor majority. The low-gain system compensates for the low-grade of energy by being more efficient. Too much demand or too much infrastructure can cause systemic breakdown in a low-gain system.

    A society level example might be this: the wealthy have more money—a high-gain system which buys energy to do work—to buy all their food from whatever world market they choose. The poor grow community gardens and small farms to grow their own food—a low-gain but energy efficient system—but its limits are the amount of food that can be produced. Too much demand causes the failure of the local food system.

  2. What I like about this model is the link between energy and information. I have been learning more about this from a book by MIT physicist, Seth Lloyd, called "Programming the Universe." Energy and information are not the exactly same thing, but they are inseparable and mutually constituting. Energy takes different forms, and the particular form that energy takes is information about that energy. Energy is conserved in more tightly organized, complex systems (1st law thermodynamics). Information is also conserved in tightly organized systems (1st law). That's why evolution tends tends towards more complex and integrated systems.

    Information is the amount of data needed to describe (or differentiate) the exact position and velocity of a particle of energy. Highly disorganized systems, like helium atoms in a balloon, require more information to describe the exact position and velocity of each helium atom in the balloon. Highly organized systems, like one brick stacked squarely on top of another, require less information to describe the exactly position and location of the bricks. Higher levels of organization conserve information (brick level) more efficiently, than lower levels of organization (atoms in the bricks). That's why systems tend toward more tightly integrated forms of organization and more layers of organization. They conserve both energy and information.

  3. I also think its interesting that Tainter's model defines information as 'codes', similar to Luhmann's codes. My goal, since studying Luhmann, has been to understand the link between social systems, i.e. information or coding, and thermodynamics, i.e. energy. Tainter's model seems to put these together. But I would also have to reconcile West's scaling theory. Seth Lloyd's point about the conservation of energy and information in complex systems seems to mirror West's theory: that material systems become more efficient as they scale up in size and complexity, i.e. urban infrastructure. However, social systems are super-exponential: they grow to an enormous size to the point of collapse, unless redirected by a new system of organization. The Internet is an example of introducing many more layers of hierarchy, integration and complex organization into the social system in order to avoid collapse and facilitate a new growth trajectory. This also follows Lloyds theory that systems tend toward more complexity and tighter integration.