Evolutionary narratives are replete with explicit or implicit references to such actions as "striving" or "struggling", but the origin of such directional behaviors is either not mentioned, or glossed-over. Such actions are simply postulated. But with centripetality we now encounter the roots of such behavior. Suddenly, the system is no longer acting at the full behest of externalities, but it is actively drawing ever more resources unto itself. Bertrand Russell (1960) called this behavior "chemical imperialism" and identified it as the very crux of evolutionary drive.
Centripetality further guarantees that whenever two or more autocatalytic loops exist in the same system and draw from the same pool of finite resources, competition among the foci will necessarily ensue, so that another postulated element of Darwinian action finds its roots in autocatalytic behavior. In particular, whenever two loops share pathway segments in common, the result of this competition is likely to be the exclusion or radical diminution of one of the non-overlapping sections. For example, should a new element D happen to appear and to connect with A and C in parallel to their connections with B, then if D is more sensitive to A and/or a better catalyst of C, the ensuing dynamics should favor D over B to the extent that B will either fade into the background or disappear altogether (Figure 4.5). That is, the selection pressure and centripetality generated by complex auto-catalysis (a macroscopic ensemble) is capable of influencing the replacement of its own elements. Perhaps the instances that spring most quickly to mind here involve the evolution of obligate mutualistic pollinators, such as yuccas (Yucca) and yucca moths (Tegeticula, Parategeticula) (Riley, 1892), which eventually displace other pollinators.
It is well-worth mentioning at this point that the random events with which an autocatalytic circuit can interact are by no means restricted to garden-variety perturbations. By the latter are meant simple events that are generic and repeatable. In Chapter 3 it was pointed out how random events can have a complex nature as well and how many such events can be entirely unique for all time. For example, if a reader were to stand on the balcony overlooking Grand Central Station in New York City and photograph a 10 X 10 m space below, she might count some 90 individuals in the picture. The combinatorics involved guarantee that it is beyond the realm of physical reality that repeating the action at a subsequent time would capture the same 90 individuals in the frame—the habits and routines of those concerned notwithstanding (Elsasser, 1969). Nor are such unique events in any way rare. Even the simplest of ecosystems contains more than 90 distinguishable individual organisms. Unique events are occurring all the time, everywhere and at all levels of the scalar hierarchy. Furthermore, the above-cited selection by autocatalytic circuits is not constrained to act only on simple random events. They can select from among complex, entirely novel events as well.
This ability of an autocatalytic circuit to shift from among the welter of complex events that can impinge upon it opens the door fully to emergence. For in a Newtonian system any chance perturbation would lead to the collapse of the system. With Darwin systems causality was opened up to chance occurrences, but that notion failed to take hold for a long while after Darwin's time, for his ideas had fallen into the shadows by the end of his century (Depew and Weber, 1995). It was not until Fisher and Wright during the late 1920s had rehabilitated Darwin through what is commonly known as "The Grand Synthesis" that evolution began to eclipse the developmentalism that had prevailed in biology during the previous decades. The Grand Synthesis bore marked resemblance to the reconciliation effected in the physical sciences by Boltzmann and Gibbs in that Fisher applied almost the identical mathematics that had been used by Gibbs in describing an ideal gas to the latter's treatment of non-interacting genetic elements. Furthermore, the cardinal effect of the synthesis was similar to the success of Gibbs—it re-established a degree of predictability under a very narrow set of circumstances.
With the recognition of complex chance events, however, absolute predictability and determinism had to be abandoned. There is simply no way to quantify the probability of an entirely unique event (Tiezzi, 2006b). Events must recur at least several times before a probability can be estimated. As compensation for the loss of perfect predictability, emergence no longer need take on the guise of an enigma. Complex and radically chance events are continuously impinging upon autocatalytic systems. The overwhelming majority have no effect whatsoever on the system (which remains indifferent to them). A small number impacts the system negatively, and the system must reconfigure itself in countering the effect of the disturbances. An extremely small fraction of the radical events may actually resonate with the autocatalysis and shift it into an entirely new mode of behavior, which can be said to have emerged spontaneously.2
Jay Forrester (1987), for example, describes major changes in system dynamics as "shifting loop dominance", by which he means a sudden shift from control by one feedback loop to dominance by another. The new loop could have been present in the background prior to the shift, or it could be the result of new elements entering or arising within the system to complete a new circuit. Often loops can recover from single insults along their circuit, but multiple impacts to several participants, as might occur with complex chance, are more likely to shift control to some other pathway.
One concludes that autocatalytic configurations of flows are not only characteristic of life, but are also central to it. As Popper (1990) once rhapsodically proclaimed, "Heraclitus was right: We are not things, but flames. Or a little more prosaically, we are, like all cells, processes of metabolism; nets of chemical pathways." The central agency of networks of processes is illustrated nicely with Tiezzi's (2006b) comparison of the live and dead deer ( just moments after death). The mass of the deer remains the same, as does its form, chemical constitution, energy, and genomic configuration. What the live deer had that the dead deer does not possess is its configuration of metabolic and neuronal processes.
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