Short works

Books : reviews

Brian C. Goodwin.
How the Leopard Changed Its Spots: the evolution of complexity.
Phoenix. 1994

rating : 3 : worth reading
review : 26 February 2002

Goodwin wants to put the organism back into biology, ousting, or at least complementing, the role of the genes.

Ever since Darwin the story has been growing that we, and all creatures, are a product of our genes, and that evolution acting on those genes steers creatures in the direction of greater fitness. But this description concentrates on the genes at the expense of the organism itself. It also seems to miss several points about organism structure. Goodwin provides varied examples of structure that seem to be caused mostly by the dynamic processes occurring as the organism develops, and only tweaked by any genetic component. For example the whorls that continually appear and then disappear on the stalk of Acetabularia in the early stages of its development have no very obvious adaptive explanation, but can be explained as a natural consequence of symmetry breaking and dynamical processes during the growth of the stalk.

Goodwin emphasises process over state. The dynamic process of an organism developing is more important, more interesting, than the state it develops into. And that process is more determined by the physical environment, the morphogenetic field it occurs in, than by the genes. These dynamical process, and their basins of attraction, constrain the forms the organism can take, and also only make sense in terms of the entire organism and its development.

Goodwin also shows how the metaphors we use affect the way we think about biological processes. As a very simple example, our talk of biological fitness peaks (rather than physical minimum energy valleys, say), leads naturally to a metaphor of an effortful struggling to climb those peaks (rather than a principle of least action, of effortlessly rolling down into the valleys). He also argues that the emphasis on genes and struggle arose so readily because it fit so naturally with then pre-existing cultural myths, especially of the Fall, sin and redemption. That has led to a "competitive" metaphor that may be harmful. The metaphors associated with complex dynamical systems may be less harmful "cooperative" emergent ones.

Towards the end of the book Goodwin leaves the biology of individual organisms, and looks at how the same principles of dynamical systems might apply to groups of individuals -- to societies. This is interesting, but rather underdeveloped, as it takes up only part of a single chapter. He concludes with a comment that this new biology of organisms leads to the idea that their value is intrinsic to their very existence, in contrast to a biology concentrating on genes, with only extrinsic value from what they do, and whether they succeed. He hopes that this will lead to a more sympathetic view of the rest of life on this planet.

Goodwin's biological arguments are certainly convincing. This is an excellent description of how important dynamical processes are to biological systems, and how biology is changing to a more theoretical, less "historical", science. He provides a T. Ingold quote that sums up what are the key features of this new science (not just biology, but all of complex systems theory):

It must be a biology that asserts the primacy of processes over events, of relationships over entities, and of development over structure.

Selected quotes

of the Beloussov-Zhabotinsky reaction:

There is no plan, no blueprint, no instructions about the pattern that emerges. What exists in the field is a set of relationships between the components of the system such that the dynamically stable state into which it goes naturally ... has spatial and temporal pattern.

similar patterns of activity can arise in systems that differ greatly from one another ... chemical reactions, aggregating slime mould amoeba, heart cells, neurons, or ants in a colony ... all show similar dynamic activity: rhythms, waves that propagate in concentric circles, spirals that annihilate when they collide, and chaotic behaviour.

Explanations in terms of history and natural selection are not helpful since they simply redescribe what is observed in terms of function and cost, but you are no wiser for the 'explanation'.

we are ... looking for the general principles of biological organization that could account for the forms of life.

the distinctive quality of morphogenetic dynamics in living organisms appears to be that shape is generated within and by a moving boundary, the dynamics changing the shape while the changing shape feeds back onto the dynamics, stabilizing the modes that generate the form and creating conditions for the next bifurcation.

Genes don't control; they co-operate in producing variations on generic themes.

[the eye] has evolved independently in at least 40 different lineages ... eyes are not improbably at all. The basic processes of animal morphogenesis lead in a perfectly natural way to the fundamental structure of the eye.
eyes have arisen independently many times in evolution because they are natural, robust results of morphogenetic processes.
As descriptions of biological processes become more sophisticated in terms of the dynamics of complex systems, there will inevitably be a tendency to abandon the use of non-generic fitness functions and to use the language of basins of attraction, attractors and repellors (unstable states), and trajectories.

autopoesis [is] the capacity of active self-maintenance and self-generation that underlies regeneration, reproduction, and healing, which are all manifestations of the capacity of organisms to generate coherent wholes.

[autopoesis] is an emergent property of life ... exploring its potential for generating new wholes.
much ... of the order that we see in living nature is an expression of properties intrinsic to complex dynamic systems organized by simple rules of interaction among large numbers of elements. This order is generic, and what we see in evolution may be primarily an emergence of states generic to the dynamics of living systems.

the parts of an organism ... are not made independently and then assembled, as in a machine, but arise as a result of interactions within the developing organism.

reproducing organisms [are] systems with the property that a part can produce a whole, so that they can regenerate and reproduce their own natures.

Ricard V. Sole, Brian C. Goodwin.
Signs of Life: how complexity pervades biology.
Basic Books. 2000

rating : 3 : worth reading
review : 24 November 2002

This is a fascinating account of the laws of complexity, and how they are exhibited in various biological systems. We get accounts of physiology, of the brain, of social insects, of ecological webs, and of evolution. The book forms a good bridge between coffee table popularisations and detailed research papers. It includes technical details, but separated off into boxes, to make them easy to skip if so inclined. [The boxes are more difficult to read than they need be, though, using a font unsuitable for mathematics, in black on a dark grey background.]

We learn that genes aren't everything: that the interaction of the organism with its environment, self organising to the edge of chaos, provides a strong framework within which the genes can tinker.

Chaos and order live together and generate unexpectedly robust patterns of emergent organization.
     The role of genes within this dynamic context is considerably less than full control and determination of the developing organism. ... they have the simpler task of stabilizing generic patterns of emergent complexity in these multicellular systems.

We learn that dynamics is an important feature of these systems: brains are not simply passive recognisers, but active systems.

different learned stimuli were stored as a spatio-temporal pattern of activity, and the strange attractor characteristic of the attention state was replaced by a new, much more ordered attractor related to the recognition process.

Most current models of neural networks perform remarkably well in a wide range of areas, but are clearly different from the far-from-equilibrium behaviour of real neural assemblies.

[these results suggest] that brain dynamics might involve multiple attractors and that a coherent and flexible information processing system requires both order and disorder to operate.

We learn of the importance of social insects.

the dry weight of ants and termites in some rainforests is about four times that of all the other land animals

We learn how the environment plays a large role in the observed complexity of social insects. Indeed, the differences in the environment alone may be sufficient to explain different behaviours in different specifies of ants.

[This ant behaviour simulation is] consistent with Chris Langton's 1990 conjecture ... that living systems would maximise their computational capabilities at the edge of chaos. Computation, in other words, would require some amount of order, since information must be stored in some stable way. But the manipulation of information also requires some internal degree of disorder. The optimal compromise between both requirements occurs at the transition between order and disorder.

When many small sources [of food] are present, it is more effective to be able to switch quickly from an already exploited source to a new one. On the contrary, if the colony exploits rich but rare sources, it is important to guarantee that the sources of food are fully exploited at the cost of a reduced exploratory capacity. That the compromise between flexibility and efficiency seems to find a place close to criticality is suggested in particular by the fractal patterns displayed by [the foraging trails of] some species.

There are some lovely examples of using 3D cellular automata to model nest building behaviour, again showing how it is the interaction with the environment can profoundly affect behaviour.

A given spatial configuration ... triggers the response of a termite worker which modifies the configuration ... As the configuration changes, so do the behavioural patterns of the individuals. There is thus constant feedback between the emerging structure and the spatial distribution of activity and worker activity.

the same individual level behaviours my generate different collective responses in different environments. There is no need to invoke individual complexity in order to explain the origins of nest complexity. ... Selective pressures operate on a parameter space where there is a limited number of possible dynamical patterns and nonlinear rules. As a consequence, only a limited (but rather diverse) set of higher-level structures can be obtained.

We learn that examining single species does not tell us enough about the dynamics of complex ecological systems. Multiple species interact in non-linear an non-intuitive ways.

understanding real ecologies requires a scale of organisation far beyond the single-species level, which is simply uninformative about community dynamics.

extensive calculations ... on real food webs show that in many cases adding predators can increase the number of prey. Indirect pathways very frequently dominate direct pathways in determining the long-term outcomes of perturbations.

We learn that adding a spatial dimension to the models has a dramatic effect on the solutions possible. New solutions become possible, by allowing waves of interactions to propagate through the space. This point is made by discussing solutions to non-spatial equations, where certain parasitic behaviours are non-viable, then adding a spatial component (usually only two dimensions) and diffusion or percolation, and showing that viable solutions are now possible. [Unfortunately, some later arguments are then given for the simpler non-spatial cases only, leaving me wondering if the results are meaningful.]

The book could do with better editing. It is somewhat stodgily written in places, there are typos, and in one chapter many of the reference numbers are off by one. Despite this, Signs of Life is well worth the effort of reading. It covers a great range of biological examples, showing how many kinds of complex behaviours, non-linear processes, and emergent properties occur. Although the maths is boxed off to protect the faint hearted, the actual equations discussed are very simple -- yet displaying that astounding complexity and subtlety of solution that pervades this whole subject. And the references to more detailed literature let you follow up specific cases of interest, should you want to.

Further selected quotes:

a strange attractor: a region to which trajectories are attracted but within which they diverge

genotype and environment do not determine cell state in bacteria. Change of state can occur spontaneously, without any defined internal or external cause.

a distinctive characteristic of networks with K = 2 ... is canalization ... fourteen of the sixteen [Boolean functions of two variables] are canalizing functions. ... For K = 3 ... only 16 of the 256 Boolean functions of three variables are canalizing, and for K = 4 the fraction drops below 1%. A useful way of studying the transition from order to chaos in these networks is to vary the proportion p of 0's and 1's in the output column of the Boolean functions
[So, can you design a system that self-organises its value of p to the edge of chaos?]

[studying the brain as a black box] is rather like trying to know the details of a movie by watching people leave the theater.

ecosystems contain many more species than would be necessary if biological efficiency were the criterion for their organisation.

... Bak's idea should be generalised for those systems not displaying a well-defined scale separation between the driving force ... and the avalanches ... Since the requirement that the driving force be very slow is a strong one, one is unlikely to observe power laws in some systems that are nonetheless organised close to instability points.

increasing evidence suggests that viruses are often the result of the escape of fragments of functional genetic programs from their hosts.

the Red Queen Hypothesis. ... the probability of a species becoming extinct is approximately independent of its length of existence. ... But if evolution leads to improvement through adaptation, aren't modern mammal species more durable than their ancestors? ... species do not evolve to become any better at avoiding extinction. ... species continually adapt to each others' changes. ... species change just to remain in the evolutionary game. Extinctions occur when no further changes are possible

Brian C. Goodwin.
Nature's Due: healing our fragmented culture.
Floris Books. 2007