The Systems View of Life: A Unifying Vision

by Fritjof Capra

This spontaneous emergence of order at critical points of instability – often referred to simply as “emergence” – has been recognized as one of the hallmarks of life,

As there are only a small number of different types of attractors, so too there are only a small number of different types of bifurcation events, and like the attractors the bifurcations can be classified topologically.

This similarity of images from vastly different scales has been known for a long time, but before Mandelbrot nobody had a mathematical language to describe it.

strange attractors are exquisite examples of fractals.

it has become customary to define strange attractors as trajectories in phase space that exhibit fractal geometry.

Similarly, a crumpled-up piece of paper fills up more space than a plane but less than a sphere. Thus, the more tightly the paper is crumpled, the closer its fractal dimension will be to 3.

The more jagged the outlines of lightning or the borders of clouds, the rougher the shapes of coastlines or mountains, the higher are their fractal dimensions.

the fractal patterns of clouds, which originally inspired Mandelbrot to search for a new mathematical language, are perhaps the most stunning. Their self-similarity stretches over seven orders of magnitude, meaning that the border of a cloud magnified 10 million times still shows the same familiar shape.

The Mandelbrot set is a storehouse of patterns of infinite detail and variations. Strictly speaking, it is not self-similar because it not only repeats the same patterns over and over again, including small replicas of the entire set, but also contains elements from an infinite number of Julia sets. It is thus a “superfractal” of inconceivable complexity.

In classical mathematics, simple formulas correspond to simple shapes, complicated formulas to complicated shapes.

In nonlinear dynamics the situation is dramatically different. Simple equations may generate enormously complex strange attractors, and simple rules of iteration give rise to structures more complicated than we can even imagine.

autopoiesis means “self-making”.

cognition is inseparable from autopoiesis, as we shall explain later on in this chapter.

Now ask the question: what, beyond the great biodiversity of the organisms in the left list, is their common denominator? Something which cannot be present in any of the elements in the nonliving list? The answer is: self-maintenance via a mechanism of self-regeneration from within. Life is a factory that makes itself from within.

reductionism, then, is fine when it limits itself to structure and composition. Emergence assumes its real value at the level of properties, and its very notion is based upon the proposition that the emergent properties cannot be reduced to the properties of the parts.

the product of an autopoietic system is its own self-organization.

life, more precisely, may be seen as a system of interlocked autopoietic systems.

“What is life?” and “What is cognition?” are the two main questions in the agenda of the Santiago school.

According to the theory of autopoiesis, a living system relates to its environment structurally – that is, through recurrent interactions, each of which triggers structural changes in the system.

the structure of the environment cannot specify changes; it can only trigger them.

From these generalizations emerges the important insight that social networks exhibit the same general principles as biological networks.

The observation that the “bio-logic,” or pattern of organization, of a simple cell is the same as that of an entire social structure is highly nontrivial. It suggests a fundamental unity of life, and hence also the need to study and understand all living structures from such a unifying perspective.

in the autopoietic mechanism there is an invariant property, and this is the autopoietic self-organization of cyclic production of components and systems processes that make such components

a variable property, which is the actual structure that can vary from cell to cell, and from one individual to another, depending upon the actual structure of the cell organisms and other circumstances, of which aging is one.

What, then, are the criteria for autopoiesis? Generally, the simplest criterion is to see whether the system is capable of sustaining itself due to self-generating processes taking place within its boundary, the boundary being of its own making.

Thus, death, seen in this way, is a progressive process, and corresponds to the destruction of the emergent properties of the various levels characterizing the complexity of the entire organism.

“neg-emergence”

the living organism is characterized by biological autonomy

Mentioning that the atmosphere that we all breathe was not on Earth before living organisms,

[T]here is no “environment” in some independent and abstract sense. Just as there is no organism without an environment, there is no environment without an organism. Organisms do not experience environments. They create them. They construct their own environments out of the bits and pieces of the physical and biological world, and they do so by their own activities.

In this process of “enaction,” a term proposed by Varela (Varela, 2000), or co-emergence, as we can say more generally, the organic living structure and the mechanism of cognition are two facets of the same phenomenon of life

Life is the synergy of the three domains, as the notion of the “embodied mind” implies.

Mind is always present in a bodily structure; and, vice versa, a truly living organism must be capable of cognition (the process of knowing).

Consciousness is not a transcendent entity, but it is always manifest within an organic living structure,

the principles underlying life are the same at all levels.

the interaction between the living organism and the environment is a dynamic one based on co-emergence, where the living organism and the environment become one through cognitive interactions. Within cognition we have recognized the notions of recursive structural coupling and structural determination, which relate to biological evolution. In this way the “trilogy of life,” expressed in Figure 7.6, acquires a dynamic and historical perspective.

Indeed, the most interesting self-organizing systems, including many centrally important to the life of the cell, are dynamic; that is, they are nonequilibrium systems that form their characteristic order while dissipating entropy.

The term “emergence” refers to the arising of novel properties of the organized structure, novel in the sense that they are not present in the parts or components.

There are two remarkable aspects of this process: first, the spontaneous formation of local order, attended by an overall increase of entropy (or disorder), and second, the formation of spherical compartments

“islands of order in a sea of disorder” are characteristic of the “dissipative structures” of living systems.

The folding of actin and of myosin, as well as several other examples given until now, are cases of processes under thermodynamic control, where the product forms because it is more stable than the starting components.

There are also cases of kinetic control, in which the products form because the reaction velocity to arrive at them is much larger than the velocity to arrive at the more stable products.

In the language of chemistry, the activation energy barrier (the energy barrier that must be overcome for a chemical reaction to occur) is much lower than the energy barrier to arrive at the thermodynamically more stable forms. This is why the products under kinetic control form preferentially.

Emergent properties are the novel properties that arise when a higher level of complexity is reached by putting together components of lower complexity. The properties are novel in the sense that they are not present in the parts: they emerge from the specific relationships and interactions among the parts in the organized ensemble.

Emergent properties can already be observed in geometry, where a line can be seen as emerging from the motion of a point, a two-dimensional surface from the motion of a line, and so on. At each level of complexity, novel, emergent properties arise – angles, surface, volume, etc. – which are not present at the lower level.

life itself is an emergent property.

none of the basic constituents of a living cell – nucleic acids, proteins, lipids, polysaccharides, etc. – are alive by themselves. But when they all come together in a particular space/time situation, life – the ultimate emergent property – arises.

each bee appears to behave as an independent element, acting apparently on its own account, but the whole population of bees produces a highly sophisticated structure emerging from their collective activities.

The systems view of life takes a third position, asserting that there is no need to assume any mysterious force to explain emergent properties, but that the focus on relationships, patterns, and underlying processes is essential.

As shown in Figure 9.6, the upward stream of emergence goes from the genes to the proteins, and on to the tissues, organs, and the organism – the genes being the primary cause of this upward stream.