Biocomplexity at all Levels of Biological Organisation

This theme contains the central application of our thinking: to explain how life as a general phenomenon, independent of the scale we look at it, is a kind of information processing. In recognising that life’s information is embodied as functional complexity and using information theory to understand how this naturally builds a hierarchy of functional levels (see here) in which each of life’s defining phenomena play out, we emphasise the unity over scales and through time. The rules generating complexity apply continuously from atoms to whole ecosystems and integrate life with the wider universe of information dynamics. In a fundamental sense, found through an information-theory perspective, life as a whole is seen to be a single process, much elaborated by its inherent complexity. But complexity is not a vague description of diversity and intricacy here: it has a formal and functional definition which supports a deep and robust theory of life and its place in the wider universe.

The idea that information is essential to life is familiar, but has been largely confined to the molecular scale (considered in depth by the Molecular Biology theme. Here we extend the concept that life is an information phenomenon to apply at every level of organisation, from molecules to the global ecological system. Our synthesis arrives at the conclusion that living is information processing: the transformation of information by logical operations, together with its transmission (in communications and reproduction) and storage. Memory is maintained by both molecular states and ecological states as well as the more obvious nucleic acids; more generally, information is stored by life by embodying it in structure at multiple scales of organisation, from the shape of biomolecules to the networks of interaction among the populations of an ecosystem. the two main means life uses to process information are filtration (as in cognition) which selects by context and synthesis, especially combining information at lower levels of organisation to appear at higher levels in complex systems (emergence).  This information processing has one overall function: it is to perpetuate itself as that is the ultimate function of life.

Life’s information is instantiated as pattern in form embodying living structures, such as molecular and cellular structures.  The corresponding pieces of information are  combined by the creation of mutual context among forms: one form ‘means’ something to another such that a process may take place when they encounter one another (for example when a hormone meats its receptor). This context results in apparently new information, but it is not in fact new, it is ‘revealed’ by the process as an emergent property of the system. This constructive process forms arbitrarily large complexes of information, the combined effects of which include the functions of life.

In terms of a computer analogy, life is both the data and the program and its biochemical structure is the way the information is embodied. A cell can be seen as a set of algorithms running on biochemistry; an organism as a set of algorithms running on a community of cells and an ecosystem as a set of algorithms running on a community of organisms. This idea supports the seamless integration of life at all scales with the physical universe.


There are by now, many different definitions of complexity. Frances Haylighen recognises "a common, 'objective' core in the different concepts of complexity" (Haylighen 1996).
He says: "Let us go back to the original Latin word complexus, which signifies 'entwined', 'twisted together'. This may be interpreted in the following way: in order to have a complex you need two or more components, which are joined in such a way that it is difficult to separate them. Similarly, the Oxford Dictionary defines something as 'complex' if it is "made of (usually several) closely connected parts". Here we find the basic duality between parts which are at the same time distinct and connected. Intuitively then, a system would be more complex if more parts could be distinguished, and if more connections between them existed."
This idea is especially relevant to living systems, which are readily interpreted as assemblies of different parts interacting through connections, many of which represent mutual dependencies, collectively making up a functioning whole. It is especially important to realise that this model applies equally well to the whole range of levels in biological organisation: from interactions among molecules, up to interactions between living processes and the non-living earth-systems for which the Gaia hypothesis is a potential explanation.

The most significant feature of complexity, for our understanding of life, is its ability to generate emergent phenomena. These are processes and features of a complex system that cannot be understood or predicted from a study of the component parts alone. They seem to create new information out of nothing (hence 'emergent'), but the information is actually already there, instantiated in the mutual context that makes the connections among the components functional. We say more about emergence here, explaining how epiphenomena arise from information structures providing mutual information for one another.

There are two aspects of complexity. one is the 'richness' of relationships (entwinement): the  inter-connectedness of the component parts, supremely elaborated in the brain, of course, but also in ecological communities: it is what Darwin referred to as a "tangled bank". The other aspect of complexity is the number and variety of different kinds of components that, so entwined, make up the whole. This number and variety is measured by diversity and in the biological context, that is of course biodiversity. That is why biodiversity has been given a theme within this project, and we should note that it is not just the number of species, but the number of all system components, including for example genes. In our interpretation it also  quantifies the extent to which component parts are different and it includes the complexity of interconnections as well. In order to combine all these aspects of complexity, we need a common currency (so as to avoid adding 'apples and oranges'). Not surprisingly, we believe the most promising common currency to be information (as defined here).

This Theme seeks to:

The Theme is led by
Dr Keith Farnsworth