What is our model of risk in biology?
Traditionally, outside of the general theory of the evolution of ecologies and population genetics, theoretical biology has arguably focused on, either rather specialised, or else overly theoretical, problems of risk. For example, theories still vie to explain the 'riddle' of the evolution of eusocial organisms like ants, a species where many individuals sacrifice their ability to reproduce (which seems risky) in favour of supporting the genes of their relatives. This quandary over ants evolved to be this way has been used to question the whole theory of how risk is handled by evolution under natural selection.
Additionally, under the specialised theoretical framework of 'game theory' we also now have a substantial body of literature on the intricate dances involved in mating, courtship and rivalry, of larger organisms. This literature appears relatively unusual in terms of the overt overlap of risk in biology with mainstream economic theory. This overlap occurs because of the same themes of problems of reliable communication occur in both domains. Game theory predicts that communication between rivals, or potentially cooperative mates, needs to be costly to the communicator since there is an incentive for agents/animals to deceive one another about their actual value/fitness. This is an example of what is known in economics as the 'agency problem', more of which later. The game theory of 'Costly signalling' summarises the idea and is exhibited in the evolution of peacock's feathers: We can show that male peacocks must incur a costly energetic penalty for producing fine feathers for courtship display. This cost ensures the lustre of their feathers then remains a reliable guide for the female of a male's fitness. In other words the information content is the cost of the producing the message while the 'message' itself is rather meaningless.
Group selection versus individual selection
The theories just mentioned, ant cooperation and costly signalling, may seem relatively isolated from mainstream evolutionary theory and isolated also in terms of their domains in biology compared to the subject as a whole. But in fact, they both feature in a debate from the 1960's onwards about evolution of groups versus individuals which attempted to revise the whole theory of natural selection. In the case of mating and game theory, 'group selection' supposedly favoured the evolution of male ritualised fighting (e.g. stag fights) which would prevent too much damage to each individual as they competed for the right to mate. In ants, of course, group selection was also seen as a potential explanation as to why individuals in the colony are produced without the capacity to reproduce as individuals. The question of whether group selection plays a part in evolutionary theory now seems reasonably settled after these extensive debates. It turned out in favour of the more conservative view that group selection doesn't exist, or is at least actually an inconsistent concept because, essentially, of the agency problem. Lot's of behaviour that might seem like group selection at work can be explained using game theory which doesn't assume any group selection at work. Yet, despite this, the same old arguments are being 'rehearsed' by a new generation involved in studying evolution of communication between different species of bacteria, quite often without incorporating the progress made in the previous few decade's literature.
The agency problem
These broader kinds of problems of selection can be understood from the perspective of 'agency': Where is the incentive for an agent to promote the interests of a group against their own self-interests? Can an agent represent the interests of a group him/herself? The risk to an individual who contributes to the good of the group is of being 'cheated' by other agents who don't contribute as much, often known as 'free-loaders' in economic literature. In general, the lack of 'agency' in the group itself is called the 'agency problem', and relates to the fact that while it may be in everyone's interests to coordinate better as a group, this can't happen by magic. We need a theory about how long-range coordination of behaviour (both temporal and spatial) can actually occur, and what the difficulties of this really are under natural selection, i.e. incorporating a solution to the agency problem. Looking at this issue in terms of specific empirical problems of risk management can help to advance and generalise theories of risk management in biology. However, I believe that the continued preoccupation by some new variant of the old dichotomy of 'group selection versus individual selection' may be obscuring more fruitful ways of proposing solutions to the agency problem in biology.
Mathematical innovation on risk management is crucial to empirical progress in 'risk biology'
Biological systems are concerned with risk far beyond the isolated examples discussed so far and so new research can help to take us beyond sterile discussions about the theory of evolution as an abstract concept. Indeed, recent research in microbiology makes it clear that new models of risk are really needed to genuinely understand some rather pervasive empirical problems in biological systems at the cellular level. In fact, the research picture today demands that risk management in biology is developed to address a number of outstanding empirical questions. Some of these empirical questions now also seem tailor-made for innovating not only in the maths of biology but also in our models of risk management in economics. This is an argument for putting the two disciplines together to bear a combined (hybrid) fruit. One example comes from my last blog post where I touched on the relevance of 'viability' and 'sustainability' as a problem in biology. Yet even more vital than the overlap in current concerns in economics with concerns in risk biology is the overlap in the type of solutions biological systems appear to have adopted in response to risk problems. At the heart of these solutions at the cellular level are extensive communications systems and systems of exchange. In other words, we now know that biological systems are solving resource allocation problems as coordination problems using a myriad of communications, even between unrelated species, (in the case of biofilms and prokaryotic communities).
Microbiology encounters generalised risk problems of coordination
Economics is at heart a social science related to coordination problems between agents. Consequently, one would not expect that much crossover with biology if instances of coordination problems in biological systems are relatively isolated, e.g. confined to courtship and mating, 'programmatic' developmental biology and eusocial organisms like ants. Yet it turns out that many other areas of biology explicitly involve coordination problems and, crucially, also employ 'social' solutions to these coordination problems.
Microbiology
Some of the 'hottest' research in communications in nature is in microbiology. Metazoan cells were already known to have complex signalling systems to coordinate behaviour such as cell differentiation and developmental processes and more and more signalling systems are now being discovered in this class of organism. In addition to this, it turns out that so-called *simpler* systems such as bacteria also address complex coordination problems to manage resources and create public goods. Biofilms often consist of different species working together to process nutrients and recycle resources. As an example of solving a complex coordination problem, researchers describe how by exchanging electrical signals, two Bacillus biofilms can “time-share” nutrients. Consider, for example, this accessible Quanta article and the work of researchers in to the existence of electrical signalling pathways between different biofilms. Recent work on eletroactive biofilms also shows how infrastructure ('nanowires') can be built across the biofilm community to harvest energy and distribute it to lower layers of the biofilm which provide other services in return. This type of scenario has been found in biofilms in hot springs. Here is a review of some of this research.
Your teeth are a place where communities (and so solutions to coordination problems) thrive
As an example of bacteria communities, the biofilms you know as tartare and plaque on your teeth are actually a complex community of a variety of species that can work together to produce public goods such as the hard tartare that builds up to protect them from removal. The resilience of these bacteria to cleaning is a result of the ability of these diverse microbes to work together and produce public goods that they all benefit from, such as tartare, but how do they avoid 'free-loading' mutations which no longer contribute to the public good? This is essentially an out-standing economics agency problem, re-stated in terms of microbiology. In general biofilms are a subject of much theoretical research to understand their general resistance and stability, and the emergence of the cooperative systems that appear to develop under evolutionary selection even under the tension of agency problems. (Much of this research is driven by the need to understand how to control biofilms and to deal with the rapid evolution of biofilm resistance to anti-bacterial drugs).
Here is a small sample of just some of the areas in which coordination problems are being solved via complex signalling and communications (known as signal transduction or 'ST') systems in microbiology:
Social behaviour and collaborative decision-making
'Social' signalling (quorum sensing) and the debates about how to understand how seemingly 'pro-social' behaviour fits in to the agency problem of evolution under natural selection is alive and well at the cellular level of biology. This time the data promises to be more decisive in advancing theory.
Kyle L. Asfahl, Martin Schuster; Social interactions in bacterial cell–cell signaling, FEMS Microbiology Reviews, Volume 41, 2017, Issue 1, Pages 92–107, https://doi.org/10.1093/femsre/fuw038
West, S. A., Griffin, A. S., Gardner, A., & Diggle, S. P; Social evolution theory for microorganisms. Nature reviews microbiology, 2006. 4(8), 597.
Exchange
Newly discovered exchange mechanisms is another burgeoning area of research which clearly overlaps with economic concepts; nanotubes, vesicles and horizontal gene transfer (e.g. viruses, and virus like gene transfer) are all revising our understanding of the variety of depth of exchange mechanisms at a cellular level in both eukaryotes and prokaryotes. See, this Quanta article for an introduction.
Systems biology using information theoretic approaches
At the same time, research methods in biology are starting to align themselves more with traditional research modes in economics. The main driver for this is more sophisticated imaging and other methods that allow us to quantify the information exchange occurring between cells and systems. See this review for example and the example of bet hedging:
Levchenko, Andre, Ilya Nemenman; Cellular noise and information transmission, Current opinion in biotechnology Volume 28 2014, Pages 156-164, https://doi.org/10.1016/j.copbio.2014.05.002
Beaumont, H. J., Gallie, J., Kost, C., Ferguson, G. C., & Rainey, P. B; Experimental evolution of bet hedging. Nature, 2009 462 (7269), 90.
Slime moulds and political economy
Political economy problems are also alive and well in slime moulds.
Latty, Tanya, and Madeleine Beekman. "Irrational decision-making in an amoeboid organism: transitivity and context-dependent preferences." Proceedings of the Royal Society of London B: Biological Sciences 278.1703 (2011): 307-312.
Summary of richness of micro-biological communications
So, to summarise, just as in economics, coordination problems in microbiology form the heart of the science of efficient resource allocation. Biologists are discovering that coordination problems are resolved in nature using extensive communications and signalling as well as the development of complex shared infrastructure. These solutions are in fact ubiquitous rather than niche issues in biology as once might have been thought. In prokaryotes such communication infrastructure is evolving in often diverse communities of species which also enjoy a web of mutually beneficial relationships that are also inevitably in tension with private interests. Taken together, this evidence suggests we can expect some convergence in models of risk in economics and biological systems and, indeed, we are already seeing the beginning of inter-disciplinary research between economics and biology such as the slime mould paper (and others I could mention). I predict that this convergence will be essential to resolve how these microbiological communities can remain stable under the stresses of evolutionary innovation and the agency problems that beset all systems whether human economies, eusocial ants, mating peacocks, or, more fundamentally (in evolutionary terms), coordination problems between competing and cooperating individual cells and genes.
But new mathematics likely needed
The use of these existing models based on current theories is different to prior work on more isolated examples from previous decades (such as signalling for mating individuals or rivals); Rather than simply borrowing from existing models in economic theory new mathematics is likely to be needed. This is partly due to the more 'alien' domain that we are working in at a microbiological level when compared to traditional economic domain of the humans species and its means of exchange. But that also offers the chance to make radical empirical discoveries to align with the new mathematics. Radically new, yet rigorous, models backed by new empirical data are arguably something that economics as a profession has traditionally been rather starved of. Consequently, in my next blog, in 1 or 2 week's time, I will be introducing a framework that I am developing to sketch out a new applied mathematics of risk in biology which I am actively working on with Andrea Fantuzzi, Research Fellow in department of Life Sciences at Imperial College. I will also discuss some problems in organisational economics and biological empirical research to illustrate the work I have done in this area. I will be sharing the details of the theory outputs I have developed using this framework over the coming year and will aim to blog once every 2-3 weeks with discussions of the theory, illustrations via empirical problems, and so on. This work will be combined with active work in organisational economics to produce a hybrid theory of how coordination problems are solved under the agency problem. In other words, watch this space for more details! I believe that new economics will likely come from the study of biofilms and similar communities. Just think about that next time you brush your teeth!