Dr Keith D. Farnsworth 
Reader in
Theoretical Biology (retired)School of Biological Sciences,
Queen's University Belfast
United Kingdom.
Email: k.farnsworth (at) qub.ac.uk
BSc. (Hons) Astrophysics, University of London 1984
MSc. Acoustics, Southampton, 1985;
PhD. Mathematical Biology, Edinburgh 1994
MSc. Public Health Epidemiology, Aberdeen 2002
Here is a list of highlighted Publications The full set is available on Google Scholar
Also on ResearchGate, of course.
For a bit of nostalgia, please take a look at my Research Team page - those were the days!
About me:
I am a theoretical biologist, last employed by the Queen’s University Belfast (from which I retired in 2024). Counter to the current fashion for applied research led by anxious funding agencies, I am trying to develop as deep as possible an understanding of what life is and how it works (in a material universe) [1]. Over the past 24 years, though, I have been active in marine biology, helping create the size-spectrum approach to fisheries ecology, with applications in sustainable fisheries management and the 'ecosystem based approach' to the same, culminating in contributions to the 'Real-time incentive' scheme of fisheries regulation and co-management plans for artisan fisheries in Egypt. Before that I worked on the behavioural ecology of large mammalian grazers, showing how they can coexist in the wild, matching their distribution to the resources available using multi-scale biased diffusion. Before that I worked on optimality theory for branched systems such as trees and even before that, I was briefly involved in medical physics, helping to develop the MRI scanner and some aspects of doppler ultrasound scanners. Somewhere in the middle of all that, I got interested in medical epidemiology and public health medicine - it remains a sort of side-line (that proved more frustrating than useful during the Covid pandemic).A lot of my previous work was more or less motivated by employers and funding agencies. Now, as I say, I am using my time to concentrate on what I am personally motivated by; because it is where I think I can make the most profound contribution. These deeper theoretical enquiries led from information theory and cybernetics, to causation and what has been termed ‘the organisational approach to biological systems’. On the way, I have proposed a modernisation of Aristotle’s four aspects of cause, especially identifying formal cause with information embodied in the pattern of matter and interpreting efficient cause as the empowerment of formal cause with physical force [2, 8]. So far that is proving very useful in constructing explanations for biological phenomena of fundamental interest [3, 4, 5, 6]. The organisational approach helps us understand why organisms are special in the sense of causation and agency [3, 7, 9] and is certainly open to philosophical approaches. The central idea is that of closure to efficient causation: unique to organisms and without which, agency cannot be attributed. Life remains a great mystery and I see it as the most fascinating and marvellous thing in the universe. A lot of the pioneering work (e.g. by Rosen, Varela and Maturana, Kauffman, Pattee and many others) has necessarily been quite abstract, but recently people like Jannie Hofmeyr and Marcello Barbieri have built much more biochemical realism into our explanations. At the moment my contribution seems to be to develop a link between these and the physics and information theory that describes its physical underpinning. It's an exciting ride - for those that like that sort of thing.
[1] Farnsworth, K.D., Nelson, J., Gershenson, C., 2013. Living is information processing: From molecules to global systems. Acta Biotheor. 61, 203–222. doi:10.1007/s10441- 013-9179-3.
[2] Farnsworth, K.D., 2022. How an information perspective helps overcome the challenge of biology to physics. BioSystems 217, 104683. doi:https://doi.org/10.1016/j. biosystems.2022.104683.
[3] Farnsworth, K.D., 2018. How organisms gained causal independence and how it might be quantified. Biology 7, 38. doi:10.3390/biology7030038.
[4] Farnsworth, K.D. and Elwood, R.W. 2023. Why it hurts: with freedom comes the biological need for pain. Animal Cognition, 1-17. doi:10.1007/s10071-023-01773-2.
[5] Farnsworth, K.D., Albantakis, L., Caruso, T., 2017. Unifying concepts of biological function from molecules to ecosystems. Oikos 126, 1367–1376. doi:10.1111/oik.04171.
[6] Farnsworth, K.D., 2021. An organisational systems-biology view of viruses explains why they are not alive. BioSystems 200, 104324. doi:0.1016/j.biosystems.2020.104324.
[7] Farnsworth, K.D., 2017. Can a robot have free will? Entropy 19, 237. doi:10.3390/ e19050237.
[8] Farnsworth, K.D., 2025. How Physical Information Underlies Causation and the Emergence of Systems at all Biological Levels. Acta Biotheoretica 73 (2), 6.
[9] Farnsworth, K.D., 2025. Homeostatic set-points are physical and foundational to organism. Biosystems 105634.
(You can get more detail on my publications here)
More on my research activity
What is Life?
My expedition into biological information and function started with thoughts about biodiversity. Rather than taking it for granted that this had to do with the number of species in a community, I sought to quantitatively define what biodiversity really is. I realised ‘diversity’ meant degree of difference and that is mathematically equivalent to the quantity of information. But not information about the community, it was information that is physically embodied in its structure and form. So started an effort to quantify biodiversity in units of information: the sum of differences (i.e. complexity) in and among forms which physically embody the information [10,11]. Notably, biodiversity was a combination of genetic, functional and organisational diversity and the common factor among these was information- embodied at levels of organisation from molecular up to ecological. Indeed information turned out to be the essence of all living systems.
But life is not static information, it is constantly renewing, replicating and adapting: life itself, necessarily dynamic, must be information processing. Paralleling John Von Neumann's insight into self-replication, it can be said that life is computation and what it is computing is itself. It was obvious that not all the differences, e.g. among leaf shapes or the markings on a shark, matter. A lot of this detail was just random. What was needed was some quantifiable measure of functional information - loosely - that which causes a difference "that makes a difference" - to use Bateson's memorable phrase. w
The idea of biological function, with all its awkward teleological implications had not been resolved at that point, so with colleagues, I set about to establish a generally applicable definition. The best starting point for one consistent with phyisical principles was the 'functional role' account attributed to Cummins (1970). Formalised and set in a more concretely physical context, that became a definition [5] using two important concepts: a) the hierarchy of organisation in living systems (from atoms, thought cells and organisms, to ecosystems) and b) causation as the physical expression of physically embodied information.
To understand this concept, I needed to know what information did for, and meant to, living organisms. The result was a realisation that living itself is fundamentally a process of information processing, i.e. computing. Life is a cybernetic process: a set of logical rules acted out by molecular interactions, in total having the effect of self-replication.
But if living organisms are computing, what is it that they are working out? The answer came from Maturana and Varela’s theory of autopoiesis and Von Neumann's self-replicator theory : life is computing itself. That is a completely auto-reflexive cybernetic process and attempts to understand it led me to the theories of Robert Rosen and Stuart Kauffman. They captured self-making in the ideas of closure to efficient causation, autocatalytic sets and thermodynamic work cycles, but these remained rather abstract. More recent advances, e.g. by Jannie Hofmeyr and Marcello Barbierei have made the ideas more biologically grounded. But the role of information was still obscure and questions remained about whether closure to efficient causation and downward causation could exist at all (many scientists still believe they cannot).
The breakthrough came from realising that information, in general, constrained randomness by specifying the particular from among a random set of possibilities (diagram above: A random unconstrained; B simple strong constraint, as in a crystal; C more complicated constraint of interaction among molecules and D functional effect of dynamic morphological constraint in enzyme action, as in the 'lock and key mechanism').
Physically, life computing itself means that it constantly constrains the set of possible chemical reactions that take part within, to only that small subset which collectively and continuously re-make the organism. The computation is in and among the biochemical reactions (elements of analogue computing), most of which, just as in a digital computer, are controllable. The action of an enzyme can be switched on and off by reversible changes in its shape in response to a control signal and networks of such signals amount to a computer. Obviously, all talk of control implies constraint and thereby physical information. The value of information is the constraint it provides, selecting what is functional from all that is not.
To define function, we needed
[10] Lyashevska, O., Farnsworth, K.D. (2012) How many dimensions of biodiversity do we need? Ecological Indicators, 18: 485-492.
[11] Farnsworth, K.D., Lyashevska, O., Fung, T.C. (2012). Functional Complexity: The source of value in biodiversity. Ecological Economics 11: 46–52.
For those that are interested, here is a short description of other research work I been involved in.
Sustainable Fisheries Management
Fisheries science is an application of ecological theory to practical problems of current real-life importance. It is vital work if we are to save the world's fisheries from the global collapse to which many believe they are heading. A major part of this work is pursued through European Union and Irish Government funding in collaboration with the Danish Technical University. The main project was developing "An Ecosystem Approach to Fisheries Management". In general, my team and I used multispecies population dynamic models, including recruitment, growth and predation, the core of which (for most of them) was the McKendrick-VonFoerster equation (figure bleow). This work is also being used to create new theories of organism distribution, predator-prey dynamics, life history, and evolution.
Applications to Global Food
Security
Building an 'appropriate technology' management system for artisan
fisheries of the Egyptian Red Sea is the work of an Egyptian PhD student
that I most recently was supervising. It is interesting that this
contributes towards something that the ancient Egyptians of tomb
paintings, papyrus scrolls and pyramids would be quite at home with.
Being pioneers of administration and quantification, I am sure those
ancient Egyptians would approve of the `data limited stock assessment'
methods being deployed and the participatory management processes (they
were certainly not the autocratic tyrants we used to be misled into
thinking). It seems the fishery is over-exploited and declining, so
proper management is urgently needed for this ancient way of life to
survive.In a major collaboration, funded by Science Foundation Ireland, my team helped to devise an alternative to the stock quota system of the Common Fisheries Policy. This alternative is the Real Time Fisheries system, developed by Dave Reid (Marine Institute, Ireland) and Sarah Kraak (Thünen Intitut, Germany), who very sadly died of COVID-19 in 2021. RTI is a high spatial and temporal resolution quasi-economic incentive method which supplies real-time fine-grid tariff maps to operating vessels, using a lot of technology, data and sophisticated modelling.
Mathematical ecology
Before fisheries, I developed a theoretical understanding of how large mammalian grazing animals managed to co-exist in the wild and how the effectively distributed themselves to optimise their food resources (leading to some generalisations of the 'ideal free distribution' - a kind of spatial game theory result. On the way, I developed a modification of the foraging functional response for large mammalialn herbivores and this was taken up in several aquatic ecology works through collaboration with Prof. Jaimie Dick and colleagues. Even before that I worked out the optimal growth algorithm for the shape of botanical trees, did a bit of mathematical epidemiology and diagnostic imaging physics involving the UK's first clinical MRI scanner (for the Institute of Cancer Research).
