Highlighted Publications (K.D. Farnsworth)
(I give a very short explanation of the most relevant ones. For a full list of publications, please consult Google Scholar)Here are the main papers on IFB subjects
Homeostatic set-points are physical and foundational to organism
autonomy
K. D. Farnsworth (2025) BioSystems, 105634.
Explains how the set-point is coded
in DNA, translated into molecular forms and transformed via
emergence into the control characteristics (enzyme kinetic
properties and reaction network topology) of a homeostatic system,
especially using allosteric control -- in every cell.
How Physical Information Underlies Causation and the Emergence of
Systems at all Biological Levels
K. D. Farnsworth (2025) Acta Biotheoretica, 73 (2), 6..
Distinguishes between physical,
formal and statistical (Shannon) information, shows physical
information is necessary for physical (efficient) cause and
explains how information embodied at different organisational
levels produce emergent properties, with examples from
neuroscience and ecology.
How biological codes break causal chains to enable autonomy for
organisms
K. D. Farnsworth (2023) BioSystems, 232.
Biological codes (e.g. genetic) do
far more than translate from one medium to another. They enable
biological systems to control whether physical information is
causal or not. This paper established the description of
information embodiment in concrete terms of medium, basis and
scale. It shows how transducers work to strip off the force
component of physical cause, leaving only information. This is the
way biological systems break from strict cause-effect chains,
otherwise mandatory for physical systems.
Why it hurts: with freedom comes the biological need for pain
K. D. Farnsworth and RW Elwood (2023) Animal Cognition, 1-17.
Pain is not a signal, it is the
product of a neurological system that integrates cognition of
nosiception (noxious stimuli) with hormone-based evaluation for
action selection (response). Pain is the qualitative feeling
generated by the network-wide result of this integration. It is a
mental command to attend to the source of the feeling and only
justifiable for organisms that have a) alternate options for
response and b) an anticipatory evaluation system with which to
choose. This is an advanced application of control by information.
How
an information perspective helps overcome the challenge of biology
to physics
K. D. Farnsworth. (2022) BioSystems 217. 104683.
Distinguishes between physical,
formal and statistical (Shannon) information, shows physical
information is necessary for physical (efficient) cause and
explains how information embodied at different organisational
levels produce emergent properties, with examples from
neuroscience and ecology.
An organisational systems-biology view of viruses explains why
they are not alive
K. D. Farnsworth. (2020) Biosystems 200. 104324.
Whether or not viruses are alive
depends on what we mean by life. I took an organisational view -
life is an information process that necessarily involves closure
to efficient causation (following Rosen's definition) and since no
virus has that property, they are not alive. In this paper, I
developed my ideas on formal and physical causation and their
dependence on, respectively, different kinds of information.
How
organisms gained causal independence and how it might be
quantified
K. D. Farnsworth. (2019). Biology 7 (3), 38.
Identifies agency with agent
causation and specifies the physical requirements for any system
to have that property (only organisms qualify). Builds a nested
hierarchy of control loops, with basic homeostasis at the core
(level 1). Working outward: (2) perception-action systems; (3)
action selection systems; (4) cognitive systems; (5) a self-model
able to anticipate and evaluate actions and consequences. Each
higher level is associated with a step up in causal independence.
Using a mathematical framework to describe this, suggests
Integrated Information Theory (IIT) as a means to quantify causal
independence, which has generally increased through evolutionary
developments identified by the levels of the hierarchy.
Unifying
concepts of biological function from molecules to ecosystems
KD Farnsworth, L Albantakis, T Caruso. (2018). Oikos 126 (10),
1367-1376
Defines function by causal role:
function is a process performed by a component that is necessary
for the performance of a higher level process by the system of
which it is part (adapting Cummins, 1975). Uses the idea of a
nested hierarchy of physically causal systems, from molecular
interactions up to the entire global ecosystem. Function is a
teleonomic term that can only make sense in the context of closure
to efficient causation. A numerical worked example is provided and
the overall 'master function' of biological systems is identified
as biomass accumulation.
Can
a Robot Have Free Will?
KD Farnsworth. (2017) Entropy 19 (5), 237.
Of course 'robot' originally meant
slave, so the answer could be trivially - no. But more
substantially, I used this paper to understand the scientific
explanation for free will to exist at all (some scientists believe
it to be impossible). It was here that I first applied Rosen's
concept of closure to efficient causation (c.l.e.f.), reasoning
that for free will to be meaningful it had to arise from agent
causation. The paper shows that agent causation can only arise
from a system with c.l.e.f. - in particular, since machines cannot
(yet) make themselves, they do not have that property and so fail
at least one of the necessary criteria for free will. Living
systems do pass this test.
Living
through Downward Causation
Farnsworth, K.D., Ellis, G.F.R. and Jaeger, L.(2017). Ch.13. in From
Matter to Life. (Eds. Walker, S.I., Davis, P.C.W. and Ellis, G.F.R.).
Cambridge University Press.
Introduces readers to the idea of
functional information at multiple hierarchical levels of
organisation - the cybernetic structure of living systems. Several
examples illustrate how downward causation emerges and operates to
effect the process of living, based on the developments reported
in the 2013 Acta Biotheoretica paper.
Living
is Information Processing: From Molecules to Global Systems
Farnsworth, K.D., Nelson, J., Gershenson, C. (2013). Acta
Biotheoretica 62(2): 203-222.
Introduces information as a pattern
of difference and shows how this can be causal through mutual
effects of one pattern on another. Then multiple instances of this
can form emergent systems; some capable of computation. Life is a
nested hierarchy of these information complexes and it computes
itself, using molecular interactions as the 'hardware': molecules
embody the information for computation in their structures and
life is the algorithm that computes itself. The 'hard' emergence
implied by this hierarchical computation is shown to be physically
plausible (countering Kim's exclusion argument) because it is
nothing more than information appearing at higher organisational
scales - an idea formalised in later papers (especially Farnsworth
2025, Acta Biotheoretica).
Functional Complexity: The source of value in biodiversity
Farnsworth, K.D., Lyashevska, O., Fung, T.C. (2012). Ecological
Economics 11: 46–52.
Having established that biodiversity
is information (total difference among organisms) and that at
least some of this information is functional (defined in
Farnsworth et al. Oikos 2018), its value derives from the
ecological function that functional information content (FIC -
Szostak, Nature 2003) affords. Ecological function was defined as
stable community biomass production rate and measured for a
complete set of hypothetical communities composed from subsets of
a complete simulated community. Community complexity was measured
by FIC/AIC (algorithmic information) and 'function' by stable
biomass production in a quantitative implementation of the Noah's
Ark problem, based on an ecological model of marine communities
with growth, predation and recruitment. The result was an
information metric for quantifying biodiversity-ecosystem function
relationships, illustrated empirically (on model systems). Very
roughly, the more complexity (FIC/AIC) the more function, but
subject to a law of diminishing marginal returns.
Lyashevska, O., Farnsworth, K.D. (2012)
How many dimensions of biodiversity do we need? Ecological
Indicators, 18: 485-492.
Biodiversity includes phylogenetic
and community composition and not only the count of differences,
but the aggregate degree of difference - all amounting to
information embodied in the ecological community. Hierarchical
cluster analysis of a multitude of biodiversity indicators reveals
three canonical axes of diversity. This work consolodated the idea
of biodiversity as embodied information.
Some other ecology
K.D. Farnsworth, A.H. Adenuga, R.S. de Groot. (2015). The complexity of biodiversity: A biological perspective on economic valuation. Ecological Economics. (on line).
Focardi, S., Farnsworth, K.D., Poli, B.M., Ponzetta, M.P., Tinelli, A. (2003). Sexual segregation in ungulates: individual behaviour and the missing link. Population Ecology, 45: 83-95.
Farnsworth, K.D., Focardi, S., Beecham, J. (2002). Coexistence and facilitation of animals from grassland-herbivore interactions. The American Naturalist, 159: 24-39.
Farnsworth, K.D., Anderson, A.R.A. (2001). How simple grazing rules lead to reaction diffusion systems and their consequence for vegetation community dynamics. Oikos, 95:15-24.
Ruxton, G.D., Humphries, S., Farnsworth, K.D. (2001). Non-competitive phenotypic differences can have a strong effect on ideal free distributions. Journal Of Animal Ecology, 70: 25-32.
Beecham, J.A., Farnsworth, K.D. (1999). Animal group forces resulting from predator avoidance and competition minimisation. Journal of Theoretical Biology, 198: 533-548.
Farnsworth, K.D., Beecham, J.A. (1999). How do grazers achieve their distribution? A continuum of models from random diffusion to the ideal free distribution using biased random walks. American Naturalist, 153: 509-526.
Farnsworth, K.D ., Illius, A.W. (1998). Optimal diet choice for large herbivores: an extended contingency model. Functional Ecology Vol. 12. pp74-81.
Farnsworth. K.D., Beecham, J.A. (1997). Beyond the ideal free distribution: a more general model of predator distribution. Journal of Theoretical Biology, Vol. 187. pp 389-396.
Farnsworth, K.D., Niklas, K.J. (1995). Theories of optimisation form and function in branching architecture in plants. Functional Ecology, Vol. 9. pp 355-363.
Some related marine biology
Fung, T. Farnsworth, K.D. Reid, D.G.and Rossberg A.G. (2015).
Impact of biodiversity loss on production in complex marine food webs
mitigated by prey-release. Nature Comms. 6. 10.1038/ncomms7657
Houle, J.E., Andersen, K.H., Farnsworth, K.D., Reid, D.G. (2013). Emerging asymmetric interactions between forage and predator fisheries impose management trade-offs. J. Fish Biology. Online: 10.1111/jfb.12163