From
the Editors - When Bad Genetics Can Kill
Contrasting fortunes of two Nobel
laureate geneticists
James Watson, who shared the 1962
Nobel Prize for the double-helix
structure of DNA, sparked outrage among
fellow scientists for saying to a
newspaper reporter that he was
“inherently gloomy about the
prospect of Africans” and “all
our social policies are based on the fact
that their intelligence is the same as
ours, whereas all the testing says not
really.” That was not the first time
Watson abused his position to promote
what the Federation of American
Scientists condemned as “personal
prejudices that are racist, vicious and
unsupported by science”.
Previously, for example, he suggested
that people with low IQ had genes for
stupidity, and he would like to prevent
them from being born or give them gene
therapy (Why
Genomics Won't Deliver, SiS
26).
Within a week of his latest
transgression, Watson was suspended, and
subsequently resigned, from his post as
chancellor of the prestigious Cold Spring
Harbour Molecular Biology Laboratory.
Nonetheless, it was precisely such
eugenicist, genetic determinist
propaganda that Watson has used so
effectively in selling the Human Genome
Project back in the 1980s. And if
anything significant had come out of
sequencing the human and other genomes,
it was to explode the myth of genetic
determinism once and for all (see Living
with the Fluid Genome, ISIS
publication). Some of us had been arguing
all along that genes and environment are
inseparable well before the Human Genome
Project was conceived. The surprise is
how readily the environment could
specifically mark and change genes and
genomes to influence later generations.
‘The inheritance of acquired
characters’ is nowhere as evident as
in molecular genetics (see Life After the
Central Dogma series, SiS 24).
Another Nobel laureate (Nobel Peace
Prize 1970) who should know his genetics
better is Norman Borlaug, father of the
Green Revolution, a reductionist approach
to agriculture based on breeding
genetically uniform high yielding
varieties (HYVs) that has brought
short-term increases in crop yields at
tremendous environmental and social
costs.
Borlaug has persisted in promoting
this failed approach, especially in the
form of genetically modified (GM) crops,
as made clear in a recent Nature
editorial, “Feeding a hungry
world”.
Far from suffering disgrace, Borlaug
is showered with awards, the latest being
the US Congressional Gold Medal,
America’s highest civilian honour.
At the presentation event, M.S.
Swaminathan, father of the Green
Revolution in India, gave the keynote
address.
India meanwhile is caught in a
worsening epidemic of farmers’
suicide as the result of the Green
Revolution. Its agricultural minister
acknowledged in the Indian Parliament
that an estimated 100 000 farmers have
taken their own lives between 1993 and
2003; and the introduction of GM crops to
the country since has escalated the
suicides to 16 000 a year (Stem
Farmers’ Suicides with Organic
Farming, SiS 32).
Borlaug is doing a great deal more
damage to the world than Watson with
their bad genetics. The difference is
that while Watson is now seen as a
liability in attracting grants and
investments, Borlaug serves as ideal
mouthpiece for the biotech
industry’s fake moral crusade of
feeding the world.
Failures of the Green Revolution
widely acknowledged
The failures of the Green Revolution
are widely acknowledged. Swaminathan
himself referred to a Green Revolution
“fatigue”: a drop in yield, as
well as a sharp drop in the yield of
grain per unit of fertilizer applied.
The Green Revolution packaged
specially bredHYVs with fertilizers,
pesticides, and irrigation. And given
optimum inputs, these HYVs did indeed
increase yields dramatically, especially
in the short term. In the longer term,
the soils become depleted and degraded,
and yields fall even as more and more
fertilizers are used. Similarly, pests
become resistant to pesticides, and
greater amounts have to be applied.
Farmers and the general public become
increasingly at risk from the toxic
effects of pesticides and fertilizers
that contaminate ground water. At the
same time, heavy irrigation results in
widespread salination of agricultural
land, while aquifers are pumped dry.
The high costs of fertilizer and
pesticides put small farmers at a
disadvantage right from the start,
driving them off the land while big
farmers grow bigger, thereby deepening
the divide between rich and poor.
But even farmers who manage to keep
going are soon plunged deeper and deeper
into debt by the spiralling costs of more
fertilizers and pesticides, coupled with
falling income from reduced crop yields,
or massive crop failures from droughts,
pests and diseases to which the
genetically uniform HYVs are especially
susceptible. For many of these farmers,
the only exit from debt is suicide.
The Green Revolution’s success in
raising yields has blatantly failed to
reduce poverty or hunger. India’s 26
million tonne grain surplus in 2006 could
feed the estimated 320 million of its
people who are hungry, but starving
villagers are too poor to buy the food
produced in their own countryside.
The Green Revolution also led to the
loss of crop biodiversity, compromising
food security for small farmers and
increasing malnutrition for all.
Bangladesh lost nearly 7 000 traditional
rice varieties and many fish species. In
the Philippines, more than 300
traditional varieties disappeared.
Instead of learning from the failures
of the Green Revolution, Borlaug,
Swaminathan and the biotech industry are
offering the world a second ‘doubly
green’ revolution in GM crops, and
they are taking it to Africa.
Beware the Alliance for a Green
Revolution in Africa
Bill & Melinda Gates and the
Rockefeller Foundation announced a joint
$150 million Alliance for a Green
Revolution in Africa (AGRA) on the
grounds that the Green Revolution had
bypassed Africa. But as the Food First
Institute points out, the Consultative
Group on International Agricultural
Research, which brings together the key
Green Revolution research institutions,
has invested 40 to 45 percent of their
£350 million annual budget in Africa;
which shows that the Green Revolution
must have failed Africa, not bypassed it.
The Green Revolution failed Africa for
the same reasons it failed Asia and Latin
America: it did not address the causes of
poverty and hunger. On the contrary it
contributed to increasing hunger and
poverty in the midst of plenty.
Borlaug claims to have reduced hunger
in the world through the Green
Revolution, and even many of his critics
are willing to give him credit for that.
But this too, turns out to be a myth. In
the two decades from 1970 to 1990
spanning the Green Revolution, the total
food available per person in the world
rose by 11 percent while the estimated
number of hungry people fell from 942 m
to 786 million, a 16 percent drop.
However, if China is left aside, the
number of hungry people in the rest of
the world actually went up by more
than 11 percent, from 536 to 597 million.
Rural Africa has been devastated by 25
years of ‘free trade’ policies
imposed by the World Bank, the
International Monetary Fund, the World
Trade Organisation, the US and EU.
The forced privatization of food crop
marketing boards - which once guaranteed
African farmers minimum prices and held
food reserves for emergencies - and rural
development banks - which gave farmers
credit to produce food - left farmers
without financing to grow food and
without buyers for their produce. Free
trade agreements have made it easier for
private traders to import subsidized food
from the US and EU than to negotiate with
thousands of local farmers. This
effective dumping drives local farm
prices below the costs of production and
puts local farmers out of business.
Introducing GM monoculture crops will
further narrow the genetic base of
indigenous agriculture, increase
farmers’ indebtedness in paying for
patented seeds, and bring extra
environmental and health risks (see GM
Science Exposed., ISIS CD book).
Given appropriate land reform and
institutional support in finance and
marketing, there is no doubt that farmers
in Africa, India and elsewhere can free
themselves from the cycle of
indebtedness, increasing poverty, hunger,
malnutrition and ill-health, especially
with zero-input organic farming methods
based on indigenous crops and livestocks
(see How
to Beat Climate Change & Be Food and
Energy Rich - Dream Farm 2 also
Organic Now series, SiS 36). The
really green revolution has started in
Ethiopia a few years ago, when the
government adopted organic agriculture as
a national strategy for food security.
Crops yields have doubled and tripled
while reversing the damages of the failed
Green Revolution (see Greening Ethiopia
for Self-sufficiency series, SiS
23).
ISIS Press Release 21/09/07
Thermodynamics of
Organisms and Sustainable Systems
Invited lecture for conference on Environment,
Agriculture, Food, Health and Economy,
World Food Day, 17 October 2007, La
Sapienza University, Rome, Italy
Dr.
Mae-Wan Ho, Institute of Science in
Society, m.w.ho@i-sis.org.uk
A fully
referenced and illustrated version of
this article is posted on ISIS
members’ website. Details
here
An electronic version of this report,
or any other ISIS report, with full
references, can be sent to you via e-mail
for a donation of £3.50. Please e-mail
the title of the report to: report@i-sis.org.uk
Abstract
I have developed a
“thermodynamics of organized
complexity” based on a nested
dynamical structure that enables the
organism to maintain its organisation and
simultaneously achieve non-equilibrium and
equilibrium energy transfer at
maximum efficiency (Ho 1993, 1998a,
2007a).
The healthy organism excels in
maintaining its organisation and keeping
away from thermodynamic equilibrium
– death by another name – and
in reproducing and providing for future
generations. In those respects, it is the
ideal sustainable system (Ho, 1998b,c; Ho
and Ulanowicz, 2005). Looking at
sustainable systems as organisms provides
fresh insights on sustainability, and
offers diagnostic criteria that reflect
the system’s health.
This paper formalises and updates the
‘zero-entropy’ model of
organisms and sustainable systems, and
shows how sustainable development is
possible by explicit reference to a
‘zero-emission’,
‘zero-waste’ integrated food
and energy ‘Dream Farm 2’.
Key Words: Cycles,
coherent energy storage, space-time
structure, fractal dynamics,
sustainability, sustainable development,
minimum entropy production, internal
entropy compensation, circular economy
What is Schrödinger’s
negentropy?
Schrödinger (1944) wrote: “It is
by avoiding the rapid decay into the
inert state of ‘equilibrium’
that an organism appears so
enigmatic…What an organism feeds
upon is negative entropy. Or, to put it
less paradoxically, the essential thing
in metabolism is that the organism
succeeds in freeing itself from all the
entropy it cannot help producing while
alive.”
Schrödinger was struggling to make
explicit the intimate relationship
between energy and organisation. To make
progress, we need to see life with fresh
eyes.
By half accident, we discovered in my
laboratory in 1992 that all living
organisms display dynamic liquid
crystalline rainbow colours under the
polarising light microscope that
geologists use to look at rock crystals
and other birefringent materials (Ho and
Lawrence 1993; Ho et al, 1996;
Ross et al, 1997). The fact that
living moving organisms, with all their
molecules churning around transforming
energy could appear like a dynamic liquid
crystal display is evidence that living
organisms are coherent (organized) to a
high degree, right down to the alignment and
motions of the protein molecules in
their tissues and cells, and it is coherent
energy that is being mobilized and
transformed in the organisms (Ho 1993,
1998a, Ho et al, 2006b).
This spurred me on to reformulate
thermodynamics for living systems over
the past 15 years, the details of which
are presented in successive editions of The
Rainbow and the Worm, the Physics of
Organisms (Ho, 1993, 1998a, 2007a). I
shall recapitulate the main results and
bring this work up to date, as it has
large implications for the environment,
food, health and the economy, the themes
of our conference.
How organisms make a living
The first thing to take note is that
organisms do not make their living
by heat transfer. Instead, they are
isothermal systems (c.f. Morowitz, 1968)
dependent on the direct transfer of
molecular energy, by proteins and other
macromolecules acting as “molecular
energy machines”. For isothermal
processes, the change in Gibbs free
energy is,
DG
= DH
- TDS
(1)
Thermodynamic efficiency requires that
DS,
the change in entropy, approaches 0
(least dissipation), or DG,
the change in free energy, approaches 0
(free energy conservation or
entropy-enthalpy compensation) (Ho,
1995).
The organism as a whole keeps far away
from thermodynamic equilibrium, but how
does it free itself from “all the
entropy it cannot help producing while
alive”? That’s the point of
departure for the “thermodynamics of
organised complexity”.
The pre-requisite for keeping away
from thermodynamic equilibrium – the
state of maximum entropy or death by
another name – is to be able to
capture energy and material from the
environment to develop, grow and recreate
oneself from moment to moment during
one’s life time and also to
reproduce and provide for future
generations, all part and parcel of
sustainability.
The organism has solved its problems
of sustainability over billions of years
of evolution. It has an obviously nested
physical structure. Our body is enclosed
and protected by a rather tough skin, but
we can exchange energy and material with
the outside, as we need to, we eat,
breathe and excrete. Within the body,
there are organs, tissues and cells, each
with a certain degree of autonomy and
closure. Within the cells there are
numerous intracellular compartments that
operate more or less autonomously from
the rest of the cell. And within each
compartment, there are molecular
complexes doing different things:
transcribing genes, making proteins and
extracting energy from our food, etc.
More importantly, the activities in all
those compartments, from the microscopic
to the macroscopic are perfectly
orchestrated, which is why the organism
looks like a dynamic liquid crystal
display, as explained earlier.
An organism has physical barriers
separating the inside from the outside,
but never completely. It can be
questioned whether such physical closure
is necessary, at least as far as the
sustainable system is concerned. More
important than physical closure is dynamic
closure, which enables the organism to store
as much energy and material as possible,
and to use the energy and material most
efficiently, i.e., with the least
waste and dissipation (see above).
The key to understanding the
thermodynamics of the living system is
not so much energy flow (Prigogine, 1967,
Morowitz, 1968, and Ulanowicz,
1983) as energy capture and storage under
energy flow (Fig. 1). Energy flow is of
no consequence unless the energy can be
trapped and stored within the system,
where it is mobilised to give a
self-maintaining, self-reproducing life
cycle coupled to the energy flow. (By
energy, I include material flow, which
enables the energy to be stored and
mobilised.)
Figure 1.
Energy flow, energy storage and the
reproducing life-cycle
My approach
diverges significantly from the framework
established by earlier applications of
thermodynamics to ecology as described in
detail in Ho and Ulanowicz (2005).
Stored energy is distinct from exergy
as widely used by ecologists, and also
from free energy as defined by
chemists and physicists (see Eq. 1). It
is stored energy being mobilised in a non-classical
steady state that characterise living
organisms and sustainable systems, as
will be made clear below.
Cycles make sense
The perfect coordination
(organisation) of the organism depends on
how the captured energy is mobilised
within the organism. It turns out that
energy is mobilised in cycles, or
more precisely, quasi-limit cycles, which
can be thought of as dynamic boxes; and
they come in all sizes, from the very
fast to the very slow, from the global to
the most local.
Cycles provide the dynamic closure
that’s absolutely necessary for
life, perhaps much more so than physical
closure.
Biologists have long puzzled over why
biological activities are predominantly
rhythmic or cyclic, and much effort has
gone into identifying the centre of
control, and more recently to identifying
master genes that control biological
rhythms, to no avail.
The organism is full of cycles,
possibly because cycles make
thermodynamic sense. (Nevertheless,
Morowitz (1968) has proven an important
theorem that a flow of energy from a
source to a sink in a system at steady
state will lead to at least one cycle.)
Cycles mean returning again and again to
the same states, and no entropy is
generated in a perfect cycle. In other
words, the system as a whole remains
organized. Cycles give dynamic stability
as well as autonomy to the organism; and
this is apparently also the case in
ecosystems (Ulanowicz, 1983). Moreover,
cycles enable the activities to be
coupled, or linked together, so that
those yielding energy can transfer the
energy directly to those requiring
energy, and the direction can be
reversed when the need arises. This
is implicit in Onsager’s reciprocity
relationship which shows how symmetrical
coupling of processes can arise naturally
in a system under energy flow (see Ho,
1993, 1998a, 2007a). These symmetrical,
reciprocal relationships are most
important for sustaining the system. Our
metabolism is actually organised
precisely in that way: closing cycles and
linking up, with pathways that readily
reverses the direction of energy and
material flows.
Figure 2 is a diagram representing the
nested cycles that span all space-time
scales, the totality of which make up the
life cycle of the organism (Ho, 1998a).
The life cycle has a self-similar fractal
structure, so if you magnify each cycle,
you will see that it has smaller cycles
within, looking much the same as the
whole. Fractal dynamics are the hallmarks
of natural processes and are especially
fit for the organisation of living
systems (Ho, 2007a), as we shall see.
Figure 2.
The life cycle of the organism consists
of a self-similar fractal structure of
cycles turning within cycles
This complex nested dynamical
space-time structure of the organism is
the secret of sustainability. As
explained below, it maximises the
efficiency and rapidity of energy
mobilisation, and the degree of
space-time differentiation is directly
correlated with the amount of energy
stored.
Redefining the Second Law for living
systems
Physiologist Colin McClare (1971) made
an important contribution towards
reformulating thermodynamics so that it
can apply to living systems. He proposed
that in a system defined by some
macroscopic parameter, such as
temperature, q,
its energies can be separated into two
categories: stored (coherent)
energies that remain in a non-equilibrium
state within a characteristic time, t, and thermal
(random) energies that exchange with each
other and reach equilibrium (or
equilibrate) in a time less than t (see Fig
3).
Figure 3. Stored vs
thermal energy
McClare introduced time structure into
systems, with the very important
consequence that there are now two ways
to mobilise energy efficiently with
entropy change approaching zero: very
slowly with respect to t, so it is
reversible at every point; or very
rapidly with respect to t, so that
the energy remains stored as it is
mobilised.
For a process with characteristic
timescale of 10-10s, a
millisecond is an eternity, so a
‘slow’ process need not be very
slow at all to be energy efficient. Most
enzyme reactions therefore could be
occurring at thermodynamic equilibrium.
On the other hand, resonant energy
transfer is an example of a very fast
process occurring in <10-14s,
so the energy remains stored as it is
transferred. The latter process too, is
very important for living systems.
Resonance interactions coordinate
reactions in different parts of the cell
and the organism. Resonating molecules
attract one another, and there is indeed
recent evidence that proteins, nucleic
acids and other molecules find one
another through resonating to the same
electromagnetic frequencies (see Ho,
2007b).
McClare (1971) proposed that,
“Useful work is only done by a
molecular system when one form of stored
energy is converted into another”.
In other words, thermalised energies
cannot be used to do work, and
thermalised energy cannot be converted
into stored energy. This raised obvious
objections, as critics pointed out,
automobiles do run on thermalised
energy from burning petrol, so the
proposal could not be right.
McClare’s proposal was
incomplete, and I completed his proposal
as follows (Ho 1993, 1995): “Useful
work is only done by a molecular system
when one form of stored energy is
converted into another in the same
system.” The additional phrase
“in the same system”
effectively defines a ‘system’
by the extent to which thermal
energies equilibrate within a
characteristic space-time.
In the case of the automobile and
other similar contraptions, the hot gases
expand against a constraint, the piston,
which, in taking up the thermalized
energy, does work against the system external
to the combustion chamber.
This definition of a system is crucial
for the nested space-time structure of
the organism. The organism is actually
partitioned into a hierarchy of systems
within systems within systems defined by
equilibration space-times. Energies
thermalised or equilibrated within a
smaller space-time (system) will still be
out of equilibrium in the larger system
encompassing the first (see Fig. 4). So,
even though the organism as a whole is
far from thermodynamic equilibrium, its
space-time differentiation nevertheless
allows for a hierarchy of local
near-equilibrium regimes to be maintained
within.
Figure 4. A nested
hierarchy of space-times in which
equilibrium and non-equilibrium co-exist
Stored energy, like exergy and
free energy, refers to energy available
for doing useful work. But stored energy
is explicitly defined with respect to a
characteristic space-time, and is hence a
real property of systems rather than a
pseudo-property (see Ho and Ulanowicz,
2005).
The nested space-time structure in
organisms optimises thermodynamic
efficiency by allowing the organism to simultaneously
exploit equilibrium (very slow) and
non-equilibrium (very fast) energy
transfers with minimum dissipation,
always with reference to the
characteristic timescales of the
processes involved as described above. It
also optimises the rapidity of energy
mobilisation. Biochemical reactions
depend strictly on local concentrations
of reactants, which could be enormously
high, depending on their extent of
equilibration, which is generally quite
restricted. Cell biologists are beginning
to take seriously the view that the cell
approaches the solid-state, or more
accurately, a liquid crystalline state,
where nothing is freely diffusible, and
even the cell water is organized into
polarized multi-layers (Ho, 1998a, 2007a,
Ho et al, 2006b; see also Ling, 2001).
Another point to note is that the
greater the space-time differentiation,
the more coherent energy is stored within
the system. Because the activities are
all coupled together, the energy
residence time depends on how many
activities there are within the system.
Finally, there is a dynamic
structure to the space-time
differentiation, so the activities
can remain mostly distinct and
independent, and yet are poised to
exchange energies with one another. In
other words, the energies in different
space-time domains need to be separately
mobilised and yet able to spread from any
point to the entire system, and
conversely, converge from all over the
system to any point whenever and wherever
required. I have proposed that a
self-similar fractal organisation
provides such a space-time structure (Ho,
1998a, b, c). But it was only a few days
ago that I suddenly realised why.
As we were about to watch Simon
McBurney’s A Disappearing Number
at the Barbican, a play created around
the Indian mathematical sensation
Srinivasa Ramanujan, I asked Peter
Saunders if all irrational numbers were
arbitrarily close to rational numbers,
and he said yes. My guess was that
because all fractals are close to
harmonics (or in mathematical terms,
every irrational number is arbitrarily
close to a rational number), phase
coupling and energy transfer through
resonance is readily achieved by shifting
from fractals to harmonics. There is now
abundant evidence that fractal dynamics
characterizes the healthy heart rhythm,
which reflects the constant
intercommunication between the heart and
all other parts of the body (see Ho,
2007c). Real time monitoring also shows
how the heart rhythm can change abruptly,
and how positive emotions such as love
and appreciation can make the heart beat
in synchrony with the pulse and
respiratory rhythms, possibly through
resonance on a macroscopic scale (see Ho
2007d).
The ‘zero-entropy’ model
In the ideal – represented by the
healthy mature organism as well as the
healthy mature ecosystem (Odum, 1969) -
the system is always tending towards a
dynamic balance, a non-classical
steady state (Fig. 5), as will be
explained shortly. The simple equation, S DS = 0,
inside the cycle, says there is an
overall internal conservation of energy
and compensation of entropy so that the
system organisation is maintained and
dissipation minimized
(Schrödinger’s negentropy); while
the necessary dissipation exported to the
outside, is also minimised, S DS >
0.
Figure 5.
Zero-entropy model of the ideal organism
and sustainable system
Internal entropy compensation and
energy conservation implies that positive
entropy generated somewhere is
compensated by negative entropy elsewhere
within the organism over a finite time.
This is possible only if the internal
microscopic detailed balance at every
point of classical steady state theory is
violated.
Denbigh (1951) defined the steady
state as one in which “the
macroscopic parameters such as
temperature, pressure and composition,
have time-independent values at every
point of the system, despite the
occurrence of a dissipative
process.” That is far too
restrictive to apply to the organism and
the sustainable system. Instead, Ho
(1993, 1998a) proposed to define the
living system in homeostasis as a
“dynamic equilibrium in which the
macroscopic parameters, such as
temperature, pressure and composition
have time-independent values despite the
occurrence of dissipative
processes.” The omission of the
phrase “at every point of the
system” is significant.
Microscopic homogeneity is not
necessary for the formulation of any
thermodynamic state, as the thermodynamic
parameters are macroscopic entities quite
independent of the microscopic
interpretations. Like the principle of
microscopic reversibility, it is
extraneous to the phenomenological laws
of thermodynamics, as Denbigh himself had
convincingly argued.
It is the organised space-time
heterogeneity within the living system
that allows for the necessary
‘free’ variation of the
microscopic states within the macroscopic
thermodynamic constraints. Thus,
stability criteria that apply to the
system as a whole need not be satisfied,
or stronger yet, cannot be
satisfied in every individual space-time
element for all times.
The tendency to conserve coherent
energy and compensate for entropy
production within the system will
result in the minimum entropy being
exported to the outside. Intuitively, one
can see that if the system were maximally
efficient, then it would also produce the
least dissipation.
From the outside, it might appear that
the system is “maximally
dissipative” in terms of having
“degraded” the energy gradient
most effectively (Schneider and Kay,
1994; Hannon and Ulanowicz, 1987). But
this misses the coherent energy stored
non-degraded within the system, and
stored energy is also embodied in
biomass.
Sustainable systems as organisms and
diagnostic signs of sustainability
I have suggested diagnostic criteria
of sustainability or health that depend
on the tendency of a sustainable system
to maximize non-dissipative cyclic flows
of energy and minimizing dissipative
flows (Ho, 1998c).
Maximising non-dissipative cyclic
flows will increase the following: energy
storage capacity, which translates into
carrying capacity or biomass; the number
of cycles in the system; the efficiency
of energy use; space-time
differentiation, which translates into
biodiversity; balanced flows of resources
and energy; reciprocal coupling of
processes. The minimization of
dissipation will result in reducing
entropy production (towards zero).
These diagnostic criteria are
interlinked, so once one is identified,
the others are likely to follow. Some
support for these criteria is that they
are similar to those Schneider and Kay
(1994) have identified for mature,
established ecosystems (Ho, 1998c).
Data collected for carbon-energy flows in
two aquatic marsh ecosystems next to a
large power-generating facility in the
Crystal River in Florida showed that the
‘stressed’ system, exposed to
hot water coming out of the nuclear power
station, which increased the temperature
by 6 C, captured 20% less energy, made
20% less efficient use of the energy
captured, had 50% fewer cycles and 34%
less biomass than the control.
Schneider and Kay (1994) also drew
attention to some interesting
measurements made by Luvall and Holbo
(1991) with a NASA thermal infrared
multispectral scanner from the air, which
assess energy budgets of terrestrial
landscapes. They found that the more
developed the ecosystem, the colder
its surface temperature. This is
consistent with the maximisation of
energy storage capacity and the
minimisation of dissipation.
Another indication of the energy
efficiency and potential increase in
carrying capacity of sustainable systems
is provided by a comparison of 25 rice
cultivation system (see Ho 1998c), of
which 8 were pre-industrial in terms of
low fossil fuel input (2-4%) and high
labour input (35-78%), 10 were
semi-industrial with moderate to high
fossil fuel input (23-93%) and low to
moderate labour input (4-46%) and seven
were full industrial with 95% fossil fuel
input and extremely low labour input of
0.04 –0.2%). The total output per
hectare (in GigaJoule) in the
pre-industrial fell into a low (2.4 to
9.9) and a high-output (149.3 to 166.9)
subgroup, with the former one-twentieth
to one-fifth of the full industrial
average. However, the output of the high
subgroup was two to three times the
full-industrial systems. The yields
of semi-industrial systems were more
homogeneous, with an average of 51.75GJ,
while the yields of full-industrial
systems, even more uniform, averaged
65.66 GJ.
When the ratio of total energetic
output to total input was calculated, the
pre-industrial low yielding systems
ranged between 6.9 and 11.5, whiles
figures for the high output system
registered from 15.3 to 29.2.
Semi-industrial systems gave ratios of
2.1 to 9.7, whereas the ratios of
full-industrial systems were not much
better than unity. These figures
illustrate the law of diminishing
returns: there seems to be a plateau of
output per hectare around 70-80 GJ
regardless of the total input, which is
only exceeded in the three high-yielding
pre-industrial systems of Yunnan, China.
Intensifying energy input led to a drop
in efficiency, particularly sharp as
input approaches the output ceiling,
which appeared to conform to the notion
of a uniform carrying capacity. But this
is highly misleading, as the carrying
capacity depends on how the land is
organised for production (see below).
Dream Farm 2
There is no longer any doubt that we
are living through climate change as
fossil fuels are fast depleting, and
hurricanes, droughts and floods are
destroying lives, homes and crops all
over the world. I remain optimistic,
however, because we actually have a
wealth of knowledge that is capable of
provide food security and health for all,
and significantly mitigate climate change
(Ho et al 2006a).
A major
obstacle to implementing this knowledge
is the overwhelming commitment of our
elected representatives to the dominant
neo-liberal economic model, otherwise
known as the environmental bubble-economy
(Brown, 2003). It is based on the
exploitation of environmental resources
beyond their capacity for renewal or
regeneration in order to fuel perpetual
economic growth.
I have proposed a
‘zero-emission’,
‘zero-waste’ ‘Dream Farm
2’ based on the zero-entropy model.
In practice, Dream Farm 2 maximises the
use of renewable energies and turns
‘wastes’ into food and energy
resources, thereby freeing us completely
from fossil fuels (for the latest update
see Ho, 2007e) (Figure 6).
Figure 6.
Dream Farm 2 based on the zero-entropy
model of the organism
The diagram is colour-coded: red is
for energy, green for food, black is
waste in the conventional sense of the
word, but is soon transformed into
resources, and blue is for water
conservation and flood control, a key
requirement in stable food and energy
production under the vagaries of rainfall
patterns now experienced across the
world.
The anaerobic digester is the core
technology for treating wastes,
preventing pollution and generating
energy. Livestock manure, food, paper and
other biological remains are fermented by
naturally occurring waste-gobbling
bacteria and turned into biogas, which
provides much of the energy needs. The
partially cleansed wastewater goes into
the algal basins where algae
photosynthesis produces all the oxygen
needed to detoxify the water, making it
safe for the fish. The algae are
harvested to feed chickens, ducks, geese
and other livestock. The fishponds
support a compatible mixture of 5-6 fish
species. Water from the fishponds
‘fertigates’ crops growing in
the fields or on the raised dykes. Fruits
and vegetables can be grown in floats on
the surface of the fishponds. Water from
the fishponds can also be pumped into
greenhouses for aquaculture of fruits and
vegetables. The water, purified of
nutrients, is returned to the aquifers.
The anaerobic digester yields a residue
rich in nutrients that is an excellent
fertiliser for crops. It can also be
mixed with algae and crop residues for
culturing mushrooms after steam
sterilisation. The residue from mushroom
culture can be fed to livestock or
composted. Crop residues are fed back to
livestock. Crop and food residues can be
used to raise earthworms to feed fish and
fowl. Compost and worm castings go to
condition the soil. Livestock manure goes
back into the anaerobic digester, thus
closing the grand cycle. The result is a
highly productive farm that’s more
than self-sufficient in food and energy, and
saves substantially on carbon
emissions.
Anaerobic digestion of livestock and
other wastes saves carbon emissions twice
over, by preventing the serious
greenhouse gases methane and nitrous
oxide from reaching the atmosphere, and
by methane substituting for fossil fuel
use to run vehicles and farm machinery.
For a country like the UK, anaerobic
digestion of all biological wastes could
provide more than 11 percent of the
country’s energy use and more than
50 percent of its transport fuels.
In addition, all the building
materials will be sourced, and buildings
designed to minimise carbon emissions and
energy use.
The farm will incorporate other forms
of renewable energies suitable for local
energy generation at the medium, small to
micro-scale: solar panels/walls, small
wind turbines, and microhydroelectric
generators where appropriate.
The approach is to get the farm up and
running while new technologies and
designs are researched and incorporated,
such as generating hydrogen from wastes
or from methane, using algae to capture
carbon dioxide from combined heat and
power generation and making biodiesel,
and fuel cells that take methane to
reform into hydrogen. All of that will be
part of an education/research component
of the farm. The farm will also provide
an excellent showcase for new,
appropriate technologies.
Zero-Entropy Model vs the
Dominant Model of Infinite Growth
Dream Farm 2 illustrates how the zero
entropy model contrasts with the dominant
model, and more importantly, how it is
possible to have sustainable growth and
development. Too many critics of the
dominant paradigm think that the only
alternative to unsustainable growth is to
have no growth at all.
The minimum entropy exported to the
environment is important, as the system
depends on environmental input, hence,
entropy exported to the environment will
simply mean diminished environmental
input. This can be made more explicit by
enclosing the system within the immediate
environment of the system as in Figure 7.
Figure 7.
The coupled flows of system and
ecological cycles in a sustainable system
The ecological environment surrounding
the system is now explicitly represented
also as a zero-entropy cycle. You have to
imagine, once again, that this is a
fractal diagram, and that the environment
surrounding the system is itself
exporting to a larger ecological domain,
and this kind of embedding can go on,
ultimately to the entire earth. And of
course, each cycle is made up of many
smaller cycles within (see Fig. 2) all
working by reciprocity and cooperation.
In contrast, the dominant model of
infinite competitive growth is a case of
the bigger fish swallowing the smaller ad
infinitum, and it describes equally
how a person should behave and how a
company should develop in order to be
successful. But it is the entropy and
waste generation that concerns us here,
so I have represented it diagrammatically
in Figure 8. This system grows
relentlessly, swallowing up the
earth’s resources, laying waste to
everything in its path, like a hurricane.
There is no closed cycle to hold
resources within, to build up stable
organised social or ecological
structures. It captures the essence of
our ‘boom and bust’ economy.
The money market is especially entropic,
as I have pointed out elsewhere (Ho
1998b, c), mainly because it is not based
on any real-valued goods or services;
furthermore, it artificially inflates the
purchasing power of the rich, leading to
greater exploitation of environmental
resources.
Figure 8.
The dominant economic model of infinite
unsustainable growth that swallows up the
earth’s resources and exports
massive amounts of wastes and entropy
(left) contrasted with the zero-entropy
model
The dynamically closed cycle of the
zero-entropy mode, on the other hand,
enables stable organised social or
ecological structures to build up, and
to grow and develop in a balanced
way, as distinct from the dominant model
of infinite, unsustainable growth.
As in the zero-entropy model of the
organism, the sustainable system’s
cycle contains more cycles within that
are interlinked symmetrically to help one
another thrive and prosper (see Fig. 2).
This principle is well illustrated in
sustainable integrated farming.
The minimum integrated farm has the
farmer, livestock and crops (Fig. 9). The
farmer prepares the ground to sow the
seeds for the crops to grow that feed the
livestock and the farmer; the livestock
returns manure to feed the crops. Very
little is wasted or exported to the
environment. In fact, a high proportion
of the resources are recycled and kept
inside the system. The system stores
energy as well as material resources such
as carbon. The extra carbon is
sequestered in the soil as the soil
improves, and in the standing biomass of
crops and livestock.
Figure 9.
The minimum integrated sustainable farm
More importantly, the farm can
perpetuate itself like that quite
successfully and sustainably, or it can
grow by engaging more cycles, units of
devolved autonomy that help one another
do better. (In analogy with the organism,
it will develop a more complex space-time
differentiation, and grow bigger.)
In the old paradigm, organisms are
predominantly seen to compete for
resources and for space. But we’ve
got three space dimensions and the time
dimension too. We’ve got space-time
that we can fill up more thickly with
life cycles of different sizes that
occupy different space-times. That is
exactly what organisms in a naturally
biodiverse ecosystem do to maximise the
reciprocal, symbiotic relationships that
benefit all the species. So you can add
fish, algae, poultry, worms, mushrooms,
etc., turning the ‘waste’ from
one cycle to resource for another
(Fig.10).
Figure 10.
Sustainable system develops and grows by
incorporating more life cycles within the
system, the wastes from one cycle is
resource for another.
The more lifecycles incorporated, the
more energy and standing biomass are
stored within the system, and the greater
the productivity of the farm. It will
also support an increasing number of
farmers and farm workers.
Productivity and biodiversity always
go together in a sustainable system, as
generations of farmers have known, and
recent academic researchers have
rediscovered. I had predicted the
same earlier on the basis of a space-time
differentiation that maximises
distributed energy storage (Ho, 1998b,c).
The different life cycles are essentially
holding the energy for the whole system,
and by way of reciprocity, recycling
the energy within the system. Once it is
recognized that coherent energy is stored
within the system, it follows that energy
can be recycled, contrary to the
conventional wisdom that regards only
materials as capable of being recycled.
Industrial monoculture, in contrast,
is the least energy efficient in terms of
output per unit of input, and often less
productive in absolute terms despite high
external inputs (see above), because it
does not close the cycle, it does not
have the biodiversity (space-time
differentiation) and reciprocity to hold
the energy within and ends up generating
a lot of waste and entropy and depleting
the soil.
In a recent visit to China, I was
delighted to discover that something very
similar to the model of sustainable
systems as organisms is in the official
Chinese mainstream discourse; they call
it the “circular economy”.
Chinese farmers have perfected it over
the past two thousand years especially in
the Pearl River Delta of southeast China
(Ho 2006). It disposes of another myth:
that there is a constant carrying
capacity for a given piece of land, in
terms of the number of people it can
support.
There is a world of difference between
industrial monoculture and circular
integrated farming, it is the difference
between the dominant linear input-output
maximum entropy model and the
zero-entropy sustainable model. The
carrying capacity depends on how the land
is organised for production. The Pearl
River Delta sustained an average of 17
people per hectare in the 1980s, a
carrying capacity at least ten times the
average of industrial farming, and two to
three times the world average.
The thermodynamics of organisms and
sustainable systems tells us not only why
we must move away from the dominant
environmental bubble economy, but
especially how we can create a healthier,
richer, more equitable and satisfying
life without fossil fuels, and we should
start right now.
Acknowledgment
I am very grateful to Mario and
Loredana Pianesi of Un Punto Macrobiotico
for inviting me to this conference and
instigating this paper.
Peter Saunders is used to having
questions on mathematics fired at him at
random. This time it was a direct hit,
and the excitement has yet to subside.
Ulanowicz, R.E. Identifying the
structure of cycling in ecosystems.
Mathematical Biosciences 65, 219-237,
1983.
Denbigh K.G. The Thermodynamics of
the Steady State, Mathuen & Co.,
Ltd., New York, 1951.
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