Self-organising Agro- ecosystems

355 Pages·2008·2.55 MB·English

Self-organising Agro-

ecosystems

by

Raoul A. Robinson

Second edition, revised

Sharebooks Publishing
www.sharebooks.ca

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© Raoul A. Robinson, 1996, 2004, 2007.

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Library and Archives Canada Cataloguing in Publication

Robinson, Raoul A.
Self-organising agro-ecosystems / by Raoul A. Robinson. -- 2nd ed.,
rev.

Also available in electronic format.

Includes bibliographical references.
ISBN 978-0-9783634-1-3
1. Agricultural ecology. I. Title.
S589.7.R63 2007 577.5'5
C2007-905616-4
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Preface

This work proposes methods of reducing, even eliminating, the use of crop
protection chemicals from our crops and environment. It seems that this can best
be achieved by self-organisation (sensu Adam Smith) within agro-ecosystems.
This self-organisation can be brought about by numerous plant breeding clubs that
are employing durable resistance to crop parasites.
If we consider the food production of a country, we find a self-organising
system. Many farmers, acting individually, choose what crops to grow, and what
cultivars of those crops to grow. Their decisions are based mainly on their
environment, and on market demand, which comes from the decisions of
individual merchants who buy their produce. Systems of transport and food
processing convert raw materials into marketable products, and retailers make
these products available to consumers through stores and super-markets. These
consumers choose what they buy, usually on a basis of either cost or quality. The
stores must stock items according to customer preferences. There must be some
government control to ensure purity and hygiene, and to prevent monopolies and
cornered markets. But, in general, too much government control is damaging.
This was revealed dramatically by the failure of the Soviet system of
State-controlled agriculture. Government control must be kept to the essential
minimum, and the entire system should be self-organising. The importance of this
phenomenon of self-organisation was first recognised by Adam Smith
(1723-1790) in his book The Wealth of Nations, published in 1776, although he
did not use this term. Immanuel Kant (1724-1804) was apparently the first to use
the term ‘self-organisation’. The present volume is intended primarily for
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universities wishing to initiate student clubs for plant breeding, but it may also be
of interest to any scientist involved with crop parasites. A proper understanding of
this topic requires an acquaintance with the general systems theory, modern
complexity theory and, most of all, various concepts of the ecosystem and the
pathosystem.
A further purpose of the present book is to summarise, bring up to date, and
present in one volume, concepts that I consider relevant in earlier writings of
mine, including books that are now out of print.

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Chapter One
1. General Systems Theory
1.1 Introduction
The founder of systems theory was a little known Russian scientist called
Alexander Bogdanov, who published a three-volume work entitled Tektology in
1912-1917. A German edition was published in 1928 but the work remained
largely unrecognised and unknown in the West. Lenin denounced Bogdanov on
ideological grounds, and the Soviet authorities suppressed his works.
About a quarter of a century later, an Austrian scientist, Ludwig von
Bertalanffy, developed his general systems theory. It is unlikely that he was
ignorant of Bogdanov’s earlier work, but he never acknowledged it, and the
lingering possibility of plagiarism cannot be entirely dispelled. Nevertheless,
Bertalanffy was very influential, and he is widely recognised as one of the
principle founders of the general systems theory. His main contribution was the
concept of the open system, which would allow energy to flow into it and,
interestingly, this was an enlargement of the second law of thermodynamics.
The French physicist Sadi Carnot first formulated the second law of
thermodynamics, which postulates that all energy gradients disappear in a closed
system. This process is described as an increase in entropy, or disorder. A closed
system will thus tend to total internal uniformity of energy distribution. The open
system is in direct contrast and, by absorbing energy from outside, it can increase
its energy gradients. An open system can be described by saying that its negative
entropy (negentropy) increases.
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The concept of negative entropy can be applied to complexity of
organisation, as well as to energy. In a closed system, organisation tends to
disappear, resulting in total disorganisation, and simplicity of arrangement. In an
open system, organisation tends to increase, resulting in complexity of
organisation. All living systems are open systems. They absorb energy, and their
complexity of organisation increases.

1.2 Patterns
A pattern is an arrangement of units. A wall is a pattern of bricks, a word is
a pattern of letters, a tune is a pattern of notes, a molecule is a pattern of atoms,
and so on.

1.3 Systems
A system is a series of patterns of patterns, and each pattern of patterns is
called a systems level (see 1.4). There are many kinds of system, including
electrical systems, mechanical systems, political systems, solar systems, living
systems, taxonomic systems, traffic systems, and so on. Systems theory studies
the properties that these various systems have in common. The most relevant of
these properties are described under the various headings below.
When it is applied to a word, the suffix ‘-ation’ often implies a system.
Thus, we have ‘transport’ and ‘transportation’. When someone offers a ride and
says “May I offer you transportation?” he should really say ‘transport’. And the
system of public busses and underground trains in London is called “London
Transport”, when it should really be “London Transportation”. Similar comments
can be made about ornament and ornamentation (a system of ornaments),
classification (a system of classes), experimentation, hyphenation, organisation,
plantation, medication, and so on.
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1.4 Systems Levels
A pattern of patterns is usually called a systems level. For example, a book
is a static system, which consists of subsystems called chapters. Collectively,
these chapters constitute a systems level. Each chapter consists of subordinate
patterns of patterns (or secondary subsystems) called paragraphs. And so on,
downwards, through sentences, words, and letters. The book itself is part of a
super-system called a library. Clearly, a book has many systems levels.
The importance of recognising systems levels is that they lead to the
concepts of emergents, reductionism, and suboptimisation. It will transpire that
these concepts are central to any analysis of twentieth century crop science.

1.5 Hierarchies and Networks
We tend to think of systems levels in terms of hierarchies. Each systems
level is a rank in the hierarchy, superior to the rank below it, and inferior to the
rank above it. This is a very convenient and useful method of analysis but, in fact,
it is often a misrepresentation. It is perhaps more accurate to think in terms of
networks, and of networks nesting within other networks, all interacting within
themselves and among themselves. Some networks are larger than others, but this
does not necessarily make them superior. Nevertheless, for simplicity of
discussion, I will continue writing in terms of systems levels.
A beautiful example of a network is the Internet. Here is a network of
networks if ever there was one. Perhaps we should think of the Internet as some
kind of ‘super-organism’, with a ‘life’ of its own, and soon to produce entirely
new emergents (see 1.9) of enormous importance, which we can now perceive
only dimly, if at all. One of the more obvious emergents will be entirely new
forms of global awareness and democracy.
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1.6 Homeostasis
The term ‘homeostasis’ was coined by the American physiologist Walter
Cannon (1932) who was describing the many self-regulatory mechanisms in the
human body. The classic example of homeostasis is the maintenance of body
temperature. If we get too hot, we sweat, and evaporation cools us down.
Conversely, if we get too cold, we start shivering, and this involuntary exercise
warms us up. Subsequently, homeostasis was recognised in many other systems.
For example, Lerner (1954), coined the term ‘genetic homeostasis’ to describe the
maintenance of an optimum genetic constitution of a population.
Homeostasis describes an important aspect of systems control, which
results in the maintenance of a desirable steady state. The mechanism of this
control is called feedback.

1.7 Feedback
The term ‘feedback’ refers to the output controlling or influencing the
input. The cyberneticists, who recognised two kinds of feedback, introduced the
concept of the ‘feedback loop’. And they called self-balancing feedback ‘negative
feedback’, and self-reinforcing feedback ‘positive feedback’.
Negative feedback is illustrated by all homeostatic mechanisms. For
example, the automatic steering of a ship exhibits a phenomenon that engineers
call ‘hunting’. That is, the ship tends to veer slightly away from its proper course,
and the homeostatic steering mechanism brings it back again. But it may then veer
slightly off course in the other direction, and the steering mechanism brings it
back again. This control, this homeostasis, which returns the ship to its optimum,
is negative feedback which, obviously, is self-balancing and valuable.
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The resilience, flexibility, and overall stability of a complex adaptive
system, such as an ecosystem, are a consequence of its many negative feedback
loops. For example, if a parasite becomes excessively damaging, the host
population accumulates resistance to it, and the parasitism returns to its normal
level. It is this feedback which brings the system back to its optimum whenever
there is a deviation from the norm.
Positive feedback, being self-reinforcing, is often destructive. In common
usage, it is often called a vicious spiral. With positive feedback, there is an
exponential increase. That is, the rate of increase is itself increasing.
An example of positive feedback is the self-fulfilling prophecy. If false
rumours circulate that an airline is about to go bankrupt, passengers will avoid it
for fear of cancelled flights and valueless tickets. There is then a rapid loss of
business, which leads to increasingly strong rumours of bankruptcy. These
increasing rumours are positive feedback, and the previously solvent airline loses
so much business that it may well go bankrupt. A similar positive feedback can
lead to a stock market crash. Another example is the ear-splitting howl that often
develops in a public address system. The microphone picks up the hum of the
speakers. The hum is then amplified, and the hum of the speakers increases.
Positive feedback makes the hum rapidly louder and louder.
Perhaps the most important example of positive feedback in biology is the
population explosion. The total reproduction of a population depends on numbers
of individuals. As reproduction increases, so numbers increase, and the rate of
increase itself increases, in a vicious spiral. Species that are capable of very rapid
population explosions are called r-strategists (see 1.13) and they are of special
significance in crop pathosystems.

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1.8 Resilience
The combination of all the homeostatic mechanisms in a system produces
the emergent property of resilience. Resilience means that the system can suffer
quite wide swings away from its optimum, and then recover.

1.9 Emergents
An essential feature of a pattern is that it has emergent properties, often
called ‘emergents’. An emergent can be observed only at its own systems level. It
cannot be discerned from any lower systems level. This can be put another way by
saying that an emergent has ‘novelty’. That is, as one progresses to higher and
higher systems levels, each emergent is new in the sense that it does not occur at
any lower systems level. An emergent is often described by saying that the whole
is greater than the sum of its parts. The whole includes both the sum of all the
parts of the system, as well as the emergents, which are additional to the sum of
all those parts.
In a living system, any behaviour, at any systems level, is an emergent
property of that system. Life itself is an emergent. In the past, various
characteristics that are unique to living organisms were often described as ‘vital
forces’, and these too are emergents. So too are the various human intangibles,
such as creativity, generosity, and sociability, that are generally considered
‘unscientific’, simply because they cannot be easily measured.
In this general context of behaviour being an emergent, it is possible to
speak of ‘plant behaviour’, at any systems level. Obviously, plants do not walk
and talk, but they exhibit behaviour in the sense of growth, sexual recombination,
reproduction, and death. Indeed, Fisher & Hollingdale (1987) have shown that
plants with sun-tracking leaves have both a primitive sight, and a daily movement.
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