p.1 Ecosystems are incredibly complex, and it is therefore not surprising, that many different viewpoints
are needed to obtain a more complete image of an ecosystem.
p.5 We want to understand the reaction of nature to our influence and we have realised that reductionistic
methods alone cannot cope with the environmental problems, mainly due to -
1) unexpected effects and rare events, unexpected in time and space may occur at any time
due to the high amount of linkages and indirect effects in ecosystems, and because
2) ecosystems are extremely complex which renders them impossible to analyse and thereby
unable know all the details.
Consequently, we cannot attempt to find the understanding of the whole by adding all the
reductionistic details. We have to use another approach, which is system ecology, where the system analytical focus
is put on the properties of entire ecosystems.
p.8 A model can be considered as a synthesis of elements of knowledge about a system.
The quality of the model is therefore very dependent on the quality of our knowledge about the elements of the system and
the available data... The model represents a synthesis of knowledge and data and can provide results particularly about the
system properties... We use models, in other words, to uncover the holistic properties.
p.13-14 Holism attempts to reveal the properties of complex systems such as ecosystems by
studying the systems as a whole. According to this approach the system properties cannot be found by a study
of the components separately due to the high complexity and due to the presence of emergent properties... Reductionism
attempts to reveal the properties of nature by separating the components from their wholeness to simplify the study and to
facilitate the interpretation of the scientific results... no science has succeeded in understanding the structure
and dynamics of a complex system from a reductionistic approach alone... The conclusion from these considerations
is clear: we need both approaches, but because it is much easier to apply the reductionistic method, analytical work has been
the overwhelming synthetic work in science... The need for a more holistic approach increases with the complexity,
integration, number of interactions, feedbacks and regulation mechanisms.
p.41-42 sustainable development is an interdisciplinary concept... Bossel... states that
in searching for principles to guide sustainable development, it is only natural to have a closer look at the global ecosystem,
which has demonstrated sustainability over a few billion years. Ecosystems are working models of sustainable complex
systems, and it is reasonable to study them for clues to the sustainable management of the human enterprise. Apart
from this strategy of nature as a model for human dynamics, the ecological constraints alone determine the real potentials
of human life.
p.45 All sustainable activities have to accept the natural system of constraints in which the investigated
entity operates.
p.54 The potential of self-modification and change of organisms causes a high degree of variability (Ekschmitt
et al. 1996). Thus, physical constraints do not entirely determine ecological systems. Organisms exchange material and energy
with the external environment to build their structures and maintain their activities... the future development of ecological
systems normally cannot be derived from a simple set of rules or equations describing physical laws. Instead, ecological
development results from the totality of all factors contributing to a particular situation and interaction within the system
(Pahl-Wostl 1995)
p.104 A model is an abstraction of reality. It is a formal description of the essential elements
of a problem... we can think of a model as a formal description of the system-of-interest.
p.106 Simulation is the process of using a model to mimic, or trace through step by step, the behaviour
of the system we are studying.
p.106 The goal of the first phase of systems analysis is to develop a conceptual or qualitative,
model of the system-of-interest... we abstract from the real system those components that must be considered to address
our questions... Next we categorize model components depending on their specific roles in describing system structure and
identify specific relationships among components that generate system dynamics... In many respects conceptual model
formulation is the most intellectually challenging phase of systems analysis. The best basis for the
many difficult, and often highly subjective, decisions that must be made regarding the choice of
model components is a thorough familiarity with the real system. Prior modelling experience also is an asset.
p.144 The term complex systems thinking is being used to refer to the body of knowledge that deals
with complexity. Complex systems thinking has its origins in von Bertalanffy's general systems theory.
p.145 Properties of complex systems to bear in mind when thinking about ecosystems.
- Non-linear: Behave as a whole, a system. Cannot be understood by simply decomposing into pieces
which are added or multiplied together.
- Hierarchical: ... The systems is nested within a system and is made up of systems...
- Internal causality: ... self-organizing. Characterized by: goals, positive and negative feedback,
autocatalysis, emergent properties and surprise.
- Window of vitality: Must have enough complexity but not too much. There is a range within which self-organisation
can occur...
- Dynamically stable?: There may not exist equilibrium points for the system.
- Multiple steady states: There is not necessarily a unique preferred system state in a given situation...
- Catastrophic behaviour: The norm... moments of unpredictable behaviour... sudden discontinuities,
rapid change...
- Chaotic behaviour: our ability to forecast and predict is always limited... regardless of how sophisticated
our computers are and how much information we have.
p.145-146 Maruyama... was one of the first to examine the issues of complexity... he identified a class of
systems which require... explanations that involve both positive and negative feedback loops and autocatalysis, mutual causality.
He demonstrated how probabilistic or deterministic loops of mutual causality can increase a system's pattern of heterogeneity
towards higher levels of organised complexity. He showed that traditional explanations in terms of linear causality, that
is in terms of a clear cause and effect relationship, were not possible for the phenomena exhibited by this class of systems.
The problem is that when feedback loops dominate a system, the effect becomes part of the cause. So the cause is not
independent of the effect as is required by linear cause and effect explanations.
p.146 It has been argued... that ecosystems fall into the class of systems that Maruyama identified and which
Koestler called SOHO systems. The dynamics of such systems are described by narratives. A central question to be addressed
by the narrative description of a SOHO system is an elaboration of its propensities. The elaboration delineates the mutual
causality of the feedback loops and autocatalytic process which give the system its coherence as an entity. This set of propensities,
which define a holon, is referred to as its "canon".
p.168 If we pump energy into a system the equilibrium will, according to Le Chatelier's Principle, shift towards
a utilisation of the energy.
p.199 emergent properties are observable at the systems level alone, and will not, and cannot, be
found by following the reductionist strategies of research in accordance with the normal positivistic ways of performing
science. The "secrets" of emergent properties are to be revealed by holistic research strategies only.
p.209 Many of the problems we face in management today are related to emergent properties as they
are dealing with the unpredictable behaviour of nature and its unexpected responses to the way we interact with it...
our chances to deal with management problems and eventually improve our future interaction with nature, in
terms of eliminating or minimising, unwanted effects of our actions, totally relies on an improved understanding of
the mechanism underlying this emergence.
p.258 Bossel (1992) uses what he calls six basic orientors or requirements
to develop a system model that is able to describe the system performance properly.
p.385 In ecological systems, resilience is the extent to which a system can withstand disruption before
shifting into another state (Holling 1973).
p.385 those examining ecological resilience tend to look for other stable states, and the locations of the
boundaries between states.
p.506 Ecological self-organization is a key component of at least two explicit descriptions of ecological
integrity. Kay & Schneider (1995) identify three "organisational facets" that ecological integrity encompasses: the ability
to maintain normal operations under normal environmental conditions, the ability to cope with changing environmental conditions,
and the ability to continue the process of self-organisation. Muller (1998b) condenses these facets, and calls those ecological
systems integer [JLJ - from p.504, a "healthy" state of the ecological interaction network] that (i) are able to maintain
their organisation and steady state after small disturbances, and that (ii) have a sufficient adaptability and developmental
capacity to continue self-organised development... the future-directed potential of an ecological system to self-organise
has to be assessed. This potential depends on conditions and constraints
p.525 There is obviously an immense variety of system environments, just as there is an immense variety
of systems. But could it be that all of these environments have some common general properties? If that were the case, we
could expect their reflections as "basic system needs" or "system interests" in all systems that have been shaped
by their environments. These reflections would orient not just structure and function of systems, but also their
behaviour in the environment. Moreover, with proper attention to these fundamental orientations ("basic orientors")
of systems towards general properties of their environment, we could design systems to be successful in a given environment...
Indicators of viability and sustainability have to reflect how well the "basic system needs" or "basic orientors"
are satisfied under given circumstances. [JLJ - Hmmm... useful for game theory]
p.526 The assessment of orientor satisfaction, i.e. of system viability and sustainability, can
be done by identifying indicators that can provide information about how well each of the orientors is being fulfilled
at a given time. In other words, the basic orientors provide us with a checklist for asking a set of questions for finding
out how well a system is doing in its environment... Each of the basic orientors stands for a unique requirement.
That means that a minimum of attention must be paid to each of them, and that compensation of deficits of one orientor by
over-fulfillment of other basic orientors is not possible... Viability and sustainability of a system require
adequate satisfaction of each of the system's basic orientors. Planning, decisions, and actions in societal systems
must therefore always reflect at least the handful of basic orientors (or derived criteria) simultaneously... a system's
development will be constrained by the basic orientor that is currently "in the minimum". Particular attention will
therefore have to focus on those orientors that are currently constraining. [JLJ - sounds like a plan for managing search
efforts in a game.]
p.530 Note that the different indicators cannot be combined into one number describing the current
state of "sustainability"... each of the basic orientors has to be satisfied separately.
p.551 Technological optimists argue that human systems are fundamentally different from other natural systems
because of human intelligence and that history has shown that resource constraints can be circumvented by new ideas (Myers
and Simon, 1994).
p.563 Both the setting of a goal and the considerations in order to reach it are intellectual activities...
Of course, ecosystems, unlike human systems, do not have a goal. There is no intellectually fixed destination that natural
development moves towards. In addition, there is no chance to formulate or realise the wish to grow into a specific direction
in these systems.
