Lesson 2.4: Complex system theory

Icône de l'outil pédagogique Author

Frank Ewert


Icône de l'outil pédagogique Systems thinking and theory

Systems’ thinking has evolved as a result of the increasing complexity of problems that could not be addressed with more traditional, e.g. analytical approaches. The theory assumes that no matter how complex or diverse the world is, it will always be possible to find different types of organization in it. It investigates both the principles common to all complex entities, and the (usually mathematical) models which can be used to describe them (Heylighen and Joslyn, 1992). Systems’ thinking is applied in a wide range of fields from industrial enterprises and armaments to esoteric topics of pure science (von Bertalanffy, 1976).

A system is defined as a group of independent but interrelated elements comprising a unified whole that is relatively autonomous, self-organising, viable, sustainable and performing. The systems concept includes: boundary and therefore system-environment composed of other systems, input and output and components (Bossel, 1989; Heylighen and Joslyn, 1992), (Figure 1). A living system performs due to processes and relationships among components. In addition, hierarchy, goal-directedness and information are also considered as part of the systems concept (Heylighen and Joslyn, 1992). System theory with application to agricultural systems has been significantly progressed by the work of De Wit (Leffelaar, 1999).

Figure 1. Schematic representation of a system within a given environment with boundary, components (C1…C4) and processes and relationships (bold arrows) among components. Interactions with the environment are through inputs and outputs (white arrows).

 


Icône de l'outil pédagogique Complexity and hierarchy

The notion of complexity is vague and indicates that a system has many (the term is relative and changes with time) components and relationships among these components. In a complex system, the whole is more than the mere sum of its parts implying that understanding of the components of a system is not sufficient to understand its overall behaviour. Other important features of complex systems are that relationships among components are non-linear and contain feedback loops; they are nested and open systems with boundaries that are difficult to determine. Complex systems are highly structured and are very sensitive to the initial conditions. Important types of complex systems are (1i) chaotic, (2) complex adaptive and (3) non-linear systems.

Analysis of complex systems faces the problem of integrating knowledge from different disciplines (biophysics and socio-economics) and levels of the organisation. Hierarchy theory offers a concept for the investigation of systems that operate on several spatio-temporal scales. It is a dialect of general systems theory and has emerged as part of a movement towards a general science of complexity. It focuses on levels of organization and issues of scale and the perspective of the observer of the system plays an important role. An example for hierarchical systems is the biological organisation as commonly used in ecology and environmental sciences with levels such as organism, population, community, landscape etc. (Figure 2). Hierarchical systems have an organisational structure that refers to the shape of a pyramid, with each row of objects linked to objects directly beneath it (Figure 2a). Thus, at a given level of resolution, a system is composed of interacting objects/components (i.e., lower-level entities or sub-systems) and is itself a component/object (or sub-system) of a larger system (i.e., higher level entity). Such nested systems are commonly called holarchic systems with holons representing the objects/components of the system. For the analysis of such systems it is not always required to account for the full complexity; concentration on objects/components that are of particular importance for the behaviour of the system may suffice (Figure 2b). Scale issues are extremely important when analyzing complex systems. Proper scaling may decrease complexity (Parker et al., 2002) and several methods have become available (Ewert et al., 2006).

Integrated assessment and modelling has been suggested as a solution to the management of complex environmental systems. It is a way of systems thinking; a way to balance the different aspects (biophysical, institutional, social and economic) of the system (Harris, 2002). SEAMLESS-IF uses the concept of systems theory (Ewert et al., 2005).

 

 

  Figure 2. Schematic representation of a hierarchical system with a) fully or b) partially nested sub-system.

 

 


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