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Complexity is a condition of systems composed of many interconnected parts, where the behaviour of the whole system cannot be fully understood by simply analysing the behaviour of its components. Complex systems are adaptive and generate a new quality of collective behaviour through self-organisation. They are frequently characterised as having extreme sensitivity to initial conditions as well as emergent behaviour that are not predictable or completely deterministic (Meyers, 2009). When related to socio-environmental issues, failing to understand complexity often leads to policy resistance and the worsening of problems. Ignoring the time and spatial distance between causes and effects typically results in policies that generate transitory improvement before the problems grow worse (Sterman, 2000).

According to Sterman (2000), natural and human systems combine several characteristics which give rise to complexity:

• Dynamics, systems change at many different and sometimes interacting

time scales;

• Tight couplings, which reflects the notion that ‘everything is connected to everything else’, given the multiple intra- and inter-relationships between actors and natural systems;

• Feedback, where decisions made in tightly coupled systems lead to actions which influence subsequent decisions;

• Non-linearities, characterising relationships where the effect is not proportional to cause;

• History-dependence, wherein some decisions create path dependence, precluding alternative options and leading to irreversible actions;

• Self-organisation, describing situations where behaviour arises spontaneously from the internal structure of systems. Small and random perturbations are often amplified and moulded by the feedback structure generating different time and spatial patterns;

• Adaptiveness, relating to changes in the capabilities and decision rules of the agents in complex systems, leading to evolutionary and learning processes.

Several mathematical and modelling methods and tools (e.g. agent-based modelling, cellular automata, game theory and system dynamics) have been progressively applied to scientific, engineering and societal issues that can only be adequately described in terms of complexity and complex systems (Meyers, 2009). Complex systems are becoming the focus of innovative research and application in many areas, providing a theoretical justification for a post-normal approach to the management of science-related issues (Funtowicz and Ravetz, 1994). Such is the case in ecological economics, where the engagement of complex knowledge communities has been increasingly advocated for responding to complexly interacting sociophysical systems and environments (Henshaw, 2010).

References:

Funtowicz, S., Ravetz, J. (1994) Emergent Complex Systems. Futures, 26 (6) 568-582.

Henshaw, Philip (Lead Author); Mark McGinley (Topic Editor). (2010) Complex systems. In: Encyclopedia of Earth. Eds. Cutler J. Cleveland (Washington, D.C.: Environmental Information Coalition, National Council for Science and the Environment). [First published in the Encyclopedia of Earth January 18, 2010; Last revised November 22, 2010; Retrieved November 11, 2012, available at http://www.eoearth.org/article/Complex_systems].

Meyers, R. (2009) Encyclopedia of Complexity and Systems Science. Springer, New York, USA.

Sterman, J. (2000) Business Dynamics. Systems Thinking and Modeling for a Complex World. McGraw-Hill, USA.

Useful websites:

Complexity Digest [http://comdig.unam.mx]

Complexity Blog [http://complexityblog.com/]

This glossary entry is based on a contribution by Nuno Videira 

EJOLT glossary editors: Hali Healy, Sylvia Lorek and Beatriz Rodríguez-Labajos