Discrete Dynamics in Nature and Society
Volume 3 (1999), Issue 2-3, Pages 81-108

Population growth and environment as a self-organizing system

Peter M. Allen

International Ecotechnology Research Centre, Cranfield University, Bedford MK43 OAL, UK

Received 16 November 1998

Copyright © 1999 Peter M. Allen. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Over recent years a new understanding of complex systems, and their dynamics and evolution has emerged, and these have been shown to provide a new basis for models of the changing patterns of population and economic activities that shape the landscape. In this paper we make clear the necessarily partial description that any particular model must provide, and show the importance of a multidisciplinary, holistic understanding, linking any particular model to the co-evolution of its environment. In addition, we show how evolutionary processes link the microscopic level of molecules through successive scales of structure and organization ultimately to the biosphere itself, to issues of climatic change, of biomes at the continental scale and atmospheric and oceanic circulation patterns. Some very recent results will be shown which demonstrate that the world climate has already been modified considerably by human activities, particularly agriculture, underlining the vital need to understand better the on-going interaction between human activities and the biosphere.

Models will be described which can link the co-evolution of these multiple scales of organization and change, and which can be used to help to explore the consequences of different possible policies, and in this way to provide information concerning the agendas, risks and issues to be addressed in the 21st Century, as well as pointing to possible policies that may be appropriate. Already models exist which can explore the dynamics of urban development, the patterns of land-use, and the possible environmental impacts of these in the context of a still fast growing population. Such models provide a framework within which questions such as those concerning energy consumption, transportation, social conditions can be explored and agendas and priorities set. Clearly, advances in information and telecommunications technologies present great opportunities for increasing accessibilities without necessarily increasing mobility or energy consumption, and models which can help in assessing their potential impact on development and in their successful implementation are of great value.

Complex system models can also be of great use in exploring the long term implications of the present, increasing, reliance on market systems and economic signals in the allocation of resources and patterns of investment. In particular, complex systems models can explore the effects of the precise regulatory framework within which a market operates, and as a result may be able to suggest ways in which long term, sustainable development can be achieved despite the present short term horizons of the players in market dynamics. In addition, of course, they can illuminate and inform actors about the longer term, and perhaps actually lengthen the time horizon considered by market participants. In short, the insights arising from complex systems models could, hopefully, play a role in expanding the understanding, the conceptual framework and the ethical basis of decision making in the 21st Century.