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14 - Modelling conservation conflicts

from Part III - Approaches to managing conflicts

Published online by Cambridge University Press:  05 May 2015

By
Johannes P. M. Heinonen  and
Justin M. J. Travis
Edited by
Stephen M. Redpath ,
R. J. Gutiérrez ,
Kevin A. Wood  and
Juliette C. Young
Johannes P. M. Heinonen
Affiliation:
University of Aberdeen
Justin M. J. Travis
Affiliation:
University of Aberdeen
Stephen M. Redpath
Affiliation:
University of Aberdeen
R. J. Gutiérrez
Affiliation:
University of Minnesota
Kevin A. Wood
Affiliation:
Bournemouth University
Juliette C. Young
Affiliation:
NERC Centre for Ecology and Hydrology, UK
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Summary

Modelling enables theory and empirical evidence to be brought together to build representations of how real-world systems work and how they are likely to respond to external influences. Models can take many forms, such as simple verbal or written descriptions, flow diagrams, sets of mathematical equations or computer programs. Usually the process begins with the development of a verbal or written description of a real-world system (i.e. a ‘conceptual model’), which subsequently can be translated into a mathematical or computational format (i.e. an ‘implemented model’). This implemented model can then be given appropriate inputs such that outputs, predicting the dynamics of the system of interest, are generated (Edmonds and Hales, 2003; Wilensky and Rand, 2007; Fig. 14.1). The outputs can then be compared to understanding or empirical data related to the behaviour of a natural system and this comparison can result in modification of the conceptual model. This iterative process can make a major contribution to our understanding of how systems work and what may be the crucial drivers of a system (Edmonds, 2000; Fig. 14.1).

It has been argued that the most important goal of modelling is to understand general mechanisms, not to generate specific predictions using models (Grimm, 1999). However, where sufficient, empirically verified, knowledge and understanding of a system exists, models can provide an excellent means for testing how a complex system may respond to different drivers for a natural resource system, and assess the likely responses of a system to alternative possible future management (Frederiksen et al., 2001; Bunnefeld et al., 2011). Importantly, even in cases where knowledge of a system is too limited for modelling to provide robust quantitative predictions, models can still be developed that yield useful qualitative predictions of expected trends and system dynamics (such as population cycles or the risk of extinction), particularly about influential mechanisms of the system.

Models can help us understand where and why ecological conflicts occur. They enable us to identify the main drivers of conflict by simplifying the system to key components that still replicate patterns in the real conflict system.

Type
Chapter
Information
Conflicts in Conservation
Navigating Towards Solutions
 , pp. 195 - 211
Publisher: Cambridge University Press
Print publication year: 2015

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